agentsclimarketplace

Analyse

Skill Borda/AI-Rig/plugins/codex-rig/skills/analyse

A collection of personal AI coding assistant configurations, specialist agents, and automated workflows optimized for Python and ML open-source development.

Install
npx -y skills add Borda/AI-Rig --skill analyse

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 23 stars23 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Minimal codex-native analysis loop. Use for issue/PR/problem analysis before implementation with measurable gates.

SKILL.md

5.8 KB, as published. Nobody here has run it

Analyse

Run evidence-first analysis: truth, risk, next action before implementation, review, release, sync.

Input Schema

{
  "question": "required analysis question",
  "scope": "required files, diff, issue text, report path, PR number, or repo area",
  "mode": "local|github|report|ecosystem",
  "done_when": "findings are source-backed, ranked, and have explicit confidence"
}

Workflow

Codex provides this selected SKILL.md path. Resolve PLUGIN_ROOT as the directory two levels above the containing skill directory, then use only helpers under PLUGIN_ROOT/shared/ that are listed in package-manifest.json. Never guess a cache version or fall back to a source checkout.

01: Create run directory

Run python PLUGIN_ROOT/shared/create_run.py --skill analyse once. Retain its single printed path as <run-directory> and substitute that literal path into every later artifact path and helper argument. Never store or reuse the path through a shell variable; shell variables do not persist across tool calls.

02: Normalize the analysis mode

  • local: code, local diff/reports, pasted text.
  • github: live issue/PR/discussion metadata.
  • report: .reports/** or .reports/codex/** artifact.
  • ecosystem: downstream/API/dependency impact; current external claims need live web/gh evidence.

Unsupported/ambiguous mode => fail with usage note, unless pasted evidence supports local.

03: Capture scope and source inventory before drawing conclusions

Use python PLUGIN_ROOT/shared/collect_diff.py --help; collect working-tree into <run-directory>/baseline. Scan references separately; record failed diff collection.

Structural context (optional): for local/ecosystem scope naming a Python module or symbol, probe codemap-py once: python PLUGIN_ROOT/shared/codemap_adapter.py context --category analysis [--target <qname>] --out <run-directory>/codemap-context.json. Per ../../shared/codemap-contract.md, absence/incompatibility is non-fatal — continue with the evidence above. Persist the result once here; step 05 specialist fan-out consumes <run-directory>/codemap-context.json, never a fresh query.

04: Gather evidence with a ledger. Write <run-directory>/evidence.md with one row per claim:

| Claim | Source | Freshness | Confidence | Notes |
| --- | --- | --- | --- | --- |

Evidence rules:

  • Code claims: file/line refs.
  • External/current: primary sources or unavailable-live-verification caveat.
  • Thread/report: distinguish facts/hypotheses.
  • List duplicate/related findings; do not silently collapse.

05: Orchestrate specialist analysis when the question has independent axes

Use ../../shared/specialist-orchestration.md for broad/multi-risk PR/issue, ecosystem, or independently challenged conclusions. Stay single-agent when narrow local fan-out duplicates context.

Write <run-directory>/orchestration.md when fan-out is used or intentionally skipped for a broad scope. Include:

  • specialist axes considered
  • context pack per triggered axis
  • skipped axes with rationale
  • consolidation plan

Routes: solution-architect architecture/API; qa-specialist testability; security-auditor risk; web-explorer current ecosystem; scientist method; curator config/workflow drift; challenger high-impact conclusions.

06: Analyze alternatives before recommending action

Required sections in <run-directory>/analysis.md:

  • Question
  • Scope
  • Verified Facts
  • Hypotheses
  • Rejected Alternatives
  • Findings
  • Recommendations
  • Gaps

07: Run the self-review check

Run git diff --check as an argv command. Write its combined output to <run-directory>/review.txt and retain its exit status as review evidence; do not erase a nonzero result.

08: Decide gate result

  • pass: evidence-backed ranked findings, explicit gaps.
  • fail: missing scope/blocking-claim evidence, stale external claim as fact, or no result artifact.

09: Run shared gates and write the validated result artifact

Follow ../../shared/helper-cli-contract.md and helper --help. Analysis-only: mark lint/format/types/tests not applicable with reasons; review needs non-empty analysis.md, self-review.md, clean diff. Write ANALYSE_METADATA, validate analyse, promote only validated candidate.

Replace skip with command when analysis includes code changes/executable probes.

Self-Critical Gate

Before final output, answer in <run-directory>/self-review.md:

  1. Which claim would be most damaging if wrong?
  2. What evidence directly supports it?
  3. What plausible alternative did you rule out?
  4. Which facts are unverified or stale?
  5. What next check would most improve confidence?

Critical conclusion without self-review cannot pass.

Fail-Fast Rules

  1. Missing question or scope => fail.
  2. Unsupported mode with insufficient pasted/local evidence => fail.
  3. Current external claim lacks live primary-source evidence/stale-unverified caveat => fail.
  4. Blocking conclusion without evidence ledger entry => fail.
  5. Missing self-review for critical conclusions => fail.
  6. Broad multi-axis analysis lacks orchestration evidence/skip rationale => fail.
  7. Result artifact missing => fail.

Quality Gates

Required checks:

  • review: evidence ledger, self-review, git diff --check when diff exists.

Optional checks:

  • lint, format, types, tests: only with code changes/executable probes.

Calibration Hooks

Update calibration when routing or evidence expectations change:

  • benchmark patterns: analyse
  • behavioral cases: unsupported claims, stale-source caveats, duplicate/related-item handling

Output Contract

Use shared gate schema from ../../shared/quality-gates.md.

Minimum artifact payload template: result-template.json.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.