| name | co-scientist-audit-report |
| description | Research audit report skill. Systematic quality assessment of experimental designs, statistical analyses, reproducibility, and reporting standards compliance.
Use when working with systematic quality assessment of experimental designs, statistical analyses, reproducibility.
|
Research audit report
Research audit report skill. Systematic quality assessment of experimental designs, statistical analyses, reproducibility, and reporting standards compliance.
Use This Skill When
- Systematic quality assessment of experimental designs.
- Statistical analyses.
- Reproducibility.
- Reporting standards compliance.
Required Inputs
- Research objective, decision target, or hypothesis.
- Available data, source constraints, and domain assumptions.
- Required outputs, success metrics, and deadline or reproducibility constraints.
Workflow
- Confirm scope, assumptions, and the exact artifact set to save.
- Apply the narrowest domain method that answers the request with defensible evidence.
- Save code, tables, figures, and intermediate outputs to files instead of chat-only output.
- State limitations, uncertainty, and any validation or sensitivity checks performed.
- Append skill selection, handoff I/O, and file writes to
logs/process-log.jsonl.
Deliverables
report.md: concise method, results, interpretation, and file inventory in the user's language.
results/: structured outputs, metrics, model artifacts, or extracted findings.
figures/: English-only charts, diagrams, or panels when visual output is needed.
data/: processed or derived datasets when transformation occurs.
Quality Gates
If any gate fails: identify the specific failing check, fix the issue, and re-validate before proceeding.
Gotchas
- Citation style varies by journal (author-year vs numbered). Confirm target format before writing
- Claims in Discussion must trace back to specific Results. Do not introduce new data in Discussion
- Supplementary materials must be self-contained with their own figure/table numbering
Validation Loop
- Execute analysis and generate outputs
- Check:
- Method selection matches the research question and stated assumptions
- All outputs are saved to files (no chat-only results)
- Limitations and uncertainty are explicitly stated
logs/process-log.jsonl is updated with execution trace
- If any check fails:
- Identify the failing gate
- Fix the specific issue
- Re-run validation
- Proceed only after all gates pass