# crawlora-skills - 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 crawlora-skills. 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_0004` supported 0.86 - **Users who want to bring professional workflows into a host AI**: The repo contains Skill documents. Evidence: `skills/app-review-mining/SKILL.md`, `skills/crawlora/SKILL.md`, `skills/product-price-research/SKILL.md`, `skills/serp-keyword-research/SKILL.md` et al. Claim: `clm_0005` 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: `skills/app-review-mining/SKILL.md`, `skills/crawlora/SKILL.md`, `skills/product-price-research/SKILL.md`, `skills/serp-keyword-research/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` 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 - `npx skills add github.com/Crawlora-org/crawlora-skills --skill youtube-research` Evidence: `README.md` Claim: `clm_0006` supported 0.86 - `npx skills add github.com/Crawlora-org/crawlora-skills \` Evidence: `README.md` Claim: `clm_0006` supported 0.86, `clm_0007` supported 0.86, `clm_0008` supported 0.86 - `npx skills add github.com/Crawlora-org/crawlora-skills --all` Evidence: `README.md` Claim: `clm_0008` supported 0.86 - `/plugin marketplace add Crawlora-org/crawlora-skills` Evidence: `README.md` Claim: `clm_0009` supported 0.86 - `/plugin install crawlora-skills@crawlora-skills` Evidence: `README.md` Claim: `clm_0010` 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**: 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: 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_0004` 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: `skills/app-review-mining/SKILL.md`, `skills/crawlora/SKILL.md`, `skills/product-price-research/SKILL.md`, `skills/serp-keyword-research/SKILL.md` et al. Claim: `clm_0005` 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: `skills/app-review-mining/SKILL.md`, `skills/crawlora/SKILL.md`, `skills/product-price-research/SKILL.md`, `skills/serp-keyword-research/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` 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 - **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_0006` 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`, `skills/app-review-mining/SKILL.md`, `skills/crawlora/SKILL.md`, `skills/product-price-research/SKILL.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` - **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`, `skills/app-review-mining/SKILL.md`, `skills/crawlora/SKILL.md`, `skills/product-price-research/SKILL.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`, `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: `README.md`, `lib/crawlora.sh`, `skills/app-review-mining/SKILL.md`, `skills/app-review-mining/reference/endpoints.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**: 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.) - **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 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. - **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_0011` 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` Claim: `clm_0012` 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_0013` 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: `skills/app-review-mining/SKILL.md`, `skills/crawlora/SKILL.md`, `skills/product-price-research/SKILL.md`, `skills/serp-keyword-research/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` 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: 23 - Important-file coverage: 23/23 - Evidence index entries: 23 - Role / Skill entries: 5 ### 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 crawlora-skills, 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 crawlora-skills 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 crawlora-skills, 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 5 role / Skill / project-doc entries. - **app-review-mining** (skill): Mines App Store and Google Play data via the Crawlora API — app details, reviews, ratings, store rankings, and similar apps — as clean JSON. Use when the user wants mobile-app reviews, ratings, store charts/rankings, or competitive ASO app store optimization research without scraping store pages. Activation hint: When the user's task is highly relevant to the workflow described by “app-review-mining”, use it for a pre-install experience first, then decide whether to install. Evidence: `skills/app-review-mining/SKILL.md` - **crawlora** (skill): Fetches structured public web data via the Crawlora REST API — search engines, e-commerce, social, finance, maps, app stores, media, and reviews — returning clean JSON instead of HTML. Use whenever the user needs real data from a public website prices, listings, reviews, transcripts, SERPs, trends, financials, places and would otherwise have to scrape or parse HTML. Activation hint: When the user's task is highly relevant to the workflow described by “crawlora”, use it for a pre-install experience first, then decide whether to install. Evidence: `skills/crawlora/SKILL.md` - **product-price-research** (skill): Researches products, prices, sellers, and reviews across major online marketplaces Amazon, eBay, Shopify stores, and Shop.app using the Crawlora API, returning clean JSON. Use when the user asks to find a product, compare prices or sellers, track listings, or pull marketplace reviews — instead of scraping store pages. Activation hint: When the user's task is highly relevant to the workflow described by “product-price-research”, use it for a pre-install experience first, then decide whether to install. Evidence: `skills/product-price-research/SKILL.md` - **serp-keyword-research** (skill): Runs SERP and keyword research via the Crawlora API — Google, Bing, and Brave search results plus Google Trends interest-over-time and related/rising queries — returning clean JSON. Use when the user wants search-engine rankings, SERP snapshots, autocomplete/keyword suggestions, or trend data instead of scraping result pages. Activation hint: When the user's task is highly relevant to the workflow described by “serp-keyword-research”, use it for a pre-install experience first, then decide whether to install. Evidence: `skills/serp-keyword-research/SKILL.md` - **youtube-research** (skill): Pulls structured YouTube data — video and channel details, transcripts/captions, comments, playlists, and search — via the Crawlora API as clean JSON, with no yt-dlp or HTML scraping. Use when the user provides a YouTube URL or asks for a transcript, comments, channel/video metadata, or video search results. Activation hint: When the user's task is highly relevant to the workflow described by “youtube-research”, use it for a pre-install experience first, then decide whether to install. Evidence: `skills/youtube-research/SKILL.md` ## Evidence Index - Indexed 23 evidence entries. - **Crawlora Agent Skills** (documentation): ! Website https://img.shields.io/badge/website-crawlora.net-2563eb https://crawlora.net ! Docs https://img.shields.io/badge/docs-crawlora.net%2Fdocs-555 https://crawlora.net/docs ! Skills https://img.shields.io/badge/Agent-Skills-7c3aed https://docs.claude.com/en/docs/agents-and-tools/agent-skills/overview ! License: MIT https://img.shields.io/badge/License-MIT-green LICENSE Evidence: `README.md` - **App review mining & ASO** (skill_instruction): Pull App Store iOS and Google Play Android app details, reviews, ratings, rankings, and similar-app lists as normalized JSON from the Crawlora API. Evidence: `skills/app-review-mining/SKILL.md` - **Crawlora — structured public web data** (skill_instruction): Crawlora — structured public web data Evidence: `skills/crawlora/SKILL.md` - **Product & price research** (skill_instruction): Look up and compare products, prices, sellers, and reviews across Amazon, eBay, Shopify storefronts, and Shop.app — all as normalized JSON from the Crawlora API, with no HTML scraping. Evidence: `skills/product-price-research/SKILL.md` - **SERP & keyword research** (skill_instruction): Capture search-engine results Google, Bing, Brave and keyword/trend signals Google autosuggest, Google Trends as normalized JSON from the Crawlora API. Evidence: `skills/serp-keyword-research/SKILL.md` - **YouTube research** (skill_instruction): Resolve YouTube videos and channels, and pull transcripts, comments, playlists, and search results as normalized JSON from the Crawlora API — no yt-dlp , no browser, no scraping. Evidence: `skills/youtube-research/SKILL.md` - **Marketplace** (structured_config): { "name": "crawlora-skills", "owner": { "name": "Crawlora", "email": "hello@crawlora.net" }, "metadata": { "description": "Crawlora Agent Skills — structured public web data search, e-commerce, social, finance, app stores, media, reviews via the Crawlora REST API.", "version": "1.3.0" }, "plugins": { "name": "crawlora-skills", "description": "Five Agent Skills for fetching structured public web data with the Crawlora API: an umbrella catalog skill plus product/price, YouTube, app-review, and SERP/keyword research recipes.", "source": "./", "homepage": "https://crawlora.net", "repository": "https://github.com/Crawlora-org/crawlora-skills", "license": "MIT", "keywords": "crawlora", "web-scrap… Evidence: `.claude-plugin/marketplace.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` - **app-review-mining — endpoint reference** (documentation): app-review-mining — endpoint reference Evidence: `skills/app-review-mining/reference/endpoints.md` - **Crawlora endpoint catalog** (documentation): Generated from scripts/tools.json by scripts/generate.mjs — do not edit by hand. Evidence: `skills/crawlora/reference/catalog.md` - **product-price-research — endpoint reference** (documentation): product-price-research — endpoint reference Evidence: `skills/product-price-research/reference/endpoints.md` - **serp-keyword-research — endpoint reference** (documentation): serp-keyword-research — endpoint reference Evidence: `skills/serp-keyword-research/reference/endpoints.md` - **youtube-research — endpoint reference** (documentation): youtube-research — endpoint reference Evidence: `skills/youtube-research/reference/endpoints.md` - **Tools** (structured_config): {"name":"airbnb host","description":"Get Airbnb host profile. Returns a normalized Airbnb public host profile — display name, Superhost and identity-verification status, location, bio, hosting tenure, total guest-review count, and total listing count.","inputSchema":{"type":"object","properties":{"id":{"type":"string","description":"Host id numeric "}},"required": "id" }," http":{"method":"GET","path":"/airbnb/host/{id}","query": ,"pathParams": "id" ,"body":null,"group":"Airbnb"}},{"name":"airbnb host listings","description":"Get Airbnb host listings. Returns the listings an Airbnb host manages, paginated. Page 1 comes from the host profile; deeper pages page through the host's full portfol… Evidence: `scripts/tools.json` - **Crawlora** (source_file): set -euo pipefail : "${CRAWLORA API KEY:?Set CRAWLORA API KEY first — get a free key at https://crawlora.net}" base="${CRAWLORA API BASE:-https://api.crawlora.net/api/v1}" method="GET" body="" args= while $ -gt 0 ; do case "$1" in -X method="$2"; shift 2 ;; -d body="$2"; shift 2 ;; args+= "$1" ; shift ;; esac done "${ args @ }" -ge 1 { echo "usage: crawlora.sh -X METHOD /path k=v ... json-body " &2; exit 2; } path="${args 0 }" rest= "${args @ :1}" auth= -H "x-api-key: ${CRAWLORA API KEY}" if "$method" = "GET" ; then qs= for kv in ${rest @ +"${rest @ }"}; do -n "$kv" && qs+= --data-urlencode "$kv" done curl -fsS -G "${auth @ }" "${qs @ }" "${base}${path}" else -n "$body" body="${rest 0 :-{}}… Evidence: `lib/crawlora.sh` - **Generate** (source_file): const groupsOf = t ⋮---- function params t ⋮---- function endpointLine t ⋮---- function renderGroups groupNames, title, intro Evidence: `scripts/generate.mjs` - **Validate** (source_file): function parseFrontmatter text, file, errors Evidence: `scripts/validate.mjs` - **Crawlora** (source_file): set -euo pipefail : "${CRAWLORA API KEY:?Set CRAWLORA API KEY first — get a free key at https://crawlora.net}" base="${CRAWLORA API BASE:-https://api.crawlora.net/api/v1}" method="GET" body="" args= while $ -gt 0 ; do case "$1" in -X method="$2"; shift 2 ;; -d body="$2"; shift 2 ;; args+= "$1" ; shift ;; esac done "${ args @ }" -ge 1 { echo "usage: crawlora.sh -X METHOD /path k=v ... json-body " &2; exit 2; } path="${args 0 }" rest= "${args @ :1}" auth= -H "x-api-key: ${CRAWLORA API KEY}" if "$method" = "GET" ; then qs= for kv in ${rest @ +"${rest @ }"}; do -n "$kv" && qs+= --data-urlencode "$kv" done curl -fsS -G "${auth @ }" "${qs @ }" "${base}${path}" else -n "$body" body="${rest 0 :-{}}… Evidence: `skills/app-review-mining/scripts/crawlora.sh` - **Crawlora** (source_file): set -euo pipefail : "${CRAWLORA API KEY:?Set CRAWLORA API KEY first — get a free key at https://crawlora.net}" base="${CRAWLORA API BASE:-https://api.crawlora.net/api/v1}" method="GET" body="" args= while $ -gt 0 ; do case "$1" in -X method="$2"; shift 2 ;; -d body="$2"; shift 2 ;; args+= "$1" ; shift ;; esac done "${ args @ }" -ge 1 { echo "usage: crawlora.sh -X METHOD /path k=v ... json-body " &2; exit 2; } path="${args 0 }" rest= "${args @ :1}" auth= -H "x-api-key: ${CRAWLORA API KEY}" if "$method" = "GET" ; then qs= for kv in ${rest @ +"${rest @ }"}; do -n "$kv" && qs+= --data-urlencode "$kv" done curl -fsS -G "${auth @ }" "${qs @ }" "${base}${path}" else -n "$body" body="${rest 0 :-{}}… Evidence: `skills/crawlora/scripts/crawlora.sh` - **Crawlora** (source_file): set -euo pipefail : "${CRAWLORA API KEY:?Set CRAWLORA API KEY first — get a free key at https://crawlora.net}" base="${CRAWLORA API BASE:-https://api.crawlora.net/api/v1}" method="GET" body="" args= while $ -gt 0 ; do case "$1" in -X method="$2"; shift 2 ;; -d body="$2"; shift 2 ;; args+= "$1" ; shift ;; esac done "${ args @ }" -ge 1 { echo "usage: crawlora.sh -X METHOD /path k=v ... json-body " &2; exit 2; } path="${args 0 }" rest= "${args @ :1}" auth= -H "x-api-key: ${CRAWLORA API KEY}" if "$method" = "GET" ; then qs= for kv in ${rest @ +"${rest @ }"}; do -n "$kv" && qs+= --data-urlencode "$kv" done curl -fsS -G "${auth @ }" "${qs @ }" "${base}${path}" else -n "$body" body="${rest 0 :-{}}… Evidence: `skills/product-price-research/scripts/crawlora.sh` - **Crawlora** (source_file): set -euo pipefail : "${CRAWLORA API KEY:?Set CRAWLORA API KEY first — get a free key at https://crawlora.net}" base="${CRAWLORA API BASE:-https://api.crawlora.net/api/v1}" method="GET" body="" args= while $ -gt 0 ; do case "$1" in -X method="$2"; shift 2 ;; -d body="$2"; shift 2 ;; args+= "$1" ; shift ;; esac done "${ args @ }" -ge 1 { echo "usage: crawlora.sh -X METHOD /path k=v ... json-body " &2; exit 2; } path="${args 0 }" rest= "${args @ :1}" auth= -H "x-api-key: ${CRAWLORA API KEY}" if "$method" = "GET" ; then qs= for kv in ${rest @ +"${rest @ }"}; do -n "$kv" && qs+= --data-urlencode "$kv" done curl -fsS -G "${auth @ }" "${qs @ }" "${base}${path}" else -n "$body" body="${rest 0 :-{}}… Evidence: `skills/serp-keyword-research/scripts/crawlora.sh` - **Crawlora** (source_file): set -euo pipefail : "${CRAWLORA API KEY:?Set CRAWLORA API KEY first — get a free key at https://crawlora.net}" base="${CRAWLORA API BASE:-https://api.crawlora.net/api/v1}" method="GET" body="" args= while $ -gt 0 ; do case "$1" in -X method="$2"; shift 2 ;; -d body="$2"; shift 2 ;; args+= "$1" ; shift ;; esac done "${ args @ }" -ge 1 { echo "usage: crawlora.sh -X METHOD /path k=v ... json-body " &2; exit 2; } path="${args 0 }" rest= "${args @ :1}" auth= -H "x-api-key: ${CRAWLORA API KEY}" if "$method" = "GET" ; then qs= for kv in ${rest @ +"${rest @ }"}; do -n "$kv" && qs+= --data-urlencode "$kv" done curl -fsS -G "${auth @ }" "${qs @ }" "${base}${path}" else -n "$body" body="${rest 0 :-{}}… Evidence: `skills/youtube-research/scripts/crawlora.sh` - **.gitignore** (source_file): node modules/ .DS Store .log .env .env. Evidence: `.gitignore` ## 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: `README.md`, `skills/app-review-mining/SKILL.md`, `skills/crawlora/SKILL.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: `README.md`, `skills/app-review-mining/SKILL.md`, `skills/crawlora/SKILL.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. - **Introduction and Installation**: importance `high` - source_paths: README.md, .claude-plugin/marketplace.json, lib/crawlora.sh, skills/crawlora/scripts/crawlora.sh - **Skills Catalog and Endpoint Reference**: importance `high` - source_paths: skills/crawlora/SKILL.md, skills/crawlora/reference/catalog.md, skills/product-price-research/SKILL.md, skills/product-price-research/reference/endpoints.md, skills/youtube-research/SKILL.md - **Architecture and Build Pipeline**: importance `high` - source_paths: lib/crawlora.sh, scripts/tools.json, scripts/generate.mjs, skills/crawlora/scripts/crawlora.sh, skills/product-price-research/scripts/crawlora.sh - **Development, Validation, and Extending Skills**: importance `medium` - source_paths: scripts/validate.mjs, scripts/generate.mjs, scripts/tools.json, .claude-plugin/marketplace.json, skills/crawlora/SKILL.md ## Repo Inspection Evidence - repo_clone_verified: true - repo_inspection_verified: true - repo_commit: `5762ed8278094594ca03bca74354b6c7a01ccefc` - inspected_files: `README.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/Crawlora-org/crawlora-skills - 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/Crawlora-org/crawlora-skills - 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/Crawlora-org/crawlora-skills - 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/Crawlora-org/crawlora-skills - 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/Crawlora-org/crawlora-skills - Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it.