# forgekit - 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 forgekit. 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 - **AI researchers or builders of research-oriented Agents**: The README clearly centers on research, experiment, or paper workflows. Evidence: `README.md` Claim: `clm_0004` supported 0.86 - **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_0005` supported 0.86 - **Users who want to bring professional workflows into a host AI**: The repo contains Skill documents. Evidence: `global/tools/atlas/SKILL.md`, `global/tools/catchup/SKILL.md`, `global/tools/code-modernization/SKILL.md`, `global/tools/cognitive-substrate/SKILL.md` et al. Claim: `clm_0006` supported 0.86 ## What It Can Do - **AI Skill / Agent Instruction Asset Library** (Previewable before install): The project contains Skill or Agent instruction files that a host AI can read, useful for bringing professional workflows into hosts like Claude, Codex, or Cursor. Evidence: `global/tools/atlas/SKILL.md`, `global/tools/catchup/SKILL.md`, `global/tools/code-modernization/SKILL.md`, `global/tools/cognitive-substrate/SKILL.md` et al. Claim: `clm_0001` supported 0.86 - **Multi-Host Install and Distribution** (Verify after install): The project contains plugin or marketplace configuration, indicating it targets install and distribution across one or more AI hosts. Evidence: `.claude-plugin/marketplace.json`, `.claude-plugin/plugin.json`, `.codex-plugin/plugin.json` Claim: `clm_0002` supported 0.86 - **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: `README.md` Claim: `clm_0003` supported 0.86 ## How to Start - `npm install -g @codewithjuber/forgekit # or: npm install -g github:CodeWithJuber/forgekit` Evidence: `README.md` Claim: `clm_0007` supported 0.86 ## Continue-or-Stop Decision Card - **Current recommendation**: Trial the research framework first - **Why**: This project targets research workflows; the core risk is source credibility and output quality. Verify the research framework with Prompt Preview first, then trial it in an isolated environment. ### 30-Second Read - **What to do now**: Trial the research framework first - **Minimum safe next step**: Verify the research framework with Prompt Preview first; trial in isolation only once satisfied - **Do not trust yet**: Research conclusions, citations, and experiment results cannot be trusted before install. - **Continuing will touch**: Research judgment, Command execution, Host AI configuration ### What You Can Trust Now - **Target-audience signal: AI researchers or builders of research-oriented Agents** (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_0004` supported 0.86 - **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_0005` supported 0.86 - **Target-audience signal: Users who want to bring professional workflows into a host AI** (supported): Backed by a supported claim or project evidence, but that still is not the same as real install results. Evidence: `global/tools/atlas/SKILL.md`, `global/tools/catchup/SKILL.md`, `global/tools/code-modernization/SKILL.md`, `global/tools/cognitive-substrate/SKILL.md` et al. Claim: `clm_0006` supported 0.86 - **Capability exists: AI Skill / Agent Instruction Asset Library** (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: `global/tools/atlas/SKILL.md`, `global/tools/catchup/SKILL.md`, `global/tools/code-modernization/SKILL.md`, `global/tools/cognitive-substrate/SKILL.md` et al. Claim: `clm_0001` supported 0.86 - **Capability exists: Multi-Host Install and Distribution** (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: `.claude-plugin/marketplace.json`, `.claude-plugin/plugin.json`, `.codex-plugin/plugin.json` 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: `README.md` Claim: `clm_0003` supported 0.86 ### What You Cannot Trust Yet - **Research conclusions, citations, and experiment results cannot be trusted before install.** (unverified): A research Skill can organize questions and paths, but it cannot replace real literature search, paper verification, and experiment reproduction. - **Whether it fits your specific research field cannot be trusted directly.** (unverified): The Skill covering many research topics does not mean it is sufficient for your field, source requirements, and credibility standards. - **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: `.claude-plugin/marketplace.json`, `.claude-plugin/plugin.json`, `.codex-plugin/plugin.json`, `CLAUDE.md` et al. - **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. Evidence: `.claude-plugin/marketplace.json`, `.claude-plugin/plugin.json`, `.codex-plugin/plugin.json` - **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 - **Research judgment**: Problem decomposition, source paths, experiment paths, conclusion structure, and credibility judgment. Why: A research Skill can make output look more professional but cannot replace real evidence verification. - **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: `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: `.claude-plugin/marketplace.json`, `.claude-plugin/plugin.json`, `.codex-plugin/plugin.json`, `CLAUDE.md` et al. - **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: `.claude-plugin/marketplace.json`, `.claude-plugin/plugin.json`, `.codex-plugin/plugin.json`, `README.md` - **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**: Verify whether it can correctly frame the research question and evidence boundaries first; do not trust the research output 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.) - **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 source and conclusion verification checklist**: If citations or experiment paths later prove unreliable, you can return to the evidence-boundary stage and re-check. - **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. - **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_0008` inferred 0.45 - **Host AI plugin or Skill rule conflicts**: New rules may change how the user's existing host AI behaves. Mitigation: Inspect the plugin manifest and Skill files before installing, and test in isolation if needed. Evidence: `.claude-plugin/marketplace.json`, `.claude-plugin/plugin.json`, `.codex-plugin/plugin.json` Claim: `clm_0009` supported 0.86 - **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: `README.md` Claim: `clm_0010` 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 - **AI Skill / Agent Instruction Asset Library**: Use role_skill_index / evidence_index to help the user pick a usable role, Skill, or workflow first. Boundary: Can be experienced via a pre-install Prompt. Evidence: `global/tools/atlas/SKILL.md`, `global/tools/catchup/SKILL.md`, `global/tools/code-modernization/SKILL.md`, `global/tools/cognitive-substrate/SKILL.md` et al. Claim: `clm_0001` supported 0.86 - **Multi-Host Install and Distribution**: 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: `.claude-plugin/marketplace.json`, `.claude-plugin/plugin.json`, `.codex-plugin/plugin.json` Claim: `clm_0002` supported 0.86 - **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: `README.md` Claim: `clm_0003` supported 0.86 ### Context Scale - Total files: 464 - Important-file coverage: 40/464 - Evidence index entries: 80 - Role / Skill entries: 19 ### 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 forgekit, 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 forgekit 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 forgekit, 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 19 role / Skill / project-doc entries. - **atlas** (skill): Forge's code-graph. Use to find where a symbol is defined where-is-X , to discover reusable code before writing new, and to check a symbol actually exists before calling it anti-hallucination . Backed by forge atlas . Activation hint: When the user's task is highly relevant to the workflow described by “atlas”, use it for a pre-install experience first, then decide whether to install. Evidence: `global/tools/atlas/SKILL.md` - **catchup** (skill): Start-of-session context rebuild. Use when resuming work in a repo after a gap, a /clear, or a machine switch — "where were we?" answered from recorded state goal, session snapshot, decisions, recent commits instead of assumptions. Activation hint: When the user's task is highly relevant to the workflow described by “catchup”, use it for a pre-install experience first, then decide whether to install. Evidence: `global/tools/catchup/SKILL.md` - **code-modernizer** (skill): - Activation hint: When the user's task is highly relevant to the workflow described by “code-modernizer”, use it for a pre-install experience first, then decide whether to install. Evidence: `global/tools/code-modernization/SKILL.md` - **cognitive-substrate** (skill): - Activation hint: When the user's task is highly relevant to the workflow described by “cognitive-substrate”, use it for a pre-install experience first, then decide whether to install. Evidence: `global/tools/cognitive-substrate/SKILL.md` - **cost-guard** (skill): Reduce token/cost burn on large or exploratory tasks. Use when a task will touch many files, involves broad codebase search, a big migration, or when the user asks to keep cost/context low. Activation hint: When the user's task is highly relevant to the workflow described by “cost-guard”, use it for a pre-install experience first, then decide whether to install. Evidence: `global/tools/cost-guard/SKILL.md` - **design-md** (skill): Create and maintain a per-project DESIGN.md that pins the ONE visual direction so UI stays consistent across sessions and screens. Use when starting UI on a project, when look feels inconsistent, or the user mentions design system / DESIGN.md / visual guidelines. Activation hint: When the user's task is highly relevant to the workflow described by “design-md”, use it for a pre-install experience first, then decide whether to install. Evidence: `global/tools/design-md/SKILL.md` - **dev-radar** (skill): Pull current, real-world software-dev signal on demand from GitHub trending, Reddit, research papers, and blogs — filtered to the user's stack, hype-filtered, with verified sources. Use when the user asks "what's new/trending", "latest in ", "should I adopt X", or wants a dev digest. Coding topics only. Activation hint: When the user's task is highly relevant to the workflow described by “dev-radar”, use it for a pre-install experience first, then decide whether to install. Evidence: `global/tools/dev-radar/SKILL.md` - **explore-plan-code** (skill): Structured workflow for non-trivial features or unfamiliar code — explore, then plan, then implement, then verify. Use when a change spans multiple files, the approach is uncertain, or the user asks for a spec/plan first. Activation hint: When the user's task is highly relevant to the workflow described by “explore-plan-code”, use it for a pre-install experience first, then decide whether to install. Evidence: `global/tools/explore-plan-code/SKILL.md` - **handoff** (skill): End-of-session checkpoint. Use when finishing, pausing, or switching away from work in a repo — it rewrites the bounded session snapshot .forge/state.md the NEXT session is re-injected with, so nothing essential dies with this conversation. Backed by forge handoff . Activation hint: When the user's task is highly relevant to the workflow described by “handoff”, use it for a pre-install experience first, then decide whether to install. Evidence: `global/tools/handoff/SKILL.md` - **lean** (skill): Forge's minimalism discipline. Use for any "add X" / "build Y" / refactor / bug-fix — before writing code, to choose the smallest change that actually solves the problem. Reuse over rewrite, delete over add, boring over clever. Activation hint: When the user's task is highly relevant to the workflow described by “lean”, use it for a pre-install experience first, then decide whether to install. Evidence: `global/tools/lean/SKILL.md` - **problem-solver** (skill): Universal problem-solving engine that fuses proven frameworks ASQ 4-step cycle, DMAIC/PDCA, 5 Whys, Fishbone, First Principles, TRIZ, Cynefin, Design Thinking, weighted decision matrix into one staged loop. Use when the user asks to solve, analyze, or break down a problem, find root causes, choose between options, innovate, make a hard decision, handle a crisis, or wants structured/step-by-step problem solving. Activation hint: When the user's task is highly relevant to the workflow described by “problem-solver”, use it for a pre-install experience first, then decide whether to install. Evidence: `global/tools/problem-solver/SKILL.md` - **recall** (skill): Forge's cross-session memory. Use when the user says "remember this", when you learn a durable non-obvious fact/decision/gotcha worth keeping, or to recall past context. Backed by forge recall + the recall-load guard. Activation hint: When the user's task is highly relevant to the workflow described by “recall”, use it for a pre-install experience first, then decide whether to install. Evidence: `global/tools/recall/SKILL.md` - **reuse-first** (skill): Engineering standards for writing production code — reuse before building, follow existing patterns, testable/reusable design, and verify. Use for any non-trivial feature, refactor, or "add X" task, and when choosing what to build vs. adopt. Activation hint: When the user's task is highly relevant to the workflow described by “reuse-first”, use it for a pre-install experience first, then decide whether to install. Evidence: `global/tools/reuse-first/SKILL.md` - **self-improve** (skill): Self-correction and cross-session learning loop. Use when a check fails and needs iterating to green, when the user corrects the same thing more than once, or when a non-obvious fix/gotcha is worth remembering for next time. Activation hint: When the user's task is highly relevant to the workflow described by “self-improve”, use it for a pre-install experience first, then decide whether to install. Evidence: `global/tools/self-improve/SKILL.md` - **sync-docs** (skill): After ANY code change, sweep the diff for documentation that just went stale. Use when finishing an edit, before a commit/PR, or when the completion gate blocks — it turns "did I forget a doc?" into a mechanical checklist. Backed by forge docs sync . Activation hint: When the user's task is highly relevant to the workflow described by “sync-docs”, use it for a pre-install experience first, then decide whether to install. Evidence: `global/tools/sync-docs/SKILL.md` - **taste** (skill): Pick a visual design direction for a repo from Forge's menu minimalist, brutalist, editorial, playful, corporate . Use when starting UI work or when the user wants a specific look. Sets DESIGN.md, which every AI tool then follows. Activation hint: When the user's task is highly relevant to the workflow described by “taste”, use it for a pre-install experience first, then decide whether to install. Evidence: `global/tools/taste/SKILL.md` - **tech-selector** (skill): Choose a library, framework, or tool by verifying the CURRENT best option from live sources — not from training data. Use whenever picking a dependency, starting a project, or the user asks "what's the best X for Y", "latest", "which library", or wants an unbiased/current recommendation. Activation hint: When the user's task is highly relevant to the workflow described by “tech-selector”, use it for a pre-install experience first, then decide whether to install. Evidence: `global/tools/tech-selector/SKILL.md` - **ui-workflow** (skill): Reliable workflow for building or fixing UI so results look intentional, not generic. Use for any frontend/UI task — new screen, component, redesign, "make it look better", layout, styling, or when the user says UI is the pain point. Activation hint: When the user's task is highly relevant to the workflow described by “ui-workflow”, use it for a pre-install experience first, then decide whether to install. Evidence: `global/tools/ui-workflow/SKILL.md` - **hostlelo-deploy** (skill): Safe, staged deploy of Hostlelo services to the VPS. Use when asked to deploy, ship, or release a Hostlelo change kernel, widget, or Telegram control plane . Activation hint: When the user's task is highly relevant to the workflow described by “hostlelo-deploy”, use it for a pre-install experience first, then decide whether to install. Evidence: `templates/project-layer/.claude/skills/hostlelo-deploy/SKILL.md` ## Evidence Index - Indexed 80 evidence entries. - **The Forge Cognitive Substrate** (documentation): Coding agents forget what they learned, assume what they don't know, and break code they can't see. The substrate is a fast, mostly-deterministic check that runs before an agent edits your code: it flags an unclear task, picks the cheapest capable model, and shows what an edit will break — all from the repo you already have, with no extra LLM call. Evidence: `docs/cognitive-substrate/README.md` - **Forge — one shared brain for your AI coding tools** (documentation): Forge — one shared brain for your AI coding tools Evidence: `README.md` - **Examples** (documentation): Short, copy-pasteable walkthroughs. forgekit is one brain for every AI coding agent — the cognitive substrate memory, foresight, guardrails that a stateless model is missing. These examples show that brain doing its job: gating an edit before it happens, and carrying what your team learns from one machine to the next. Evidence: `examples/README.md` - **Forge documentation site Mintlify** (documentation): This folder is a self-contained Mintlify https://mintlify.com documentation site for Forge @codewithjuber/forgekit . It is additive — it does not replace the Markdown docs in docs/ , README.md , ARCHITECTURE.md , or ONBOARDING.md , which remain the source of truth. The site content is derived from those files. Evidence: `mintlify/README.md` - **Formal Synthesis — A Theory of the Cognitive Substrate for Coding Agents** (documentation): Formal Synthesis — A Theory of the Cognitive Substrate for Coding Agents Evidence: `research/formal-synthesis/README.md` - **Python prototypes** (documentation): These are the original evidence prototypes from the cognitive-substrate paper. They are preserved for auditability and result reproduction only. Evidence: `research/python-prototypes/README.md` - **Impact Oracle — Codebase World-Model + Blast-Radius Predictor** (documentation): Impact Oracle — Codebase World-Model + Blast-Radius Predictor Evidence: `research/python-prototypes/impact_oracle/README.md` - **router gate** (documentation): A research prototype of an assumption gate + complexity-aware model router for coding agents the auditable Python original of forge preflight / forge route ; a demonstration, not a benchmark . Evidence: `research/python-prototypes/router_gate/README.md` - **Package** (package_manifest): { "name": "@codewithjuber/forgekit", "version": "0.27.3", "description": "Shared memory, impact analysis, and guardrail hooks for AI coding agents — authored once, emitted as native config for Claude Code, Codex, Cursor, Gemini, Aider, and more.", "type": "module", "bin": { "forge": "src/cli.js" }, "engines": { "node": " =20" }, "exports": { ".": "./src/cli.js", "./model-tiers": "./src/model tiers.js", "./package.json": "./package.json" }, "author": "CodeWithJuber", "license": "MIT", "repository": { "type": "git", "url": "git+https://github.com/CodeWithJuber/forgekit.git" }, "bugs": { "url": "https://github.com/CodeWithJuber/forgekit/issues" }, "homepage": "https://github.com/CodeWithJuber/… Evidence: `package.json` - **forgekit — contributor instructions** (documentation): forgekit — contributor instructions Evidence: `CLAUDE.md` - **Global instructions all projects** (documentation): Loaded every session. Keep short — long files get ignored. Prune ruthlessly. Evidence: `global/CLAUDE.md` - **AGENTS.md —** (documentation): Cross-tool rules read by Codex, Cursor, Copilot, Gemini, Aider, Zed, and by Claude Code when CLAUDE.md points here . Keep tool-agnostic and thin. Evidence: `templates/project-layer/AGENTS.md` - **— project instructions** (documentation): Drop this into a repo root. Adds project context on top of the global ~/.claude/CLAUDE.md . Keep it lean; prune anything Claude gets right without it. Evidence: `templates/project-layer/CLAUDE.md` - **Contributing to forgekit** (documentation): forgekit is one brain for every AI coding agent — a cognitive substrate memory, foresight, guardrails authored once and compiled into every tool's native config. Keeping that brain small and dependency-free is the whole point, so please read this before opening a PR. Evidence: `CONTRIBUTING.md` - **atlas — the code-graph** (skill_instruction): A precomputed, portable symbol index at .forge/atlas.json . Any tool reads it via forge atlas or plain jq — no MCP required to consume. Evidence: `global/tools/atlas/SKILL.md` - **catchup — resume, don't re-assume** (skill_instruction): A fresh session that guesses the project's state re-burns every iteration the last one already paid for. Everything essential is recorded; read it BEFORE acting. Evidence: `global/tools/catchup/SKILL.md` - **Code Modernizer** (skill_instruction): A senior engineer isn't measured by how much code they wrote today, but by how little the system needs. Before touching anything, decide whether the code should be replaced with something already established. If custom code is genuinely necessary, write the least of it that solves the real problem without dropping behavior anyone relies on. Evidence: `global/tools/code-modernization/SKILL.md` - **Cognitive Substrate** (skill_instruction): Wrap the frozen model in a pre-action check: gate assumptions, route model effort, predict blast radius, decompose scope, surface past lessons, and plan verification — before editing. Evidence: `global/tools/cognitive-substrate/SKILL.md` - **Cost guard** (skill_instruction): Playbook for high-performance, low-cost runs. The constraint is the context window: performance degrades as it fills, and tokens cost money. Spend context deliberately. Evidence: `global/tools/cost-guard/SKILL.md` - **DESIGN.md** (skill_instruction): The fix for "UI comes out inconsistent" is a single written source of visual truth per project. ui-workflow says pick one direction — DESIGN.md is where that direction lives so every session and screen obeys the same rules. forge taste writes a managed one from Forge's menu; hand-write it only for a bespoke direction. Evidence: `global/tools/design-md/SKILL.md` - **Dev radar** (skill_instruction): On-demand scan of what's actually happening in software dev right now — not training-data recall. Signal over noise, coding topics only. Evidence: `global/tools/dev-radar/SKILL.md` - **Explore → Plan → Code → Verify** (skill_instruction): Separate research from execution so you don't build the wrong thing. Evidence: `global/tools/explore-plan-code/SKILL.md` - **handoff — persist what this session knows** (skill_instruction): handoff — persist what this session knows Evidence: `global/tools/handoff/SKILL.md` - **lean — the smallest change that works** (skill_instruction): lean — the smallest change that works Evidence: `global/tools/lean/SKILL.md` - **Problem Solver** (skill_instruction): This skill solves any problem — technical, business, personal, or complex — through a staged loop. Each analytical stage carries a discipline that keeps the analysis honest e.g. verify facts before diagnosing root cause . Match depth to the problem: a trivial problem gets two sentences of method, not all six stages. Evidence: `global/tools/problem-solver/SKILL.md` - **recall — durable cross-session memory** (skill_instruction): recall — durable cross-session memory Evidence: `global/tools/recall/SKILL.md` - **Reuse-first engineering** (skill_instruction): Default to reusing and following what exists. New code is a liability; the best change is the smallest one that fits the codebase. Evidence: `global/tools/reuse-first/SKILL.md` - **Self-improve** (skill_instruction): Honest scope: you can't reinforcement-learn a hosted model's weights in a config. What works is experiential learning — correct within the session, persist durable lessons for the next one. Two loops: Evidence: `global/tools/self-improve/SKILL.md` - **sync-docs — make every artifact true again** (skill_instruction): sync-docs — make every artifact true again Evidence: `global/tools/sync-docs/SKILL.md` - **taste — choose one design direction** (skill_instruction): taste — choose one design direction Evidence: `global/tools/taste/SKILL.md` - **Tech selector** (skill_instruction): Training data is stale and biased toward what was popular at cutoff. For any "what should I use" decision, verify against live sources before recommending. Evidence: `global/tools/tech-selector/SKILL.md` - **UI workflow** (skill_instruction): UI is unreliable when taste is vague and there's no check. Fix both: lock ONE visual direction, build on the project's real components, then verify with the deterministic design gate and a screenshot instead of guessing. Evidence: `global/tools/ui-workflow/SKILL.md` - **Hostlelo deploy** (skill_instruction): Staged deploy with a check at each gate. Never skip verification. Never deploy with a failing build or uncommitted secrets. Evidence: `templates/project-layer/.claude/skills/hostlelo-deploy/SKILL.md` - **Marketplace** (structured_config): { "$schema": "https://json.schemastore.org/claude-code-marketplace.json", "name": "forge", "owner": { "name": "CodeWithJuber" }, "plugins": { "name": "forgekit", "source": ".", "description": "One config, every AI coding tool. Cross-tool rules emitter, enforced guards, code-graph, memory, and cost governor." } } Evidence: `.claude-plugin/marketplace.json` - **Plugin** (structured_config): { "$schema": "https://json.schemastore.org/claude-code-plugin-manifest.json", "name": "forgekit", "displayName": "Forge", "version": "0.27.3", "description": "One config, every AI coding tool — cognitive substrate, tools, crew, guards, atlas, lean, recall from one source.", "author": { "name": "CodeWithJuber" }, "license": "MIT", "repository": "https://github.com/CodeWithJuber/forgekit", "homepage": "https://github.com/CodeWithJuber/forgekit readme", "keywords": "config", "cross-tool", "agents-md", "ai-coding", "claude-code", "cognitive-substrate" , "skills": "./global/tools", "agents": "./global/crew/doc-sync.md", "./global/crew/frontend-verifier.md", "./global/crew/independent-reviewer.md… Evidence: `.claude-plugin/plugin.json` - **Plugin** (structured_config): { "name": "forgekit", "version": "0.27.3", "description": "One config, every AI coding tool — cognitive substrate, MCP tools, guards, atlas, recall, and routing from one source.", "author": { "name": "CodeWithJuber", "url": "https://github.com/CodeWithJuber" }, "homepage": "https://github.com/CodeWithJuber/forgekit readme", "repository": "https://github.com/CodeWithJuber/forgekit", "license": "MIT", "keywords": "codex", "mcp", "ai-coding", "agents-md", "cognitive-substrate" , "skills": "global/tools", "mcpServers": ".mcp.json", "interface": { "displayName": "Forge", "shortDescription": "Cognitive substrate and one config for every AI coding tool.", "longDescription": "Forge adds a pre-actio… Evidence: `.codex-plugin/plugin.json` - **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` - **Forge — the complete guide** (documentation): One brain for every AI coding agent. A language model is stateless — one context window, wiped every call. It can't remember what your team learned, can't foresee what an edit breaks, and has no enforced guardrails. Forge is the cognitive substrate — the layer that runs before the model edits code — that supplies exactly those three things, and it ships them as native config to nine AI coding tools at once. The brain is the point; one config for every tool is how the brain gets delivered. Evidence: `docs/GUIDE.md` - **Releasing forgekit** (documentation): Releases are automatic. Merge to master and the release cuts itself — no button, no manual bump. Two workflows do everything: Evidence: `docs/RELEASING.md` - **Repository review notes** (documentation): - Runtime dependency policy is consistent: package.json has no production dependencies and the docs describe a zero-runtime-dependency Node CLI. - Core user docs are present: README, onboarding, architecture, guide, changelog, governance, support, security, releasing, and accessibility files exist. - Benchmark claims in the README point readers to reports/benchmarks.md , which is the right direction for avoiding stale marketing numbers. Evidence: `docs/REPO_REVIEW.md` - **ADR NNNN:** (documentation): - Status: proposed accepted superseded by ADR-XXXX - Date: YYYY-MM-DD Evidence: `docs/adr/0000-template.md` - **ADR 0001: Zero runtime dependencies** (documentation): ADR 0001: Zero runtime dependencies Evidence: `docs/adr/0001-zero-runtime-dependencies.md` - **ADR 0002: Adopt the SKILL.md open standard; don't invent a format** (documentation): ADR 0002: Adopt the SKILL.md open standard; don't invent a format Evidence: `docs/adr/0002-adopt-skill-md-standard.md` - **ADR 0003: Enforce invariants as guards; keep prose thin** (documentation): ADR 0003: Enforce invariants as guards; keep prose thin Evidence: `docs/adr/0003-guard-over-prose.md` - **ADR 0004: Which 2026 production standards apply to a zero-dep CLI** (documentation): ADR 0004: Which 2026 production standards apply to a zero-dep CLI Evidence: `docs/adr/0004-standards-for-a-zero-dep-cli.md` - **ADR 0005: Allow selective runtime dependencies** (documentation): ADR 0005: Allow selective runtime dependencies Evidence: `docs/adr/0005-allow-runtime-dependencies.md` - **ADR 0006: Proof-Carrying Memory is the one store** (documentation): ADR 0006: Proof-Carrying Memory is the one store Evidence: `docs/adr/0006-proof-carrying-memory.md` - **Audit remediation record** (documentation): A concise record of the honesty / wording audit and what was addressed in this change. Status legend: Done shipped here · Deferred tracked, out of scope for this pass . Evidence: `docs/audit/REMEDIATION.md` - **A Cognitive Substrate for Coding Agents — Deliverable Package** (documentation): A Cognitive Substrate for Coding Agents — Deliverable Package Evidence: `docs/cognitive-substrate/deliverable-package.md` - **Ecosystem Map: Cognitive Substrate vs. the Mid-2026 Claude Code Stack** (documentation): Ecosystem Map: Cognitive Substrate vs. the Mid-2026 Claude Code Stack Evidence: `docs/cognitive-substrate/ecosystem_map.md` - **Evidence Map: Independent Re-Grounding of Pain-Point Statistics** (documentation): Evidence Map: Independent Re-Grounding of Pain-Point Statistics Evidence: `docs/cognitive-substrate/evidence_map.md` - **Playbook — how to drive your Claude setup** (documentation): Playbook — how to drive your Claude setup Evidence: `docs/legacy/PLAYBOOK.md` - **Audit of your live ~/.claude + how this bundle fits** (documentation): Audit of your live ~/.claude + how this bundle fits Evidence: `docs/legacy/RECONCILE.md` - **Deep research — best Claude Code configs vs. yours 2026** (documentation): Deep research — best Claude Code configs vs. yours 2026 Evidence: `docs/legacy/RESEARCH-claude-config.md` - **RUN — command sheet current state** (documentation): ⚠️ Archived — pre-Forge. Kept for history; not maintained . It describes an older hand-rolled ~/.claude setup, not today's forge CLI. For the current workflow start at ONBOARDING.md ../../ONBOARDING.md → docs/GUIDE.md ../GUIDE.md . Any credentials or open action items below are historical and superseded — do not act on them. Evidence: `docs/legacy/RUN.md` - **Daily Config Radar — 2026-07-04** (documentation): ⚠️ Archived — pre-Forge. A historical auto-generated report, kept for the record. Not maintained and not the current state. See docs/GUIDE.md ../../GUIDE.md for today's tooling. Evidence: `docs/legacy/reports/2026-07-04.md` - **Substrate v2 — completing the whitepaper, and the Proof-Carrying Memory protocol** (documentation): Substrate v2 — completing the whitepaper, and the Proof-Carrying Memory protocol Evidence: `docs/plans/substrate-v2/00-overview.md` - **01 — The Proof-Carrying Memory PCM protocol** (documentation): 01 — The Proof-Carrying Memory PCM protocol Evidence: `docs/plans/substrate-v2/01-pcm-protocol.md` - **02 — Team & shared memory: a git-native CRDT ledger** (documentation): 02 — Team & shared memory: a git-native CRDT ledger Evidence: `docs/plans/substrate-v2/02-team-memory.md` - **03 — The proof-carrying reuse cache** (documentation): 03 — The proof-carrying reuse cache Evidence: `docs/plans/substrate-v2/03-reuse-cache.md` - The remaining 20 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/cognitive-substrate/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/cognitive-substrate/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 and Getting Started**: importance `high` - source_paths: README.md, package.json, install.sh, mintlify/introduction.mdx, mintlify/installation.mdx - **Architecture and the Cognitive Substrate**: importance `high` - source_paths: ARCHITECTURE.md, src/substrate.js, src/cli.js, source/substrate.json, source/rules.json - **CLI Commands and Workflows**: importance `high` - source_paths: src/cli.js, src/commands.js, src/init.js, src/sync.js, src/doctor.js - **Memory System and Team Collaboration**: importance `high` - source_paths: src/ledger.js, src/ledger_store.js, src/ledger_read.js, src/ledger_sync.js, src/ledger_bridge.js ## Repo Inspection Evidence - repo_clone_verified: true - repo_inspection_verified: true - repo_commit: `766254eba2da15a658ac3f70b1f08f5227efe708` - inspected_files: `README.md`, `package.json`, `docs/GUIDE.md`, `docs/RELEASING.md`, `docs/REPO_REVIEW.md`, `docs/adr/0000-template.md`, `docs/adr/0001-zero-runtime-dependencies.md`, `docs/adr/0002-adopt-skill-md-standard.md`, `docs/adr/0003-guard-over-prose.md`, `docs/adr/0004-standards-for-a-zero-dep-cli.md`, `docs/adr/0005-allow-runtime-dependencies.md`, `docs/adr/0006-proof-carrying-memory.md`, `docs/audit/REMEDIATION.md`, `docs/cognitive-substrate/README.md`, `docs/cognitive-substrate/deliverable-package.md`, `docs/cognitive-substrate/ecosystem_map.md`, `docs/cognitive-substrate/evidence_map.md`, `docs/legacy/PLAYBOOK.md`, `docs/legacy/RECONCILE.md`, `docs/legacy/RESEARCH-claude-config.md` 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: Capability evidence risk requires verification - Trigger: README/documentation is current enough for a first validation pass. - Host AI rule: Reproduce the official install and quickstart path in an isolated environment. - Why it matters: May increase setup, validation, or first-run risk for the user. - Evidence: capability.assumptions | https://github.com/CodeWithJuber/forgekit - 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: no_demo - Host AI rule: Reproduce the official install and quickstart path in an isolated environment. - Why it matters: May increase setup, validation, or first-run risk for the user. - Evidence: downstream_validation.risk_items | https://github.com/CodeWithJuber/forgekit - Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it. ### Constraint 3: Security or permission risk requires verification - Trigger: no_demo - Host AI rule: Reproduce the official install and quickstart path in an isolated environment. - Why it matters: May increase setup, validation, or first-run risk for the user. - Evidence: risks.scoring_risks | https://github.com/CodeWithJuber/forgekit - Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it. ### Constraint 4: Maintenance risk requires verification - Trigger: issue_or_pr_quality=unknown。 - Host AI rule: Reproduce the official install and quickstart path in an isolated environment. - Why it matters: May increase setup, validation, or first-run risk for the user. - Evidence: evidence.maintainer_signals | https://github.com/CodeWithJuber/forgekit - Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it. ### Constraint 5: Maintenance risk requires verification - Trigger: release_recency=unknown。 - Host AI rule: Reproduce the official install and quickstart path in an isolated environment. - Why it matters: May increase setup, validation, or first-run risk for the user. - Evidence: evidence.maintainer_signals | https://github.com/CodeWithJuber/forgekit - Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it.