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Borda/AI-Rig/plugins/codex-rig/skills/investigate/SKILL.md

investigate

Investigate code debugging and root-cause narrowing; use measurable gates before fixes.

Source repository stars
25
Declared platforms
1
Static risk flags
1
Last source update
2026-08-24
Source checked
2026-08-28

Decision brief

What it does: where it fits

See the fixed recurrence and root-cause policy and reasoning-progress escalation policy for repeated-obstacle handling; record and validate reasoning-progress.json before another cycle after an escalation trigger.

Best for

    Not for

    • Tasks that require unconfirmed production actions or broad system permissions.
    • Environments where the pinned source and install steps cannot be inspected.

    Compatibility matrix

    Platform support, with evidence labels

    PlatformStatusEvidenceWhat to check
    CodexDeclaredSource recordInstall path and trigger
    Claude CodeNot declaredNo explicit evidencePortability before use
    CursorNot declaredNo explicit evidencePortability before use
    Gemini CLINot declaredNo explicit evidencePortability before use
    Open the compatibility checker

    Installation

    Inspect first. Install second.

    The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.

    Source-detected install commandSource
    npx skills add https://github.com/Borda/AI-Rig --skill "plugins/codex-rig/skills/investigate"
    Safe inspection promptEditorial

    Inspect the Agent Skill "investigate" from https://github.com/Borda/AI-Rig/blob/1bb724c28af29d9037a9ad192551e9c7f83b65bf/plugins/codex-rig/skills/investigate/SKILL.md at commit 1bb724c28af29d9037a9ad192551e9c7f83b65bf. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.

    Workflow

    What the source asks the agent to do

    1. 01

      Workflow

      Run createrun.py --skill investigate per ../../shared/helper-cli-contract.md.

      failing command or observed behaviorexpected behaviorlocal vs CI vs external context
    2. 02

      Input Schema

      Review the “Input Schema” section in the pinned source before continuing.

      Review and apply the “Input Schema” source section.
    3. 03

      01: Create run directory

      Run createrun.py --skill investigate per ../../shared/helper-cli-contract.md.

      Run createrun.py --skill investigate per ../../shared/helper-cli-contract.md.
    4. 04

      02: Capture symptom and reproduction context

      failing command or observed behavior

      failing command or observed behaviorexpected behaviorlocal vs CI vs external context
    5. 05

      03: Gather signals before forming hypotheses

      Run git log --oneline -10 and python --version as separate argv commands. Write their complete outputs to /recent-commits.txt and /python-version.txt; record either collection failure rather than treating an empty file as successful evidence.

      Run git log --oneline -10 and python --version as separate argv commands. Write their complete outputs to /recent-commits.txt and /python-version.txt; record either collection failure rather than treating an empty file…Inspect python PLUGINROOT/shared/collectdiff.py --help, collect working-tree scope into /baseline; record collection failure, never treat as empty diff.Add needed tool logs, CI excerpts, tracebacks, config, changed source. Absence of evidence ≠ evidence of absence.

    Permission review

    Static risk signals and limitations

    Writes files

    medium · line 20

    The documentation asks the agent to create, modify, or delete local files.

    ### 01: Create run directory

    Writes files

    medium · line 26

    The documentation asks the agent to create, modify, or delete local files.

    Write `<run-directory>/symptom.md` with:

    Evidence record

    Why each signal appears

    EvidenceSourceComputedTestedEditorial
    SignalValueEvidence typeMeaning
    Quality score91/100ComputedDocumentation, specificity, maintenance, and trust rules
    Repository stars25SourceRepository attention, not individual Skill quality
    Compatibility1 platformsSourceDeclared in the catalog source record
    Usage guideautomated source guideEditorialGenerated or reviewed according to the visible evidence level

    Pinned source

    Provenance and original SKILL.md

    Repository
    Borda/AI-Rig
    Skill path
    plugins/codex-rig/skills/investigate/SKILL.md
    Commit
    1bb724c28af29d9037a9ad192551e9c7f83b65bf
    License
    Apache-2.0
    Collected
    2026-08-28
    Default branch
    main
    View the original SKILL.md

    Investigate

    See the fixed recurrence and root-cause policy and reasoning-progress escalation policy for repeated-obstacle handling; record and validate reasoning-progress.json before another cycle after an escalation trigger.

    Diagnosis-first loop for unclear failures: failing tests, tracebacks, regressions, surprising runtime behavior. Produce root-cause claim with evidence, falsification, rejected alternatives before any fix. Use investigate until root cause established; then hand off to implement or code-remediate.

    Input Schema

    {
      "symptom": "required failing command, traceback, runtime bug, CI failure, flaky behavior, or tool anomaly",
      "scope": "optional path/module/tool/CI run",
      "pace": "fast|full",
      "done_when": "one root cause is confirmed or the remaining uncertainty is explicit"
    }
    

    Workflow

    01: Create run directory

    Run create_run.py --skill investigate per ../../shared/helper-cli-contract.md.

    02: Capture symptom and reproduction context

    Write <run-directory>/symptom.md with:

    • failing command or observed behavior
    • expected behavior
    • local vs CI vs external context
    • first known bad time or commit, if known
    • whether the failure is deterministic, flaky, or unknown

    03: Gather signals before forming hypotheses

    Run git log --oneline -10 and python --version as separate argv commands. Write their complete outputs to <run-directory>/recent-commits.txt and <run-directory>/python-version.txt; record either collection failure rather than treating an empty file as successful evidence.

    Inspect python PLUGIN_ROOT/shared/collect_diff.py --help, collect working-tree scope into <run-directory>/baseline; record collection failure, never treat as empty diff.

    Add needed tool logs, CI excerpts, tracebacks, config, changed source. Absence of evidence ≠ evidence of absence.

    Structural context (optional): when scope names a Python module/symbol, select one task-neutral route and probe codemap-py once: python PLUGIN_ROOT/shared/codemap_adapter.py context --category implementation --query-kind <kind> [--target <qname>] --out <run-directory>/codemap-context.json. Use skip when the failure is localized and no structural fact is unresolved, the matching single route (central, callers, blast, dependencies, test-impact, or coupling) for one unresolved fact, and standard for broad or unknown scope. Map direct, all, or production caller questions to callers; use blast only for explicitly transitive caller questions. An explicit user or tool request for structural evidence overrides skip. Per ../../shared/codemap-contract.md, absence/incompatibility is non-fatal — continue with the signals above. Persist the result once here, before hypothesis ranking; step 05 specialist probes consume <run-directory>/codemap-context.json, never a fresh query.

    04: Rank hypotheses in <run-directory>/hypotheses.md

    | Rank | Hypothesis | Supporting evidence | Falsification check | Status |
    | --- | --- | --- | --- | --- |
    

    Include ≥3 plausible hypotheses unless failing command + code/log directly prove root cause.

    05: Orchestrate specialist probes when hypotheses split by domain

    Read and apply ../../shared/specialist-orchestration.md only for multi-domain symptoms or useful parallel evidence; do not load it for a narrow deterministic failure with one obvious hypothesis.

    Write <run-directory>/specialist-probes.md before fan-out: role, hypothesis, context path, expected falsification signal, mode (spawned, substituted, not_triggered).

    Recommended probe routing:

    • qa-specialist: flaky tests, failing assertions, regression reproduction, missing edge-case evidence.
    • cicd-steward: CI-only failure, matrix/cache/permission divergence, release workflow failures.
    • linting-expert: ruff, mypy, pre-commit, tool version or suppression anomalies.
    • security-auditor: only when the user expressly requests Sol or selects that role for auth, secret handling, deserialization, dependency, or permission-related failures; return its bounded read-only evidence artifact to the Terra parent/session for remediation and acceptance.
    • data-steward: data split, leakage, augmentation, DataLoader, or reproducibility anomalies.
    • squeezer: performance regressions, memory/OOM, throughput drops, GPU sync suspicion.
    • scientist: metric instability, paper/method mismatch, experiment validity.
    • web-explorer: volatile dependency or external API behavior.
    • challenger: root-cause claim that would be damaging if wrong.

    Each context pack: symptom slice, relevant logs/touched files/environment facts, exact falsification question. Specialists may request context; parent decides widening, consolidates outcomes, owns final root-cause claim.

    06: Probe the top hypotheses

    Use targeted probes confirming, ruling out, or narrowing one hypothesis at a time.

    Each probe must have a clear outcome:

    • confirmed
    • ruled_out
    • inconclusive

    Persist probe commands and outputs under <run-directory>/probes/ or inline in <run-directory>/probes.md.

    07: Run the anti-rationalization gate

    A root-cause claim requires:

    • supporting evidence from logs/code/commands
    • one falsification check
    • at least one rejected alternative
    • explicit confidence

    Low confidence: continue probing, no fix proposal.

    Write <run-directory>/root-cause.md with:

    • Evidence
    • Falsification
    • Rejected Alternatives
    • Confidence

    08: Run shared quality gates or targeted checks relevant to the failure

    Inspect python PLUGIN_ROOT/shared/run_gates.py --help, run full/targeted gates needed to falsify hypotheses.

    09: Decide gate result, write result.candidate.json, validate artifacts, and publish .reports/codex/investigate/<timestamp>/result.json

    Follow ../../shared/helper-cli-contract.md and authoritative help. Write with INVESTIGATE_METADATA, validate as skill investigate, and promote only the validated candidate.

    Fail-Fast Rules

    1. Missing symptom => fail.
    2. No evidence collected before hypotheses => fail.
    3. Root cause stated without falsification check => fail.
    4. Workaround presented as root cause => fail.
    5. Missing root-cause.md evidence, falsification, rejected alternatives, confidence => fail.
    6. Broad multi-domain symptom without specialist-probes.md or an explicit single-agent rationale => fail.
    7. Result artifact validator failure => fail.
    8. Result artifact missing => fail.

    Quality Gates

    Required checks:

    • review: hypothesis table, probe outcomes, rejected alternatives, and git diff --check.
    • artifact: shared validator confirms investigation artifacts, gate logs, and result JSON shape.

    Conditional checks:

    • tests: failing or confirming reproduction command when available.
    • lint, format, types: only when code/config changes are made as part of a probe.

    Calibration Hooks

    Update calibration when root-cause routing or workaround rejection changes:

    • behavioral cases: symptom-first routing, rejected alternatives, low-confidence probe escalation, artifact validator bypass
    • benchmark patterns: investigate

    Output Contract

    Before writing the result candidate, follow ../../shared/final-handoff-contract.md: render and bind final-handoff.json, final.md, and final-handoff.validation.json; after both validators and promotion pass, emit final.md verbatim.

    Use ../../shared/quality-gates.md.

    Final chat

    Final chat follows the shared frame with Next steps. Outcome: root-cause status/remediation readiness. Results: exactly Hypothesis | Evidence | Disposition | Next action, one row/hypothesis. Include probes/falsifiers; unresolved hypotheses or blocked evidence name owner.

    Minimum artifact payload template: result-template.json.

    Frequently asked questions

    What to verify before installation and use

    What does the investigate source document cover?

    See the fixed recurrence and root-cause policy and reasoning-progress escalation policy for repeated-obstacle handling; record and validate reasoning-progress.json before another cycle after an escalation trigger.

    How do I install investigate?

    The source record exposes this install command: npx skills add https://github.com/Borda/AI-Rig --skill "plugins/codex-rig/skills/investigate". Inspect the command and pinned source before running it.

    Which Agent platforms does the source record declare?

    The pinned source record declares support for: codex.

    Which permission-related actions were detected?

    Static rules flagged write-files in the source; the page lists the matching lines and excerpts.

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