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module-curation

Curate, review, or repair ai-gene-review ModuleReview YAML documents under modules/, including pathway/module boundary setting, parts and variant modeling, annoton-level molecular functions, representative UniProt/PTN grounding, module deep-research provenance, validation, rendering, and project batch updates.

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含まれるファイル(5)

  • SKILL.md4.1 KB
  • agents/openai.yaml205 B
  • references/modeling.md4.0 KB
  • references/research-and-grounding.md2.4 KB
  • references/validation-and-pr.md2.7 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Module Curation

Use this skill for modules/*.yaml work and for project pages that describe module/pathway curation. The goal is a reusable, defensible biological module, not a flat list of annotations or a species-specific note disguised as a module.

Workflow

  1. Read the local context before editing:
    • modules/README.md
    • the target modules/<module>.yaml
    • any adjacent <module>-deep-research-*.md
    • related projects/** batch page(s), if the task is pathway-batch work
    • relevant gene reviews and UniProt/GOA files for concrete members
  2. Decide the module boundary before filling YAML:
    • What biological process, complex, reaction chain, or reusable motif is the module?
    • Which genes/proteins are core members, and which are activation context, substrate supply, regulation, upstream/downstream biology, or separate modules?
    • Is this a concrete species/pathway instance or an abstract reusable motif?
    • Does the boundary have at least two substantive parts/roles/steps? If it collapses to one gene, one enzyme, or one reaction, do not create or retain a standalone ModuleReview; record it as pathway/gene curation and fold it into a broader module later.
  3. Model the structure:
    • Put module-level process/complex/context terms on module.concepts and module.context.
    • Put molecular functions on leaf annotons[].function, not on a biological-process module just because the member protein has that MF.
    • Use parts for required steps or roles, variant_sets for alternatives, and connections for ordered/causal links.
  4. Ground claims with checkable provenance:
    • Use exact UniProt, GO, Rhea, ChEBI, PANTHER PTHR, and PAINT PTN ids.
    • Never guess PTNs or identifiers. Resolve PTNs from local PANTHER/PAINT data or GOA WITH/FROM evidence.
    • Use representative members to orient family-level claims without turning a reusable module into a species-specific member list.
  5. Validate and render before committing:
    • uv run linkml-validate -s src/ai_gene_review/schema/gene_review.yaml -C ModuleReview modules/<module>.yaml
    • uv run python -m ai_gene_review.validation.module_validator modules/<module>.yaml
    • just render-module modules/<module>.yaml
    • render any touched project page with uv run ai-gene-review render-projects ...
    • run git diff --check

Reference Files

Load only the reference needed for the decision at hand:

  • references/modeling.md — module-vs-annoton placement, parts, variants, locations, exemplars, PTNs, and common anti-patterns.
  • references/research-and-grounding.md — module deep research, species/pathway satisfiability checks, gene review integration, and provenance rules.
  • references/validation-and-pr.md — validation, rendering, derived QC, cache noise, and PR checklist.

Curation Rules

  • Do not create or retain one-part modules. A standalone module needs at least two substantive parts/roles/steps at the modeled boundary; otherwise keep the work as pathway/gene curation or fold it into a broader multi-part module.
  • Avoid redundant parent/child context such as both cytoplasm and cytosol unless the distinction is intentional and explained.
  • Do not use broad parent processes as the module core when a specific process or reaction step is available. Keep broad terms as prose/context if needed.
  • Keep species-specific notes in evidence, notes, project pages, or concrete instantiations; reusable modules should stay species-neutral unless the scope is deliberately concrete.
  • Treat deep research as retrieval support, not authority. Every structural claim must still be grounded in identifiers, gene reviews, GOA/UniProt, GO-CAM, literature, or explicit curator judgment.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

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概要と使いどころ

Review AI Gene Review pull requests and curation changes for GO term quality, evidence support, core function identification, and annotation action justification. Use for PR review comments, review follow-up automation, and QA of gene review YAML.

日本語の概要は準備中です。原文の説明を表示しています。

ai4curation/ai-gene-review242026年10月13日 更新

Use this agent when you need to systematically review existing GO annotations for a gene and make curation decisions based on literature evidence and functional analysis. This agent should be called after seeding the SPECIES/GENE/GENE-ai-review.yaml file, which seeds each annotation with `action: PENDING`; these should all be manually reviewed.

日本語の概要は準備中です。原文の説明を表示しています。

ai4curation/ai-gene-review242026年10月13日 更新

Use this agent when you need to perform custom bioinformatics analyses on genes or proteins that go beyond standard database lookups. This includes situations where existing domain/family annotations from UniProt are insufficient, when you need to verify dubious annotations, or when you need to perform comparative analyses across gene sets. The agent creates reproducible analysis pipelines with proper dependency management and documentation.

日本語の概要は準備中です。原文の説明を表示しています。

ai4curation/ai-gene-review242026年10月13日 更新

Work with BioReason-Pro predictions and reasoning traces for protein function. Use when: comparing BioReason outputs against curated reviews, converting web exports to YAML, reviewing reasoning trace quality, or running the SFT/RL comparison. Triggers: "bioreason", "GO-GPT predictions", "reasoning trace review", "bioreason comparison", "SFT vs RL".

日本語の概要は準備中です。原文の説明を表示しています。

ai4curation/ai-gene-review242026年10月13日 更新

boss

無料

Use ONLY when the user explicitly asks to orchestrate parallel external agents (Codex or Claude Code) in tmux sessions via tp (tmux-pilot). Or when a user tells you that you're the boss or orchestrator. You can also use this if you are an operclaw agent. NEVER auto-invoke for a generic "do this in parallel" request. For in-process subagents, use superpowers:dispatching-parallel-agents instead.

日本語の概要は準備中です。原文の説明を表示しています。

ai4curation/ai-gene-review242026年10月13日 更新

Use this agent when you need to synthesize and distill the core functions of a gene from multiple information sources (textual summaries, reviewed annotations, bioinformatics analysis) and populate the `core_functions` section of a gene review YAML file. This agent should be called after completing the gene research, annotation review, and bioinformatics analysis phases of a gene review project.

日本語の概要は準備中です。原文の説明を表示しています。

ai4curation/ai-gene-review242026年10月13日 更新

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