# argus - Doramagic AI Context Pack

> Positioning: a pre-install experience and judgment asset. It helps the host AI get off to a good start, but it does not mean the project has already been installed, run, or validated.

## Sufficiency Principle

- **Sufficiency over compression**: The AI Context Pack should be sufficient for the host AI to understand the project's value, capability boundaries, entrypoints, risks, and evidence sources before starting work; it may be layered, but it does not aim for the shortest possible summary.
- **Compression policy**: Compress only noise and duplication, never context that affects judgment or the quality of the work.

## How the Host AI Should Use This

You are reading the AI Context Pack that Doramagic compiled for argus. Treat it as pre-work context: help the user understand who it fits, what it can do, how to start, what must be verified after install, and where the risks are. Do not claim that you have already installed, run, or executed the target project.

## Claim Consumption Rules

- **Fact source**: Repo Evidence + Claim/Evidence Graph; the Human Wiki only supplies salience, terminology, and narrative structure.
- **Minimum status for a fact**: `supported`
- `supported`: May be used as a project fact, but the answer must cite the claim_id and evidence path.
- `weak`: Usable only as a low-confidence lead; the user must be asked to keep verifying.
- `inferred`: Usable only for risk notes or open questions; must not be packaged as a project fact.
- `unverified`: Must not be used as fact; state clearly that evidence is insufficient.
- `contradicted`: Must show the conflicting sources and must not force a single version on the user's behalf.

## Who It Fits Best

- **Developers already using host AIs such as Claude/Codex/Cursor/Gemini**: The README or plugin config mentions multiple host AIs. Evidence: `README.md` Claim: `clm_0002` supported 0.86

## What It Can Do

- **Command-Line Startup or Install Flow** (Verify after install): The project documentation contains runnable commands; real use requires running them in a local or host environment. Evidence: `AGENTS.md`, `README.md` Claim: `clm_0001` supported 0.86

## How to Start

- `pip install argus-search && argus search -q "python web frameworks"` Evidence: `README.md` Claim: `clm_0003` supported 0.86
- `pipx install argus-search[mcp]` Evidence: `README.md` Claim: `clm_0004` supported 0.86
- `curl -X POST http://localhost:8000/api/search \` Evidence: `README.md` Claim: `clm_0005` supported 0.86
- `curl -X POST http://localhost:8000/api/extract \` Evidence: `README.md` Claim: `clm_0006` supported 0.86
- `curl -X POST http://localhost:8000/api/recover-url \` Evidence: `README.md` Claim: `clm_0007` supported 0.86
- `curl http://localhost:8000/api/health` Evidence: `README.md` Claim: `clm_0008` supported 0.86
- `curl -H "Authorization: Bearer $ARGUS_ADMIN_API_KEY" \` Evidence: `README.md` Claim: `clm_0009` supported 0.86
- `curl -s https://raw.githubusercontent.com/Khamel83/argus/main/scripts/provision-mcp-client.sh | bash -s local              # this machine; uses local stdio if argus is installed` Evidence: `README.md` Claim: `clm_0010` supported 0.86
- `curl -s https://raw.githubusercontent.com/Khamel83/argus/main/scripts/provision-mcp-client.sh | bash -s user@100.x.x.x    # remote machine` Evidence: `README.md` Claim: `clm_0011` supported 0.86
- `pip install "argus-search[mcp]"         # install from PyPI (with MCP support)` Evidence: `AGENTS.md` Claim: `clm_0012` supported 0.86

## Continue-or-Stop Decision Card

- **Current recommendation**: Needs admin / security approval
- **Why**: Continuing may involve secrets, accounts, external services, or sensitive context; get admin or security approval first.

### 30-Second Read

- **What to do now**: Needs admin / security approval
- **Minimum safe next step**: Run Prompt Preview first; if credentials or an enterprise environment are involved, get approval before trialing
- **Do not trust yet**: Role quality and task fit cannot be trusted directly.
- **Continuing will touch**: Role selection bias, Command execution, Host AI configuration

### What You Can Trust Now

- **Target-audience signal: Developers already using host AIs such as Claude/Codex/Cursor/Gemini** (supported): Backed by a supported claim or project evidence, but that still is not the same as real install results. Evidence: `README.md` Claim: `clm_0002` supported 0.86
- **Capability exists: Command-Line Startup or Install Flow** (supported): You can trust that the project contains signals of this capability; whether it fits your specific task still needs trial or after-install verification. Evidence: `AGENTS.md`, `README.md` Claim: `clm_0001` supported 0.86
- **There are Quick Start / install-command signals** (supported): You can trust that the docs mention a startup or install entrypoint; do not run it directly in your primary environment because of that. Evidence: `README.md` Claim: `clm_0003` supported 0.86

### What You Cannot Trust Yet

- **Role quality and task fit cannot be trusted directly.** (unverified): A role library proves there are many roles; it does not prove each one fits your specific task or that a role produces high-quality results.
- **Do not treat role copy as real execution capability.** (unverified): Before install you can only judge whether the role description and task profile match; you cannot prove it can complete the task inside the host AI.
- **Real output quality cannot be trusted before install.** (unverified): Prompt Preview can only show how it guides you; it cannot prove result quality in the real project.
- **Host AI version compatibility cannot be trusted before install.** (unverified): Host loading rules and version differences across Claude, Cursor, Codex, Gemini, and others must be verified in a real environment.
- **That it will not pollute your existing host AI's behavior cannot be trusted directly.** (inferred): Skill, plugin, and AGENTS/CLAUDE/GEMINI instructions may change the host AI's default behavior. Evidence: `AGENTS.md`, `CLAUDE.md`
- **Safe rollback cannot be assumed by default.** (unverified): Unless the project clearly provides uninstall and recovery instructions, verify in an isolated environment first.
- **After a real install, is it compatible with the user's current host AI version?** (unverified): Compatibility can only be verified in the actual host environment.
- **Does the project's output quality meet the user's specific task?** (unverified): The pre-install preview can only show flow and boundaries; it cannot replace real evaluation.

### What Continuing Will Touch

- **Role selection bias**: The user's judgment about which expert role should handle the task. Why: Picking the wrong role makes the AI answer from the wrong expert perspective, wasting time or misleading decisions.
- **Command execution**: Package managers, network downloads, the local plugin directory, project config, or the user's home directory. Why: Running the very first command can already change your environment; decide whether it is worth running first. Evidence: `AGENTS.md`, `README.md`
- **Host AI configuration**: The plugin, Skill, or rule-loading config of hosts like Claude/Codex/Cursor/Gemini/OpenCode. Why: Host configuration changes how the AI works afterward and may conflict with the user's existing rules. Evidence: `AGENTS.md`, `CLAUDE.md`
- **Local environment or project files**: Install results, plugin caches, project config, or local dependency directories. Why: The write scope and rollback path cannot be proven before install and need isolated verification. Evidence: `AGENTS.md`, `README.md`
- **Environment variables / API keys**: Project entry docs explicitly showing API key, token, secret, or account credential configuration. Why: If a real install needs credentials, use test credentials first and go through a permission/compliance review. Evidence: `AGENTS.md`, `CONTRIBUTING.md`, `LLM-OVERVIEW.md`, `README.md` et al.
- **Host AI context**: The AI Context Pack, Prompt Preview, Skill routing, risk rules, and project facts. Why: Importing context affects the host AI's later judgment, so avoid packaging unverified items as facts.

### Minimum Safe Next Steps

- **Run Prompt Preview first**: Use an interactive trial to verify the task profile and role match first; do not import the whole role library up front. (applies when: Applies to any project, especially when output quality is unknown.)
- **Trial-install only in an isolated directory or a test account**: Avoid letting install commands pollute your primary host AI, real projects, or home directory. (applies when: When there are signals of command execution, plugin config, or local writes.)
- **Back up your host AI configuration first**: Skill, plugin, and rule files may change the default behavior of Claude/Cursor/Codex. (applies when: When there is a plugin manifest, a Skill, or a host rule entrypoint.)
- **Do not use real production credentials**: Once an environment variable / API key enters the host or toolchain, it can create account and compliance risk. (applies when: When environment signals like API, TOKEN, KEY, or SECRET appear.)
- **After install, verify just one minimal task**: Verify loading, compatibility, output quality, and rollback first, then decide whether to use it deeply. (applies when: When moving from a trial into a real workflow.)

### Exit Plan

- **Preserve the pre-install state**: Record the original host config and project state so you can later judge whether it is recoverable.
- **Be ready to remove the host plugin / Skill / rule entrypoint**: If behavior is off after the trial install, you can restore the host AI to its pre-trial state.
- **Keep a record of the original role selection**: If output goes off-topic, you can return to the task-profiling stage and reselect a role instead of pushing on with the wrong one.
- **Record the install commands and written paths**: Without clear uninstall instructions, you at least need to know which directories or configs to clean up manually.
- **Be ready to revoke test API keys or tokens**: If test credentials leak or are misused, you can cut losses quickly.
- **If there is no rollback path, do not enter your primary environment**: No rollback is a blocker before continuing; do not proceed on trust or luck.

## What Can Only Be Previewed

- Explain who the project fits and what it can do
- Demonstrate a typical conversation flow based on project docs
- Help the user decide whether it is worth installing or researching further

## What Must Be Verified After Install

- Actually installing the Skill, plugin, or CLI
- Running scripts, modifying local files, or accessing external services
- Verifying real output quality, performance, and compatibility

## Boundary & Risk Decision Card

- **Mistaking the pre-install preview for a real run**: The user may overestimate how much configuration, permission, and compatibility verification the project has already done. Mitigation: Clearly separate prompt_preview_can_do from runtime_required. Claim: `clm_0014` inferred 0.45
- **Command execution will modify the local environment**: Install commands may write to the user's home directory, the host plugin directory, or project configuration. Mitigation: Run in an isolated environment or a test account first. Evidence: `AGENTS.md`, `README.md` Claim: `clm_0015` supported 0.86
- **To confirm**: After a real install, is it compatible with the user's current host AI version?. Why: Compatibility can only be verified in the actual host environment.
- **To confirm**: Does the project's output quality meet the user's specific task?. Why: The pre-install preview can only show flow and boundaries; it cannot replace real evaluation.
- **To confirm**: Do the install commands require network access, permissions, or global writes?. Why: This affects install risk in both enterprise and personal environments.

## Pre-Work Working Context

### Loading Order

- First read how_to_use.host_ai_instruction to establish the boundaries of this pre-install judgment asset.
- Read claim_graph_summary to confirm facts come from the Claim/Evidence Graph, not the Human Wiki narrative.
- Then read intended_users, capabilities, and quick_start_candidates to judge whether the user is a match.
- When you need to carry out a concrete task, check role_skill_index first, then evidence_index.
- For real install, file modification, network access, performance, or compatibility questions, turn to risk_card and boundaries.runtime_required.

### Task Routes

- **Command-Line Startup or Install Flow**: State that this is an after-install capability first, then give a pre-install checklist. Boundary: Must be verified after a real install or run. Evidence: `AGENTS.md`, `README.md` Claim: `clm_0001` supported 0.86

### Context Scale

- Total files: 146
- Important-file coverage: 40/146
- Evidence index entries: 75
- Role / Skill entries: 26

### Handling Insufficient Evidence

- **missing_evidence**: State that evidence is insufficient and ask the user for the target file, a README section, or after-install verification records; do not fill in facts.
- **out_of_scope_request**: State that the task is beyond the current AI Context Pack's evidence scope and suggest the user check the Human Manual or verify after a real install.
- **runtime_request**: Provide a pre-install checklist and command sources, but do not run commands for the user or claim they have been run.
- **source_conflict**: Show the conflicting sources side by side, mark them as unverified, and do not force a single version.

## Prompt Recipes

### Fit assessment

- Goal: Judge whether this project fits the user's current task.
- Expected output: A fit conclusion, key reasons, evidence citations, what can be previewed before install, what must be verified after install, and a next-step recommendation.

```text
Based on the AI Context Pack for argus, ask me 3 necessary questions first, then judge whether it fits my task. The answer must cover: who it fits, what it can do, what it cannot do, whether it is worth installing, and where the evidence comes from. Every project fact must cite evidence_refs, source_paths, or a claim_id.
```

### Pre-install experience

- Goal: Let the user feel the core workflow before installing, while avoiding packaging the preview as real capability or a marketing promise.
- Expected output: An experience script with boundary labels, an after-install verification checklist, and a cautious recommendation; with no real-run promises or strong marketing language.

```text
Treat argus as a pre-install experience asset, not an already-installed tool or a real runtime environment.

Output exactly four parts:
1. Ask me 3 necessary questions first.
2. Give an "experience script": use the three labels [Previewable before install], [Must verify after install], and [Insufficient evidence] to show how it might guide the workflow.
3. Give an after-install verification checklist: list which capabilities can only be confirmed after a real install, real host loading, and a real project run.
4. Give a cautious recommendation: only "worth researching/trialing further", "add information before deciding", or "not recommended to continue"; do not endorse the project.

Hard boundaries:
- Do not claim you have installed, run, executed tests, modified files, or produced real results.
- Do not write promise-like phrasing such as "auto-adapts", "guarantees passing", "perfect fit", or "strongly recommend installing".
- If you describe how it works after install, you must use a conditional such as "if installed successfully and the host loads the Skill correctly, it might...".
- The experience script may only be written as "example lines / hypothetical flow": use "might ask / might suggest / might show", not "has written, has generated, has passed, is running, is generating".
- Prompt Preview does not hand out install commands; if the user is ready to trial, only prompt them to read Quick Start and the Risk Card first and to verify in an isolated environment.
- Every project fact must come from a supported claim, evidence_refs, or source_paths; inferred/unverified items can only be risks or open questions.

```

### Role / Skill selection

- Goal: Pick the best-matching asset from the project's roles or Skills.
- Expected output: A list of candidate roles or Skills, each with an applicable scenario, evidence paths, risk boundary, and whether after-install verification is needed.

```text
Read role_skill_index and recommend 3-5 of the most relevant roles or Skills for my target task. For each recommendation, state the applicable scenario, likely output, risk boundary, and evidence_refs.
```

### Risk pre-check

- Goal: Identify environment, permission, rule-conflict, and quality risks before installing or adopting.
- Expected output: A checklist of environment, permission, dependency, license, host-conflict, quality risk, and unknown items.

```text
Based on risk_card, boundaries, and quick_start_candidates, give me a pre-install risk pre-check list. Do not run commands for me; only explain what I should check, why, and what impact a failure would have.
```

### Host AI kickoff instruction

- Goal: Turn the project context into a host AI instruction for the start of a conversation.
- Expected output: A pre-work instruction with clear boundaries and clear evidence citations, suitable to copy to a host AI.

```text
Based on the AI Context Pack for argus, generate a pre-work instruction I can paste to my host AI. This instruction must obey not_runtime=true and must not claim the project has been installed, run, or produced real results.
```

## Role / Skill Index

- Indexed 26 role / Skill / project-doc entries.

- **Argus Documentation** (project_doc): Top-level entry points live at the repo root: Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `docs/README.md`
- **Argus** (project_doc): ! Python 3.11+ https://img.shields.io/badge/Python-3.11+-blue https://www.python.org/downloads/ ! PyPI Version https://img.shields.io/pypi/v/argus-search https://pypi.org/project/argus-search/ ! PyPI Downloads https://img.shields.io/pepy/dt/argus-search https://pepy.tech/projects/argus-search ! License: MIT https://img.shields.io/badge/license-MIT-green LICENSE ! CI https://github.com/Khamel83/argus/actions/workflow… Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `README.md`
- **Argus examples** (project_doc): Minimal runnable examples. Every Python example here works with zero API keys — Argus falls back to DuckDuckGo when no other providers are configured. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `examples/README.md`
- **AGENTS.md — Argus** (project_doc): What this file is for: the canonical guide for AI coding agents working in this repository Claude Code, Codex, Cursor, Copilot, OpenCode, and friends . Human contributors should start with CONTRIBUTING.md CONTRIBUTING.md ; background on the project lives in CONTEXT.md CONTEXT.md and README.md README.md . CLAUDE.md CLAUDE.md is a short pointer back here with Claude-Code-specific notes. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `AGENTS.md`
- **Claude Code — Argus** (project_doc): What this file is for: Claude Code's entry point into this repo. The canonical guide for any AI coding agent Claude Code, Codex, Cursor, Copilot, OpenCode lives in AGENTS.md AGENTS.md — Claude Code reads both, but the content lives there. Keep this file short. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `CLAUDE.md`
- **Providers and Extractors** (project_doc): This page is a fuller reference for the search providers and content extractors behind Argus. For the short version with budgets and signup links see the Providers section of ../README.md ../README.md . Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `docs/providers.md`
- **Troubleshooting** (project_doc): If you can't find your issue here, run argus doctor and include its output when opening a bug report https://github.com/Khamel83/argus/issues/new?template=bug report.yml . Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `docs/troubleshooting.md`
- **Contributing to Argus** (project_doc): Argus development is standardized on Python 3.12. The published package still supports Python 3.11+, but local repo work, CI parity, and release verification should use the commands below. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `CONTRIBUTING.md`
- **Changelog** (project_doc): All notable changes to this project will be documented in this file. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `CHANGELOG.md`
- **Argus Publicity — Step-by-Step Instructions** (project_doc): Argus Publicity — Step-by-Step Instructions Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `docs/PUBLICITY-CHECKLIST.md`
- **Dashboard Design System** (project_doc): Argus uses a documented design system for its dashboard UI. The canonical source is .interface-design/system.md ../.interface-design/system.md at the repo root. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `docs/dashboard-design.md`
- **MCP Client Setup** (project_doc): Argus supports local stdio MCP and remote streamable HTTP MCP. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `docs/mcp-clients.md`
- **Releasing Argus** (project_doc): The repository version and the published package version are separate until a release is published. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `docs/releasing.md`
- **Obscura: What to Take for Argus** (project_doc): Source: https://github.com/h4ckf0r0day/obscura Date: 2026-04-24 Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `docs/research/obscura/research.md`
- **Argus Retrieval Platform Roadmap** (project_doc): Summary - Reposition Argus as a retrieval platform for agents: search, recover, capture, summarize, and persist web knowledge. - Internalize the docs-cache pattern into Argus itself. Do not require a sibling repository. - Default runtime corpus output to a global user data root resolved via platformdirs , overrideable with ARGUS DATA ROOT . - Make runtime paths visible through CLI, HTTP, and MCP. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `docs/roadmaps/argus-retrieval-platform.md`
- **Multi-Egress Worker Implementation Plan** (project_doc): Multi-Egress Worker Implementation Plan Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `docs/superpowers/plans/2026-05-22-multi-egress-worker.md`
- **Argus Simple Dashboard Design** (project_doc): Date: 2026-05-05 Status: Approved Deciders: khamel83, Gemini CLI Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `docs/superpowers/specs/2026-05-05-argus-dashboard-design.md`
- **Free Mode + Dashboard Call Count Fix** (project_doc): Free Mode + Dashboard Call Count Fix Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `docs/superpowers/specs/2026-05-22-free-mode-dashboard-fix-design.md`
- **Multi-Egress Worker Architecture** (project_doc): Date: 2026-05-22 Status: Approved Motivation: Argus runs on homelab Spectrum residential, 23.241.236.110 . Yahoo Search blocks Spectrum IP ranges. oci-dev Oracle, 141.148.146.79 can reach Yahoo. Rather than hardcoding "Yahoo → oci-dev," the system should be state-driven: declare available machines, probe what each can reach, route providers through whichever egress works — and update automatically when reachability… Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `docs/superpowers/specs/2026-05-22-multi-egress-worker-design.md`
- **Design System — Argus Dashboard** (project_doc): Personality: Precision & Density Foundation: cool gray-950 base — terminal dark, not blue-tinted Depth: borders-only Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `.interface-design/system.md`
- **Contributor Covenant Code of Conduct** (project_doc): Contributor Covenant Code of Conduct Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `CODE_OF_CONDUCT.md`
- **Context** (project_doc): What this file is for: background, glossary, and architectural decisions that don't belong in README.md README.md user-facing or AGENTS.md AGENTS.md AI-agent conventions . Add entries here when a term or design choice keeps coming up in reviews or issues. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `CONTEXT.md`
- **LLM Overview — argus** (project_doc): What this file is for: a machine-generated snapshot of repo state recent commits, env vars in use, top-level layout intended for LLM agents that want a quick situational summary without crawling the whole repo. It is regenerated by a daily cron — do not hand-edit this file , your changes will be overwritten. For the curated AI-agent guide see AGENTS.md AGENTS.md ; for user docs see README.md README.md ; for the stru… Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `LLM-OVERVIEW.md`
- **Security Policy** (project_doc): Only the latest release is actively maintained. Check PyPI https://pypi.org/project/argus-search/ for the current version. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `SECURITY.md`
- **MCP quickstart** (project_doc): The fastest way to wire Argus into an MCP-aware client. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `examples/mcp_quickstart.md`
- **Handoff: Multi-Egress Worker Architecture** (project_doc): Handoff: Multi-Egress Worker Architecture Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `thoughts/shared/handoffs/2026-05-22-multi-egress-worker-handoff.md`

## Evidence Index

- Indexed 75 evidence entries.

- **Argus Documentation** (documentation): Top-level entry points live at the repo root: Evidence: `docs/README.md`
- **Argus** (documentation): ! Python 3.11+ https://img.shields.io/badge/Python-3.11+-blue https://www.python.org/downloads/ ! PyPI Version https://img.shields.io/pypi/v/argus-search https://pypi.org/project/argus-search/ ! PyPI Downloads https://img.shields.io/pepy/dt/argus-search https://pepy.tech/projects/argus-search ! License: MIT https://img.shields.io/badge/license-MIT-green LICENSE ! CI https://github.com/Khamel83/argus/actions/workflows/ci.yml/badge.svg https://github.com/Khamel83/argus/actions/workflows/ci.yml ! MCP Registry https://img.shields.io/badge/MCP-Registry-blue https://registry.modelcontextprotocol.io/servers/io.github.Khamel83/argus ! Docker https://img.shields.io/badge/ghcr.io-khamel83%2Fargus-blu… Evidence: `README.md`
- **Argus examples** (documentation): Minimal runnable examples. Every Python example here works with zero API keys — Argus falls back to DuckDuckGo when no other providers are configured. Evidence: `examples/README.md`
- **AGENTS.md — Argus** (documentation): What this file is for: the canonical guide for AI coding agents working in this repository Claude Code, Codex, Cursor, Copilot, OpenCode, and friends . Human contributors should start with CONTRIBUTING.md CONTRIBUTING.md ; background on the project lives in CONTEXT.md CONTEXT.md and README.md README.md . CLAUDE.md CLAUDE.md is a short pointer back here with Claude-Code-specific notes. Evidence: `AGENTS.md`
- **Claude Code — Argus** (documentation): What this file is for: Claude Code's entry point into this repo. The canonical guide for any AI coding agent Claude Code, Codex, Cursor, Copilot, OpenCode lives in AGENTS.md AGENTS.md — Claude Code reads both, but the content lives there. Keep this file short. Evidence: `CLAUDE.md`
- **Providers and Extractors** (documentation): This page is a fuller reference for the search providers and content extractors behind Argus. For the short version with budgets and signup links see the Providers section of ../README.md ../README.md . Evidence: `docs/providers.md`
- **Troubleshooting** (documentation): If you can't find your issue here, run argus doctor and include its output when opening a bug report https://github.com/Khamel83/argus/issues/new?template=bug report.yml . Evidence: `docs/troubleshooting.md`
- **Contributing to Argus** (documentation): Argus development is standardized on Python 3.12. The published package still supports Python 3.11+, but local repo work, CI parity, and release verification should use the commands below. Evidence: `CONTRIBUTING.md`
- **License** (source_file): Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files the "Software" , to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: Evidence: `LICENSE`
- **Changelog** (documentation): All notable changes to this project will be documented in this file. Evidence: `CHANGELOG.md`
- **Argus Publicity — Step-by-Step Instructions** (documentation): Argus Publicity — Step-by-Step Instructions Evidence: `docs/PUBLICITY-CHECKLIST.md`
- **Dashboard Design System** (documentation): Argus uses a documented design system for its dashboard UI. The canonical source is .interface-design/system.md ../.interface-design/system.md at the repo root. Evidence: `docs/dashboard-design.md`
- **MCP Client Setup** (documentation): Argus supports local stdio MCP and remote streamable HTTP MCP. Evidence: `docs/mcp-clients.md`
- **Releasing Argus** (documentation): The repository version and the published package version are separate until a release is published. Evidence: `docs/releasing.md`
- **Obscura: What to Take for Argus** (documentation): Source: https://github.com/h4ckf0r0day/obscura Date: 2026-04-24 Evidence: `docs/research/obscura/research.md`
- **Argus Retrieval Platform Roadmap** (documentation): Summary - Reposition Argus as a retrieval platform for agents: search, recover, capture, summarize, and persist web knowledge. - Internalize the docs-cache pattern into Argus itself. Do not require a sibling repository. - Default runtime corpus output to a global user data root resolved via platformdirs , overrideable with ARGUS DATA ROOT . - Make runtime paths visible through CLI, HTTP, and MCP. Evidence: `docs/roadmaps/argus-retrieval-platform.md`
- **Multi-Egress Worker Implementation Plan** (documentation): Multi-Egress Worker Implementation Plan Evidence: `docs/superpowers/plans/2026-05-22-multi-egress-worker.md`
- **Argus Simple Dashboard Design** (documentation): Date: 2026-05-05 Status: Approved Deciders: khamel83, Gemini CLI Evidence: `docs/superpowers/specs/2026-05-05-argus-dashboard-design.md`
- **Free Mode + Dashboard Call Count Fix** (documentation): Free Mode + Dashboard Call Count Fix Evidence: `docs/superpowers/specs/2026-05-22-free-mode-dashboard-fix-design.md`
- **Multi-Egress Worker Architecture** (documentation): Date: 2026-05-22 Status: Approved Motivation: Argus runs on homelab Spectrum residential, 23.241.236.110 . Yahoo Search blocks Spectrum IP ranges. oci-dev Oracle, 141.148.146.79 can reach Yahoo. Rather than hardcoding "Yahoo → oci-dev," the system should be state-driven: declare available machines, probe what each can reach, route providers through whichever egress works — and update automatically when reachability changes. Evidence: `docs/superpowers/specs/2026-05-22-multi-egress-worker-design.md`
- **Init** (source_file): version = "1.6.2" Evidence: `argus/__init__.py`
- **Basic Search** (source_file): async def main - None ⋮---- broker = create broker ⋮---- response = await broker.search ⋮---- provider = result.provider.value if hasattr result.provider, "value" else result.provider Evidence: `examples/basic_search.py`
- **Research Pack** (source_file): async def main - None ⋮---- broker = create broker service = WorkflowService broker ⋮---- result = await service.build research pack Evidence: `examples/research_pack.py`
- **Pyproject** (source_file): build-system requires = "setuptools =68.0", "wheel" build-backend = "setuptools.build meta" Evidence: `pyproject.toml`
- **Main** (source_file): logger = get logger "api" ⋮---- def build rate limiter - RateLimiter ⋮---- auth = AuthConfig.from env ⋮---- current = broker factory = broker factory or create broker ⋮---- def get broker - SearchBroker ⋮---- current = factory ⋮---- current: WorkflowService None = None ⋮---- def get workflows - WorkflowService ⋮---- current = WorkflowService broker provider ⋮---- auth config = AuthConfig.from env ⋮---- @asynccontextmanager async def lifespan with probes app: FastAPI ⋮---- b = app.state.get broker ⋮---- probe task: asyncio.Task None = None ⋮---- async def run probes background - None ⋮---- cfg = get config ⋮---- probe task = asyncio.create task run probes background ⋮---- app = FastAPI ⋮----… Evidence: `argus/api/main.py`
- **Rate Limit** (source_file): logger = get logger "api.rate limit" ⋮---- class RateLimiter ⋮---- now = time.time cutoff = now - self. window ⋮---- window = self. requests client ip path ⋮---- retry after = int window 0 + self. window - now + 1 ⋮---- remaining = self. max requests - len window Evidence: `argus/api/rate_limit.py`
- **Routes Admin** (source_file): router = APIRouter prefix="/admin" ⋮---- def get broker request: Request - SearchBroker ⋮---- def get workflows request: Request - WorkflowService ⋮---- @router.post "/test-provider" async def test provider req: ProviderTestRequest, broker: SearchBroker = Depends get broker ⋮---- pname = ProviderName req.provider ⋮---- provider = broker. providers.get pname ⋮---- query = SearchQuery query=req.query, mode=SearchMode.DISCOVERY, max results=3 ⋮---- @router.get "/paths", response model=PathsResponse async def corpus paths workflows: WorkflowService = Depends get workflows Evidence: `argus/api/routes_admin.py`
- **Routes Dashboard** (source_file): router = APIRouter ⋮---- TEMPLATES DIR = Path file .parent / "templates" templates = Jinja2Templates directory=str TEMPLATES DIR ⋮---- ROOT PATH = os.environ.get "ARGUS ROOT PATH", "" .rstrip "/" ⋮---- COOKIE NAME = "argus dash" COOKIE MAX AGE = 86400 ⋮---- def is https request: Request - bool ⋮---- proto = request.headers.get "x-forwarded-proto", "" .lower ⋮---- def check auth request: Request - bool ⋮---- auth = request.app.state.auth config ⋮---- cookie val = request.cookies.get COOKIE NAME, "" ⋮---- def get broker request: Request - SearchBroker ⋮---- def build budget state broker: SearchBroker - list dict ⋮---- """Build per-provider budget cards. Only includes providers with a budget s… Evidence: `argus/api/routes_dashboard.py`
- **Routes Extract** (source_file): router = APIRouter ⋮---- @router.post "/extract", response model=ExtractResponse async def extract req: ExtractRequest ⋮---- result = await extract url req.url, domain=req.domain, mode=req.mode cr = result.completeness result ⋮---- @router.post "/assess-content", response model=AssessContentResponse async def assess content req: AssessContentRequest ⋮---- result = assess completeness req.text, req.url ⋮---- @router.get "/admin/cookies/health" async def cookie health Evidence: `argus/api/routes_extract.py`
- **Routes Search** (source_file): router = APIRouter ⋮---- def get broker request: Request - SearchBroker ⋮---- def to response resp, include attribution: bool = False - SearchResponse ⋮---- @router.post "/search", response model=SearchResponse async def search req: SearchRequest, broker: SearchBroker = Depends get broker ⋮---- query = SearchQuery ⋮---- response = to response resp, include attribution=req.include attribution ⋮---- resp = await broker.search query, compute attribution=req.include attribution ⋮---- @router.post "/recover-url", response model=SearchResponse async def recover url req: RecoverUrlRequest, broker: SearchBroker = Depends get broker ⋮---- query parts = req.url ⋮---- search query = SearchQuery ⋮----… Evidence: `argus/api/routes_search.py`
- **Init** (source_file): all = "rrf attribution", "shapley sample" Evidence: `argus/attribution/__init__.py`
- **Init** (source_file): all = "SearchBroker", "create broker" Evidence: `argus/broker/__init__.py`
- **Valyu uses USD units** (source_file): logger = get logger "cli" ⋮---- STATUS DISPLAY = { ⋮---- def run coro ⋮---- loop = asyncio.get running loop ⋮---- loop = None ⋮---- def emit json payload ⋮---- def workflow to dict result ⋮---- def print workflow result result, as json: bool ⋮---- @click.group @click.version option version= version , prog name="argus" def cli ⋮---- @cli.command @click.option "--json", "as json", is flag=True, help="Output as JSON" def paths as json ⋮---- payload = describe corpus paths ⋮---- @click.option "--max-results", "-n", default=10, help="Max results" @click.option "--providers", "-p", multiple=False, help="Override providers comma-separated " @click.option "--session", "-s", default=None, help="Sess… Evidence: `argus/cli/main.py`
- **Init** (source_file): all = Evidence: `argus/corpus/__init__.py`
- **Init** (source_file): all = Evidence: `argus/extraction/__init__.py`
- **Prune old timestamps** (source_file): logger = get logger "extraction.rate limit" ⋮---- class DomainRateLimiter ⋮---- def init self, max requests: int = 10, window seconds: int = 60 ⋮---- @staticmethod def extract domain url: str - str ⋮---- def is allowed self, url: str - tuple bool, int ⋮---- """Check if extracting from this URL's domain is allowed. Returns allowed, retry after seconds . """ domain = self. extract domain url ⋮---- now = time.time cutoff = now - self. window ⋮---- Prune old timestamps window = self. requests domain ⋮---- retry after = int window 0 + self. window - now + 1 ⋮---- remaining = self. max requests - len window ⋮---- def clear self - None Evidence: `argus/extraction/rate_limit.py`
- **Init** (source_file): all = "serve mcp" Evidence: `argus/mcp/__init__.py`
- **Init** (source_file): all = "get session", "get session factory", "init db", "persist search" Evidence: `argus/persistence/__init__.py`
- **Init** (source_file): all = "BaseProvider" Evidence: `argus/providers/__init__.py`
- **Base** (source_file): class BaseProvider ABC ⋮---- @property @abstractmethod def name self - ProviderName ⋮---- @abstractmethod def is available self - bool ⋮---- @abstractmethod def status self - ProviderStatus ⋮---- @abstractmethod async def search self, query: SearchQuery - tuple List SearchResult , ProviderTrace Evidence: `argus/providers/base.py`
- **Brave** (source_file): logger = get logger "providers.brave" ⋮---- BRAVE API BASE = "https://api.search.brave.com/res/v1/web/search" ⋮---- class BraveProvider BaseProvider ⋮---- def init self, config: ProviderConfig ⋮---- @property def name self - ProviderName ⋮---- def is available self - bool ⋮---- def status self - ProviderStatus ⋮---- async def search self, query: SearchQuery - Tuple List SearchResult , ProviderTrace ⋮---- start = time.monotonic ⋮---- headers = { params = {"q": query.query, "count": query.max results} ⋮---- resp = await client.get BRAVE API BASE, params=params, headers=headers ⋮---- data = resp.json ⋮---- web results = data.get "web", {} .get "results", results = self. normalize web results l… Evidence: `argus/providers/brave.py`
- **Duckduckgo** (source_file): logger = get logger "providers.duckduckgo" ⋮---- class DuckDuckGoProvider BaseProvider ⋮---- def init self ⋮---- def check available self - bool ⋮---- @property def name self - ProviderName ⋮---- def is available self - bool ⋮---- def status self - ProviderStatus ⋮---- async def search self, query: SearchQuery - Tuple List SearchResult , ProviderTrace ⋮---- start = time.monotonic ⋮---- ddgs = DDGS raw results = list ddgs.text query.query, max results=query.max results results = self. normalize raw results latency ms = int time.monotonic - start 1000 ⋮---- trace = ProviderTrace ⋮---- def normalize self, raw results: list - List SearchResult ⋮---- results = ⋮---- url = item.get "href", "" ⋮--… Evidence: `argus/providers/duckduckgo.py`
- **Exa** (source_file): logger = get logger "providers.exa" ⋮---- EXA API BASE = "https://api.exa.ai/search" ⋮---- class ExaProvider BaseProvider ⋮---- def init self, config: ProviderConfig ⋮---- @property def name self - ProviderName ⋮---- def is available self - bool ⋮---- def status self - ProviderStatus ⋮---- async def search self, query: SearchQuery - Tuple List SearchResult , ProviderTrace ⋮---- start = time.monotonic ⋮---- headers = { payload = { ⋮---- resp = await client.post EXA API BASE, json=payload, headers=headers ⋮---- data = resp.json ⋮---- raw results = data.get "results", results = self. normalize raw results latency ms = int time.monotonic - start 1000 ⋮---- trace = ProviderTrace ⋮---- def normal… Evidence: `argus/providers/exa.py`
- **Github** (source_file): logger = get logger "providers.github" ⋮---- GITHUB API BASE = "https://api.github.com/search/repositories" GITHUB CODE BASE = "https://api.github.com/search/code" ⋮---- class GitHubProvider BaseProvider ⋮---- def init self, config: ProviderConfig ⋮---- @property def name self - ProviderName ⋮---- def is available self - bool ⋮---- def status self - ProviderStatus ⋮---- async def search self, query: SearchQuery - Tuple List SearchResult , ProviderTrace ⋮---- start = time.monotonic headers = { ⋮---- params = { ⋮---- resp = await client.get GITHUB API BASE, params=params, headers=headers ⋮---- latency ms = int time.monotonic - start 1000 trace = ProviderTrace ⋮---- data = resp.json ⋮---- item… Evidence: `argus/providers/github.py`
- **Init** (source_file): all = "SessionStore", "Session", "QueryRecord" Evidence: `argus/sessions/__init__.py`
- **Init** (source_file): all = Evidence: `argus/workflows/__init__.py`
- **Design System — Argus Dashboard** (documentation): Personality: Precision & Density Foundation: cool gray-950 base — terminal dark, not blue-tinted Depth: borders-only Evidence: `.interface-design/system.md`
- **Contributor Covenant Code of Conduct** (documentation): Contributor Covenant Code of Conduct Evidence: `CODE_OF_CONDUCT.md`
- **Context** (documentation): What this file is for: background, glossary, and architectural decisions that don't belong in README.md README.md user-facing or AGENTS.md AGENTS.md AI-agent conventions . Add entries here when a term or design choice keeps coming up in reviews or issues. Evidence: `CONTEXT.md`
- **LLM Overview — argus** (documentation): What this file is for: a machine-generated snapshot of repo state recent commits, env vars in use, top-level layout intended for LLM agents that want a quick situational summary without crawling the whole repo. It is regenerated by a daily cron — do not hand-edit this file , your changes will be overwritten. For the curated AI-agent guide see AGENTS.md AGENTS.md ; for user docs see README.md README.md ; for the structured tool/CLI surface see llms.txt llms.txt and llms-full.txt llms-full.txt . Evidence: `LLM-OVERVIEW.md`
- **Security Policy** (documentation): Only the latest release is actively maintained. Check PyPI https://pypi.org/project/argus-search/ for the current version. Evidence: `SECURITY.md`
- **MCP quickstart** (documentation): The fastest way to wire Argus into an MCP-aware client. Evidence: `examples/mcp_quickstart.md`
- **Handoff: Multi-Egress Worker Architecture** (documentation): Handoff: Multi-Egress Worker Architecture Evidence: `thoughts/shared/handoffs/2026-05-22-multi-egress-worker-handoff.md`
- **Repomix.Config** (structured_config): { "$schema": "https://repomix.com/schemas/latest/schema.json", "output": { "filePath": "docs/LLM-OVERVIEW.md", "style": "markdown", "compress": true, "removeComments": true, "removeEmptyLines": true, "topFilesLength": 20, "fileSummary": true, "directoryStructure": true, "files": true, "parsableStyle": true }, "include": "argus/ / " , "ignore": { "useGitignore": true, "useDefaultPatterns": true, "customPatterns": " .pyc", " pycache /", " .egg-info/", ".venv/", "tests/" }, "security": { "enableSecurityCheck": false } } Evidence: `repomix.config.json`
- **Server** (structured_config): { "$schema": "https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json", "name": "io.github.Khamel83/argus", "title": "Argus Retrieval", "description": "Multi-provider search broker for AI agents: 14 providers, 12-step extraction, retrieval workflows.", "repository": { "url": "https://github.com/Khamel83/argus", "source": "github" }, "version": "1.6.2", "packages": { "registryType": "pypi", "registryBaseUrl": "https://pypi.org", "identifier": "argus-search", "version": "1.6.2", "runtimeHint": "uvx", "transport": { "type": "stdio" }, "environmentVariables": { "name": "ARGUS WOLFRAM API KEY", "description": "WolframAlpha App ID 2,000 free computed-answer queries/month ", "… Evidence: `server.json`
- **VCS** (source_file): Python pycache / .py cod .egg-info/ dist/ build/ .eggs/ .egg Evidence: `.dockerignore`
- **Argus core** (source_file): Argus core ARGUS ENV=development ARGUS LOG LEVEL=INFO Evidence: `.env.example`
- **Python** (source_file): Python pycache / .py cod .egg-info/ dist/ build/ .eggs/ .egg Evidence: `.gitignore`
- **.python-version** (source_file): 3.12 Evidence: `.python-version`
- **Argus reverse proxy — automatic HTTPS via Let's Encrypt.** (source_file): Argus reverse proxy — automatic HTTPS via Let's Encrypt. Usage: 1. Set ARGUS DOMAIN and ACME EMAIL in .env 2. docker compose --profile proxy up -d OR: caddy run --config Caddyfile if running Argus directly, not in Docker Cloudflare users: - SSL/TLS mode must be "Full" or "Full strict " in the Cloudflare dashboard. - "Full strict " requires a Cloudflare Origin Certificate installed on the machine free, valid 15 years . Caddy's Let's Encrypt cert also works for "Full strict ". - Caddy automatically renews the Let's Encrypt cert every 60 days. Non-Docker Argus runs as a systemd service on port 8005 : Replace argus:8000 below with localhost:8005 or whatever ARGUS PORT is set to . Evidence: `Caddyfile`
- The remaining 15 evidence entries are in `AI_CONTEXT_PACK.json` or `EVIDENCE_INDEX.json`.

## Rules the Host AI Must Follow

- **Treat this asset as pre-work context, not a runtime environment.**: The AI Context Pack contains only an evidence-backed understanding of the project, not the project's executable state. Evidence: `docs/README.md`, `README.md`, `examples/README.md`
- **When answering the user, distinguish what can be previewed from what can only be verified after install.**: The consumer value of the pre-install experience comes from reducing bad installs and misjudgments, not from pretending to be a real run. Evidence: `docs/README.md`, `README.md`, `examples/README.md`

## Questions the User Should Answer First

- Which host AI or local environment do you plan to use it in?
- Do you just want to experience the workflow first, or are you ready to actually install?
- What matters most to you: install cost, output quality, or conflicts with your existing rules?

## Acceptance Checks

- Every capability claim can be traced back to a file path in evidence_refs.
- AI_CONTEXT_PACK.md does not package previews as a real run.
- The user can understand who it fits, what it can do, how to start, and the risk boundaries within 3 minutes.

---

## Doramagic Context Augmentation

The following sections strengthen the repository context for a host AI. Human Manual data is a reading route, and pitfall notes become operating constraints.

## Human Manual Outline

Usage rule: this is only a reading route and salience signal, not factual authority. Concrete claims must still return to repo evidence or Claim Graph.

Host AI hard rules:
- Do not treat page titles, section order, summaries, or importance values as factual project evidence.
- When explaining the Human Manual outline, state that it is only a reading route or salience signal.
- Capability, installation, compatibility, runtime state, and risk claims must cite repo evidence, source paths, or Claim Graph.

- **Overview**: importance `high`
  - source_paths: README.md, pyproject.toml
- **Providers**: importance `high`
  - source_paths: argus/providers/__init__.py, argus/providers/base.py, argus/providers/brave.py, argus/providers/duckduckgo.py, argus/providers/exa.py
- **Api**: importance `high`
  - source_paths: argus/api/__init__.py, argus/api/main.py, argus/api/rate_limit.py, argus/api/routes_admin.py, argus/api/routes_dashboard.py
- **Cli**: importance `high`
  - source_paths: argus/cli/__init__.py, argus/cli/main.py

## Repo Inspection Evidence

- repo_clone_verified: true
- repo_inspection_verified: true
- repo_commit: `f704e1c779069a36c1ac9408511bdbf41df16d58`
- inspected_files: `Dockerfile`, `README.md`, `docker-compose.yml`, `pyproject.toml`, `uv.lock`, `docs/PUBLICITY-CHECKLIST.md`, `docs/README.md`, `docs/dashboard-design.md`, `docs/mcp-clients.md`, `docs/providers.md`, `docs/releasing.md`, `docs/research/obscura/research.md`, `docs/roadmaps/argus-retrieval-platform.md`, `docs/superpowers/plans/2026-05-22-multi-egress-worker.md`, `docs/superpowers/specs/2026-05-05-argus-dashboard-design.md`, `docs/superpowers/specs/2026-05-22-free-mode-dashboard-fix-design.md`, `docs/superpowers/specs/2026-05-22-multi-egress-worker-design.md`, `docs/troubleshooting.md`, `examples/README.md`, `examples/basic_search.py`

Host AI hard rules:
- Without repo_clone_verified=true, do not claim that the source code has been read.
- Without repo_inspection_verified=true, do not write README, docs, or package-file conclusions as facts.
- Without quick_start_verified=true, do not claim that the Quick Start path has run successfully.

## Doramagic Pitfall Constraints

These rules come from Doramagic discovery, validation, or compilation findings. The host AI must treat them as operating constraints, not background notes.

### Constraint 1: Security or permission risk requires verification

- Trigger: Developers should check this security_permissions risk before relying on the project: Escalation: argus#12 deployment requires manual SSH access
- Host AI rule: Before packaging this project, run the relevant install/config/quickstart check for: Escalation: argus#12 deployment requires manual SSH access. Context: Observed when using python, docker
- Why it matters: Developers may expose sensitive permissions or credentials: Escalation: argus#12 deployment requires manual SSH access
- Evidence: failure_mode_cluster:github_issue | https://github.com/Khamel83/argus/issues/13
- Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it.

### Constraint 2: Security or permission risk requires verification

- Trigger: Developers should check this security_permissions risk before relying on the project: Multi-egress worker: code complete, deployment pending
- Host AI rule: Before packaging this project, run the relevant install/config/quickstart check for: Multi-egress worker: code complete, deployment pending. Context: Observed when using node, python, docker, linux
- Why it matters: Developers may expose sensitive permissions or credentials: Multi-egress worker: code complete, deployment pending
- Evidence: failure_mode_cluster:github_issue | https://github.com/Khamel83/argus/issues/12
- Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it.

### Constraint 3: Installation risk requires verification

- Trigger: Developers should check this installation risk before relying on the project: [Feature] - Tool Hive
- Host AI rule: Before packaging this project, run the relevant install/config/quickstart check for: [Feature] - Tool Hive. Context: Source discussion did not expose a precise runtime context.
- Why it matters: Developers may fail before the first successful local run: [Feature] - Tool Hive
- Evidence: failure_mode_cluster:github_issue | https://github.com/Khamel83/argus/issues/15
- Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it.

### Constraint 4: Installation risk requires verification

- Trigger: Developers should check this installation risk before relying on the project: v1.3.0
- Host AI rule: Before packaging this project, run the relevant install/config/quickstart check for: v1.3.0. Context: Observed when using python
- Why it matters: Upgrade or migration may change expected behavior: v1.3.0
- Evidence: failure_mode_cluster:github_release | https://github.com/Khamel83/argus/releases/tag/v1.3.0
- Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it.

### Constraint 5: Installation risk requires verification

- Trigger: Developers should check this installation risk before relying on the project: v1.3.1
- Host AI rule: Before packaging this project, run the relevant install/config/quickstart check for: v1.3.1. Context: Observed when using python, docker
- Why it matters: Upgrade or migration may change expected behavior: v1.3.1
- Evidence: failure_mode_cluster:github_release | https://github.com/Khamel83/argus/releases/tag/v1.3.1
- Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it.

### Constraint 6: Installation risk requires verification

- Trigger: Developers should check this installation risk before relying on the project: v1.3.3
- Host AI rule: Before packaging this project, run the relevant install/config/quickstart check for: v1.3.3. Context: Observed during installation or first-run setup.
- Why it matters: Upgrade or migration may change expected behavior: v1.3.3
- Evidence: failure_mode_cluster:github_release | https://github.com/Khamel83/argus/releases/tag/v1.3.3
- Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it.

### Constraint 7: Installation risk requires verification

- Trigger: Developers should check this installation risk before relying on the project: v1.4.0
- Host AI rule: Before packaging this project, run the relevant install/config/quickstart check for: v1.4.0. Context: Observed when using python
- Why it matters: Upgrade or migration may change expected behavior: v1.4.0
- Evidence: failure_mode_cluster:github_release | https://github.com/Khamel83/argus/releases/tag/v1.4.0
- Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it.

### Constraint 8: Installation risk requires verification

- Trigger: Developers should check this installation risk before relying on the project: v1.5.0
- Host AI rule: Before packaging this project, run the relevant install/config/quickstart check for: v1.5.0. Context: Observed when using python, playwright
- Why it matters: Upgrade or migration may change expected behavior: v1.5.0
- Evidence: failure_mode_cluster:github_release | https://github.com/Khamel83/argus/releases/tag/v1.5.0
- Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it.