Source profileQuality 89/100

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

calibrate

Codex-native calibration loop. Use to detect leaks or major gaps across packaged skills and role cards with fixed checks plus behavioral recall, precision, and confidence-accuracy scoring.

Source repository stars
24
Declared platforms
1
Static risk flags
0
Last source update
2026-08-06
Source checked
2026-08-06

Decision brief

What it does—and where it fits

Run calibration for Codex workflow integrity and behavioral scoring.

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/calibrate"
    Safe inspection promptEditorial

    Inspect the Agent Skill "calibrate" from https://github.com/Borda/AI-Rig/blob/0ed1eaa2ec1f6294996f661ea1c5078fb7e49f52/plugins/codex-rig/skills/calibrate/SKILL.md at commit 0ed1eaa2ec1f6294996f661ea1c5078fb7e49f52. 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

      Installed plugin runs use --layout plugin --root . The runner discovers package assets from its own file location under runtime/calibration, skills, roles, and shared; --root controls only report output, Git context, and read-only classification work. It must not fall back to a…

      Require source, runid, observedat. source=live- also needs route; campaign/pair IDs; pair/registered role; actual model/effort; recomputable prompt/task-contract SHA-256; task type/scope; input/cached/output tokens; lat…recall: expected IDs recovered from known cases.precision: reported IDs matching expected IDs.
    2. 02

      06: Review behavioral metrics:

      recall: expected IDs recovered from known cases.

      recall: expected IDs recovered from known cases.precision: reported IDs matching expected IDs.confidenceaccuracy: 1 - mean(abs(confidence - per-case F1)).
    3. 03

      Usage Notes

      After meaningful agent/skill instruction change, confirm routing/output match stack.

      After meaningful agent/skill instruction change, confirm routing/output match stack.leaksfound primary drift; checksfailed mechanical gate.Behavioral metrics measure supplied observations only. fixture-selftest validates scoring; live Codex quality requires replacing/appending live-prompt observations.
    4. 04

      Input Schema

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

      Review and apply the “Input Schema” source section.
    5. 05

      01: Load calibration task set from ../../runtime/calibration/tasks.json

      Review the “01: Load calibration task set from ../../runtime/calibration/tasks.json” section in the pinned source before continuing.

      Review and apply the “01: Load calibration task set from ../../runtime/calibration/tasks.json” source section.

    Permission review

    Static risk signals and limitations

    No configured static risk pattern was detected

    This is not proof of safety. Runtime behavior, indirect dependencies, and hidden external systems are outside the static scan.

    Evidence record

    Why each signal appears

    EvidenceSourceComputedTestedEditorial
    SignalValueEvidence typeMeaning
    Quality score89/100ComputedDocumentation, specificity, maintenance, and trust rules
    Repository stars24SourceRepository 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/calibrate/SKILL.md
    Commit
    0ed1eaa2ec1f6294996f661ea1c5078fb7e49f52
    License
    Apache-2.0
    Collected
    2026-08-06
    Default branch
    main
    View the original SKILL.md

    Calibrate

    Run calibration for Codex workflow integrity and behavioral scoring.

    Input Schema

    {
      "scope": "skills|agents|routing|all",
      "pace": "fast|full",
      "mode": "ab-test|apply",
      "require_live_routes": false,
      "skip_gate": false,
      "done_when": "recall and bias scores emitted; proposals written if mode=apply; gate skipped if skip_gate=true"
    }
    

    Workflow

    Installed plugin runs use --layout plugin --root <consuming-project>. The runner discovers package assets from its own file location under runtime/calibration, skills, roles, and shared; --root controls only report output, Git context, and read-only classification work. It must not fall back to a source checkout or project .codex.

    Repository maintainers may use --layout source --root <source-project> to validate the source .codex layout. Do not mix source agents, sync manifests, or project registration checks into an installed-plugin result.

    01: Load calibration task set from ../../runtime/calibration/tasks.json

    02: Load behavioral cases from ../../runtime/calibration/behavioral-cases.json

    03: Load behavioral observations from ../../runtime/calibration/behavioral-observations.jsonl

    • Require source, run_id, observed_at. source=live-* also needs route; campaign/pair IDs; pair/registered role; actual model/effort; recomputable prompt/task-contract SHA-256; task type/scope; input/cached/output tokens; latency; outcome; tool/check failures; normalized cost; pricing reference. Each complete campaign exactly matches case/role/type/scope signatures in live-ab-tasks.json; substituted task, fixture, gate, prompt input fails.

    04: Inspect ../../runtime/calibration/run.py --help, then run plugin layout against the consuming project

    Use --require-live-routes only for the strict-live gate. Default offline scoring remains fixture-backed and makes no paid model calls.

    05: Inspect checks_failed, leaks_found, and behavioral

    06: Review behavioral metrics:

    • recall: expected IDs recovered from known cases.
    • precision: reported IDs matching expected IDs.
    • confidence_accuracy: 1 - mean(abs(confidence - per-case F1)).
    • mean_overconfidence: mean positive confidence bias over per-case F1.
    • gate_metrics_raw: unrounded pass/fail values.
    • by_source: recall, precision, confidence calibration by source.
    • observation_freshness: latest observed_at, missing timestamps, live/fixture counts.
    • live_route_acceptance: matched baseline/candidate classification and isolated tool-use quality, normalized token-efficiency proxy, evidence sufficiency per configured route; not monetary pricing evidence.

    07: Classify gaps as blocking or non-blocking

    08: Emit measured recommendations for what should be fixed or improved next

    • Failed checks/leaks first.
    • Behavioral recommendations name metric gap/affected cases when available.
    • Separate fixture-only caveats from live-quality claims.

    09: Write skill artifacts to .reports/codex/calibrate/<timestamp>/; preserve runner evidence under .reports/codex/calibration/<timestamp>/

    10: Write the validated skill-level artifact when this skill wraps the runner

    Follow ../../shared/helper-cli-contract.md/authoritative help. Gate intent: ruff lint/format calibration+skills, explicit no-typed-target reason, calibration tests, clean diff. Write CALIBRATE_METADATA, validate calibrate, promote only validated candidate.

    Native Contract Checks

    Verify configured native surface, not only runner internals.

    Skill checks:

    • configured skill file exists; frontmatter has unindented ---, name:, description:; required sections exist; artifact path .reports/codex/<skill>/; examples include status, checks_run, checks_failed, findings, confidence, artifact_path; no external runner-only metadata/cache.
    • CLI checks find every local shebang Python/shell entry point in calibration, shared helpers, code-review, offline harness; each executable, fixed-help-roster registered, authoritative --help.
    • every skill references helper-cli-contract.md, not complete local CLI invocations.
    • source layout compares ../../runtime/calibration/behavioral-cases.json version to HEAD: dirty tree same or exactly one commit-relative version step; installed plugin layout records the packaged fixture as immutable.

    Role checks:

    • installed layout requires every packaged roles/<role>/ROLE.md; source layout requires each configured source agent.
    • role-card frontmatter contains role ID, namespaced name, active model, reasoning effort, approval policy, sandbox, and fallback modes; package-manifest skill/role rosters contain every calibrated target.
    • default, review parent, runtime, research, curation, adversarial use gpt-5.6-terra; delegation/docs/CI-CD/web/OSS/static analysis use gpt-5.6-luna; only security/solution architecture use gpt-5.6-sol.
    • Luna/high is explicit human override for bounded simpler roles; preserve strict quality/cost failure, reject undocumented expansion.
    • every role defaults high; xhigh/max explicit task escalation. model_reasoning_effort follows agent-effort-policy: all high, xhigh/max task overrides.
    • high-stakes roles use high-capability tier; bounded support may lower-cost tier. No deprecated model string in active config/TOML.
    • role has clear trigger/skip/not-for boundaries, evidence ownership, execution constraints, handover, and confidence contracts; sensitive roles retain sandbox, especially read-only security audit; packaged roles require no external runtime path variable.

    Usage Notes

    • After meaningful agent/skill instruction change, confirm routing/output match stack.
    • leaks_found primary drift; checks_failed mechanical gate.
    • Behavioral metrics measure supplied observations only. fixture-selftest validates scoring; live Codex quality requires replacing/appending live-prompt observations.
    • Missing route coverage is insufficient-evidence, never acceptance; require_live_routes=true exits nonzero.
    • Compare thresholds with gate_metrics_raw, not rounded display.
    • Paid paired campaigns: ../../runtime/calibration/run_live_ab.py; plans by default, executes only --confirm-paid-run=chatgpt-subscription, verified local ChatGPT subscription login, no API key env, no CI/GITHUB_ACTIONS.
    • Each live task names a canonical role. Plugin layout prepends the exact packaged role card to both prompts; source layout preserves project-instruction plus source-agent prompt construction. Tool pairs can accept a candidate passing an executable gate when the successfully invoked baseline fails; infrastructure timeout is never a candidate win.
    • Sol critical-only unless paired quality exceeds Terra configured minimum; tie retains Terra.
    • Do not claim currency savings from normalized-token-v1; need dated authoritative model-specific price.
    • Fixture version is committed-history marker: compare git show HEAD:<path>; dirty tree stays committed or one-next version until commit.
    • Missing registration/pattern mismatch: minimal config fix then rerun before widening.

    Fail-Fast Rules

    1. Missing calibration files => fail.
    2. Missing configured skill or role file => fail.
    3. Native skill/role contract mismatch => fail unless result waives.
    4. Runtime leakage in native skill or role files => fail.
    5. Behavioral gate below threshold => fail.
    6. Result artifact missing => fail.
    7. Behavioral case-set version >1 step from committed version => fail.
    8. require_live_routes=true with incomplete route pairs => fail.
    9. Live row without the strict paired execution schema => fail.

    Quality Gates

    Required checks:

    • calibration: ../../runtime/calibration/run.py --layout plugin --root <consuming-project>.
    • behavioral-version-policy: compare case-set version to HEAD; avoid meaningless dirty-tree gaps.
    • review: inspect failed patterns, leaks, behavioral gaps, stale fixtures before recommendations.

    Conditional checks:

    • tests: run focused tests when calibration code changes.
    • format: validate JSON and shell syntax when calibration fixtures change.

    Calibration Hooks

    When calibration expectations change, update together:

    • ../../runtime/calibration/benchmarks.json
    • ../../runtime/calibration/behavioral-cases.json
    • ../../runtime/calibration/behavioral-observations.jsonl
    • ../../runtime/calibration/run.py
    • ../../runtime/calibration/live-route-policy.json
    • ../../runtime/calibration/live-ab-tasks.json
    • ../../runtime/calibration/run_live_ab.py

    Output Contract

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

    Minimum artifact payload template: result-template.json.

    Alternatives

    Compare before choosing