calibrate

Before asking, read User Questions.

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, shared; --root controls only report output, Git context, read-only classification work. It must not fall back to source checkout or project .codex.

Repository maintainers may use --layout source --root <source-project> to validate source .codex layout. Never mix source agents, sync manifests, or project registration checks into 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 strict-live gate. Default offline scoring remains fixture-backed and makes no paid model calls. Composition/outcome checks reject known redundant orchestration, conflicting active instructions, false progress stalls, and premature review plateaus; they are bounded regressions rather than a general natural-language policy proof. Historical GPT-5.6 observations stay archived. The live runner rejects selected models outside its supported GPT 6+ lineup before planning, authentication, or calls; fresh GPT-6 paired route evidence requires a separately supplied policy and authorized collection.

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

• Start with plain-English explanation of whether calibration passed and what any failure means. Then prioritize failed checks/leaks, naming exact check, file or pattern, evidence, next-action owner, and gate that must pass to resume acceptance.
• 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.
• a source checkout compares the shipped ../../runtime/calibration/behavioral-cases.json integer schema_version to that file in HEAD: same or exactly one commit-relative version step; a new family starts at 1. Installed plugin layout records an immutable-fixture skip; source layout with no .codex/calibration/behavioral-cases.json records a missing-source-fixture skip.

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.
• normal parent, review model, implementation, runtime, research, data, adversarial, performance, and executable verification use gpt-6.1-sol; delegation/docs/CI-CD/web/OSS/static analysis/curation use gpt-6-luna.
• accepted-route-evidence.json binds active_assignments to every GPT-6 role model/effort pair and direct parent/deep-review routes; active_assignment_basis marks paired quality/cost evidence pending. Preserve archived GPT-5.6 strict failures and reject unsupported GPT-6 quality claims.
• model_reasoning_effort follows the agent-effort-policy: normal parent, implementation, verification, performance, static analysis, and web evidence use medium; deep review, data/research method, challenge, coordination, documentation, CI/CD, OSS, curation, architecture, and security use high. xhigh/max require evidenced task escalation.
• 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.
• plugin-layout calibration checks one distinct task cue in each of the fifteen shipped role-card Trigger lines; a missing or multiply owned cue fails agent-task-routing. This checks declared routing only; live task selection still needs live observations.

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. An executing campaign applies full networked CLI approval and denial contract in ../../shared/native-skill-contract.md to complete owning command because it spawns codex exec. The operation-specific brief is: Action and purpose: run confirmed paid paired calibration; External capability: paid ChatGPT subscription execution through codex exec; Credential behavior: use verified local ChatGPT subscription login without reading API keys or credentials; Filesystem and worktree effects: write calibration artifacts only to selected run directory; Retry policy and safe denial outcome: stop turn on denial, retain sandboxed planning or offline scoring only. Planning and offline scoring remain sandboxed.
• Each live task names canonical role. Plugin layout prepends exact packaged role card to both prompts; source layout preserves project-instruction plus source-agent prompt construction. Tool pairs can accept candidate passing executable gate when successfully invoked baseline fails; infrastructure timeout is never candidate win.
• Archived GPT-5.6 paired evidence and live-route-policy.json keep their original Sol/Terra quality rule; that legacy campaign must not be used to validate GPT-6 routing. Define a new model-and-effort paired campaign before claiming GPT-6 quality or cost acceptance.
• Never claim currency savings from normalized-token-v1; need dated authoritative model-specific price.
• Fixture schema_version is a committed-history marker: compare the actual shipped path with git show HEAD:<path>; dirty tree stays committed or one-next version until commit. An absent source-layout fixture records a skip, not a completed check.
• Missing registration/pattern mismatch: inspect named file and expected registration or pattern first; record observed mismatch. Apply smallest evidenced correction only within authorized edit scope, then rerun that failed check before widening. Otherwise ask for exact missing file, scope approval, or owner decision; never offer only "fix configuration and retry".

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 schema_version skips or downgrades from committed HEAD, or starts a new family above 1 => fail.
8. require_live_routes=true with incomplete route pairs => fail.
9. Live row without strict paired execution schema => fail.

Quality Gates

Required checks:

• calibration: ../../runtime/calibration/run.py --layout plugin --root <consuming-project>.
• behavioral-version-policy: compare the shipped case-set integer schema_version to its own HEAD path in a source checkout; record explicit installed-cache or missing-source-fixture skips.
• 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

Behavioral coverage includes networked CLI owning-command approval for paid live execution.

Output Contract

Before writing 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 shared ordered frame. Outcome is pass, fail, or insufficient-evidence. Results has one measured check or metric per row and exactly Check / metric | Result | Evidence | Next action. Apply shared Verification, Remaining, Next steps, Confidence, and supplemental Artifact rules; include runner mode/coverage, every failed/skipped/deferred check, and calibration recovery evidence.

Minimum artifact payload template: result-template.json.