trace-analysis
Skill304 starsChanged 2 months agoMITView on GitHub
Trace an analytical claim to its receipt, source, query, result, and run evidence. Use when the user asks where a number came from, wants to verify a query, or needs to inspect provenance.
3 other projects use a version of this.
Adopted by
Most recently taken up by
- gabriellst/codmtheir own version, first seen Aug 26, 2026
- zl3311/alpha-miningtheir own version, first seen Jul 25, 2026
- itsmuskanagarwal/effective-agents-labtheir own version, first seen Jul 9, 2026
Other versions3 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 3
- gabriellst/codm★ 4same name
- itsmuskanagarwal/effective-agents-lab★ 0same name
- zl3311/alpha-mining★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository65 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- always-compareSkill
- analysis-designSkill
- analyst-coreSkill
- archaeologySkill
- archive-analysisSkill
- auth-preflightSkill
- businessSkill
- causalSkill
- chart-to-driveSkill
- close-the-loopSkill
- codex-reviewSkill
- compare-datasetsSkill
- connect-dataSkill
- connect-snowflakeSkill
- context-compareSkill
- context-traceSkill
- data-inspectSkill
- data-mapSkill
- data-profilingSkill
- data-quality-checkSkill
- datasetsSkill
- distribution-profilerSkill
- evalSkill
- evaluate-graderSkill
- experiment-briefSkill
- experimentSkill
- exploreSkill
- exportSkill
- forecastSkill
- google-doc-exportSkill
- google-slides-exportSkill
- guardrailsSkill
- historySkill
- improve-contextSkill
- knowledge-bootstrapSkill
- log-correctionSkill
- maintain-contextSkill
- metric-specSkill
- metricsSkill
- monitor-evalsSkill
- notion-exportSkill
- paceSkill
- patternsSkill
- question-framingSkill
- question-routerSkill
- reliabilitySkill
- resume-pipelineSkill
- run-pipelineSkill
- runsSkill
- score-analysisSkill
- session-handoffSkill
- setup-dev-contextSkill
- setup-notionSkill
- setupSkill
- setup-slackSkill
- setup-snowflakeSkill
- srm-checkSkill
- stakeholder-communicationSkill
- stress-testSkill
- The first 60 shown.
The file
Files
Trace one analysis
First invoke the trace skill so the machine-readable provenance record,
lightweight receipt, and shareable HTML exist. Then review the claim through
these records:
- The output states the claim.
- The receipt identifies the source, data snapshot, query, and artifacts.
- The trace records how the run unfolded.
- Logs record specific system and query events.
- The query and result provide execution evidence.
Use helpers.evals.trace.inspect_receipt on
working/trace_receipt_<analysis_id>.json to identify missing fields and
initial query risks. Then inspect the analytical details that code cannot infer
from syntax alone: population, filters, time window, timezone, exclusions,
grain, join cardinality, missingness, referential integrity, freshness,
reconciliation, and whether the claim stays within the evidence.
For a query with a join and aggregate, test the grain directly. Compare the candidate total with a defensible reference query when one exists. A query that runs successfully may still answer the wrong question.
Save the written review beside the analysis. Report the review path and the HTML trace path together. Report missing evidence as missing. A complete receipt makes an analysis inspectable. It does not make the analysis correct.
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Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
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