القائمة
Review, either de-novo, or augment the review of an existing one. A list of deep research providers may be specified.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Use when running or wiring OpenScientist for AI Gene Review gene-function hypotheses, especially blinded comparisons against local bioinformatics analyses.
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.
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".
Review computational protein or gene function predictions and fill PredictionReview YAML files using the COR/CNN/LSP/UNC/PLI/NPI/REP biological-validity taxonomy. Use for DeepECTF, BioReason/GO-GPT, InterPro2GO, PANTHER/IBA, CLEAN, GloEC, MAPred, ProteinInfer, or other predicted EC/GO annotations.
Evaluate and review GO-CAM (Gene Ontology Causal Activity Model) activities / annotons — molecular-function typing, has-input, causal relations, complexes, evidence — and check their consistency with gene annotation reviews. Use when reviewing cached GO-CAMs under gocams/, filling a GoCamReview YAML (gocams/<id>/<id>-review.yaml), or grounding a module in GO-CAM models.
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.
| name | review |
| description | Review, either de-novo, or augment the review of an existing one. A list of deep research providers may be specified. |
| argument-hint | [ORGANISM] [GENE_SYMBOL] (using [DEEP_RESEARCH_PROVIDER]) |
Review the gene specified in $ARGUMENTS.
IMPORTANT: you MUST consult the annotation-reviewer.md subagent for this task.
Run just fetch-gene ORGANISM GENE_SYMBOL if the gene directory doesn't exist yet.
Publication caching only needs the GOA file (created by fetch-gene), so it can run concurrently with deep research. Launch both at the same time:
--fallback perplexity-lite so that if the primary
provider times out, it automatically retries with perplexity-lite.
E.g. just deep-research-falcon ORGANISM GENE_SYMBOL --fallback perplexity-litejust fetch-gene-pmids ORGANISM GENE_SYMBOLRun these two steps in parallel (e.g. as concurrent background agents or shell jobs). Do NOT wait for deep research to finish before starting publication caching.
For bacterial organisms (e.g. PSEPK, ECOLI, SALTY, or any prokaryote), after deep research, also fetch FEBA/RB-TnSeq fitness data if available:
just fetch-fitness ORGANISM GENE_SYMBOL
This creates a GENE-fitness.md file with mutant fitness phenotypes and cofitness partners. The annotation-reviewer agent will use this data as additional evidence when reviewing annotations.
Invoke the annotation-reviewer subagent to systematically review all annotations.