Edit i18n/en/CLAUDE.md, not the active copy at root. Run ./setup.sh --lang en to sync. Full tree: docs/runtime-directory-structure.en.md. Wikilinks: [[slug]]. Slugs are lowercase, hyphen-separated, no spaces. Prefer in order: .venv/bin/python (.venv/Scripts/python.exe on Windows) → active conda env → python3 (python on Windows). Tools auto-load API keys from ~/.env and project-root .env via tools/_env.py.
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Scan the full wiki to detect health issues and produce a tiered fix-recommendation report (covers all entity types in runtime/schema/entities.yaml + graph consistency)
Run or manage the daily arXiv recommendation feed. Use for one-off fresh-paper recommendations, scheduled GitHub Actions setup/status/disable, email digests, and explicit high-confidence auto-ingest through /ingest.
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Build a ranked shortlist of candidate papers (anchor-driven, topic-driven, or derived from current wiki state) that the user — or an upstream skill — may decide to feed into `/ingest`. Use whenever the user asks "what should I read next", "find papers similar to this one", "recommend related work", "what's around this topic", or whenever `/ingest` is invoked with `--discover`. Does not ingest; only proposes.
Idea-driven experiment design with iterative ablation — method candidate generation (direct / hybrid / cross-idea combination) → benchmark selection → iterative ablation (non-linear: ablation can trigger method simplification and re-planning) → sensitivity analysis → main experiment → optional generalization → deep analysis of intermediate quantities. Use when designing a full experiment suite for an idea after pilot evaluation.
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Pilot result evaluation — read pilot results, apply success criteria, update idea page (pilot_result, failure_reason if failed), generate PILOT_VERDICT_REPORT. Called by /ideate Phase 5 after /exp-pilot-run.
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Pilot experiment execution — read Pilot Spec YAML, write pilot code, run experiment(Confirm with the user before operation and require the applicant to conduct manual inspection), return results. Called by /ideate Phase 5. Does NOT modify wiki pages or judge pass/fail.
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Full experiment execution pipeline — prepare code → deploy(Confirm with the user before operation and ask the applicant to conduct manual inspection) → monitor → collect results, supporting three run modes
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Run the optional Hiera-style iterative candidate search for an existing AutoSci experiment while keeping wiki knowledge and the default experiment workflow unchanged
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Ingest a paper into the wiki — creates pages (papers + concepts + methods + people) and builds all cross-references and graph edges. Trigger whenever the user says "ingest", "add this paper", drops a `.pdf` / `.tex` / arXiv URL, or asks to fold a paper into the knowledge base.
Multi-source novelty verification — WebSearch + Semantic Scholar + wiki + Review LLM cross-verify — outputs novelty score and recommendations. Optionally writes the score back to an idea page with --write.
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Compile a paper outline from the idea graph — evidence map → narrative structure → section plan + figure plan + citation plan, Review LLM review mandatory
Plain text files in a repository that tell a coding agent how the project works: commands to run, conventions to follow and things to avoid. CLAUDE.md, AGENTS.md, cursor rules and skills are the common kinds.
CLAUDE.md or AGENTS.md?
CLAUDE.md is read by Claude Code. AGENTS.md is an open format that Codex, Cursor and other agents read. Many projects keep one and point the other at it.
What is a skill?
A folder with a SKILL.md that describes one capability, such as filling PDFs or reviewing code. The agent loads it only when the task calls for it.
Can I search my own team's files too?
Your agents already can, over MCP, limited to the files you're allowed to read. Searching them from this page is coming.