一键导入
are-generate
Generate AI-friendly documentation for the entire codebase
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
菜单
Generate AI-friendly documentation for the entire codebase
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Show available ARE commands and usage guide
Show telemetry dashboard (costs, tokens, traces) (experimental)
Execute implementation with and without ARE documentation (experimental)
Compare AI planning quality with and without ARE documentation (experimental)
Reconstruct project from specification documents (experimental)
Generate project specification from AGENTS.md docs (experimental)
| name | are-generate |
| description | Generate AI-friendly documentation for the entire codebase |
| disable-model-invocation | true |
Generate comprehensive documentation for this codebase using agents-reverse-engineer.
Run the generate command in the background and monitor progress in real time.Read version: Read .claude/ARE-VERSION → store as $VERSION. Show the user: agents-reverse-engineer v$VERSION
Run the generate command in the background using run_in_background: true:
npx agents-reverse-engineer@$VERSION generate --backend claude $ARGUMENTS
Monitor progress by polling the latest progress log:
sleep 15 in Bash), then use Glob to find the latest .agents-reverse-engineer/progress-*.log file, and Read it (use the offset parameter to read only the last ~20 lines for long files)TaskOutput with block: falseOn completion, read the full background task output and summarize:
This executes a two-phase pipeline:
File Analysis (concurrent): Discovers files, applies filters, then analyzes each source file via AI and writes .sum summary files with YAML frontmatter (content_hash, file_type, purpose, public_interface, dependencies, patterns).
Directory Aggregation (sequential): Generates AGENTS.md per directory in post-order traversal (deepest first, so child summaries feed into parents), and writes CLAUDE.md pointers.
Options:
--dry-run: Preview the plan without making AI calls--eval: Namespace output by backend.model for side-by-side comparison (e.g., file.ts.claude.haiku.sum, AGENTS.claude.haiku.md)--concurrency N: Control number of parallel AI calls (default: auto)--fail-fast: Stop on first file analysis failure--debug: Show AI prompts and backend details--trace: Enable concurrency tracing to .agents-reverse-engineer/traces/