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sdrf-improve
Use when the user wants to improve an existing SDRF file strictly according to SDRF templates and specification rules (no speculative additions).
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。
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Use when the user wants to improve an existing SDRF file strictly according to SDRF templates and specification rules (no speculative additions).
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
Independently falsify and review a created, modified, or proposed SDRF against its specification, ontology terms, source evidence, repository files, and experimental design. Use after SDRF annotation or repair, before contribution or completion, when a review gate reports a pending artifact, or whenever an isolated reviewer must distrust the producer's self-assessment and issue a hash-bound verdict.
Create or improve an SDRF through a producer-reviewer workflow with deterministic validation, an evidence manifest, fresh-context adversarial review, repair, and mandatory re-review. Use when an SDRF must be independently verified before completion or contribution, when the user requests adversarial review, or when automated review hooks require a passing hash-bound receipt.
Use when the user wants SDRF annotation to run as an autonomous retained-improvement loop over one dataset, a manifest, or a dataset class such as all PRIDE cell line or crosslinking datasets.
Use when the user has a completed SDRF annotation for a ProteomeXchange dataset and wants to contribute it back to the community via a PR to sdrf-annotated-datasets.
Use when the user wants a comprehensive quality review of an SDRF file, a PR review of an SDRF submission, or a quality score assessment.
Use before sdrf:autoresearch when the user needs to screen or shortlist proteomics studies from PRIDE, MassIVE, ProteomeXchange accessions, or a manifest using detailed user-defined inclusion/exclusion criteria; extract study-level metadata from repository records and publications; and write an evidence-backed TSV for downstream annotation, review, or meta-analysis.
| name | sdrf:improve |
| description | Use when the user wants to improve an existing SDRF file strictly according to SDRF templates and specification rules (no speculative additions). |
| user-invocable | true |
| argument-hint | [file path or paste SDRF content] |
You are improving an SDRF file using ONLY specification/template rules.
Do not suggest additions based on:
If a change is not justified by template metadata (required/recommended) or
TERMS.tsv rules, do not recommend it.
spec/sdrf-proteomics/TERMS.tsvspec/sdrf-proteomics/sdrf-templates/templates.yamlspec/sdrf-proteomics/sdrf-templates/{name}/{version}/{name}.yaml for each template in useFor affinity-proteomics, align with the official template/spec rules:
affinity-proteomicsolink OR somascan (mutually exclusive)comment[sdrf template] columns (NT/VV format).Do not "upgrade" template versions automatically. If a newer version exists, report it as an optional migration task.
Construct an explicit checklist from template YAML files:
not available, not applicable, pooled) via TERMS.tsv flagsFor affinity-proteomics specifically, ensure checks include:
comment[platform] (required)comment[panel name] (recommended)comment[quantification unit] (optional; values include NPX/RFU in spec)comment[normalization method] (optional)comment[fraction identifier] (optional)And for child templates:
olink.yamlsomascan.yamlClassify findings into these categories only:
recommended in active templatesDo not include free-form "quality" recommendations outside A/B/C.
Report every finding with source traceability:
required / recommended / optional)Example format:
Finding: Missing column `comment[panel name]`
Severity: recommended
Source: spec/sdrf-proteomics/sdrf-templates/affinity-proteomics/1.0.0/affinity-proteomics.yaml
Action: Add `comment[panel name]` with panel identifier values.
Before modifying file contents:
Required fixes can be applied directly if the user asked to "fix all required issues."
The goal is strict conformance improvement, not curation enrichment.