agentsclimarketplace

Eval

Skill Kanevry/session-orchestrator/skills/eval

Loop engineering for AI coding agents — turn ad-hoc sessions into a repeatable research → plan → wave-execute → close loop with verification gates. Runs on Claude Code, Codex CLI, Cursor, and Pi. MIT community plugin.

Install
npx -y skills add Kanevry/session-orchestrator --skill eval

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

What its author says it does

Copied from the file, not written here

Use this skill to run an honest session-process evaluation (Standard v1, aiat-llm-eval/1.0) — score the last completed orchestrator session against the pre-registered rubric-v1 dimensions, run /eval, evaluate this session, produce an eval report, or re-verify a stored eval run for reproducibility. Deterministic-first with an optional advisory LLM judge; never produces a global score.

SKILL.md

13.4 KB, as published. Nobody here has run it

Platform Note: State files use the platform's native directory: .claude/ (Claude Code), .codex/ (Codex CLI), or .cursor/ (Cursor IDE). Shared metrics + the eval journal live in .orchestrator/metrics/. See skills/_shared/platform-tools.md.

Eval Skill — Session-Process Evaluation (aiat-llm-eval/1.0)

On-demand, honest measurement of ONE completed orchestrator session against the pre-registered rubric-v1 check set. The deterministic engine (scripts/eval-session.mjsscripts/lib/eval/engine.mjs) reads only local metrics files (sessions.jsonl + events.jsonl), scores the five deterministic dimensions, appends a session-eval record to the journal, and optionally renders an HTML report. An opt-in LLM judge overlays two advisory dimensions.

The standard this skill implements is docs/eval/aiat-llm-eval-v1.md; the frozen, content-hashed check set is skills/eval/rubric-v1.md.

Posture Contract (load-bearing — read before executing)

  • No global score, by construction. The record has no overall/total/mean field, and this skill never derives one. Report per-dimension verdicts only.
  • Never guess. Missing source data yields cannot-determine (a first-class, non-error verdict) with an honest reason — never a fabricated pass/fail. Do NOT "fill in" a missing KPI or infer a gate result the events do not show.
  • Deterministic before judge. The five deterministic dimensions are complete on their own. The judge (Phase 3) is opt-in, ADVISORY, and uncalibrated in v1 — never blend a judge verdict into the deterministic tally.
  • Journal is SSOT; the report is a derived view. The append-only .orchestrator/metrics/eval.jsonl is authoritative. The HTML report is rebuildable from any stored record and is never authoritative over the journal.
  • --verify is the reproducibility proof. Re-scoring stored source data reproduces the stored dimensions byte-for-byte (exit 0) or reports drift (exit 1). This proves the SCORING replays — NOT that the model is deterministic.
  • Self-evaluation is labelled as such. The orchestrator scoring its own session is a self-evaluation, not an independent audit.

Phase 0: Bootstrap Gate

Read skills/_shared/bootstrap-gate.md and execute the gate check. If the gate is CLOSED, invoke skills/bootstrap/SKILL.md and wait for completion before proceeding. If the gate is OPEN, continue to Phase 1.

<HARD-GATE> Do NOT proceed past Phase 0 if GATE_CLOSED. There is no bypass. Refer to `skills/_shared/bootstrap-gate.md` for the full HARD-GATE constraints. </HARD-GATE>

Phase 1: Config & Argument Loading

1.1 Read Session Config

Read and parse Session Config per skills/_shared/config-reading.md. Extract the eval block (scripts/lib/config.mjs returns it as config.eval, parsed by scripts/lib/config/eval.mjs):

enabled:  boolean  (default false)
mode:     'warn' | 'off'            (default 'warn')
judge:    'off' | 'haiku' | 'sonnet' (default 'off')
report:   'html' | 'none'           (default 'html')
handle:   string | null             (default null)

On-demand /eval runs regardless of eval.enabled. The enabled flag gates the AUTOMATIC session-end eval phase only — it does NOT gate this command (same posture as /reconcile vs reconcile.enabled). mode: off is honoured as a kill-switch only for the automatic phase; on-demand invocation still runs. If eval.judge is off, skip Phase 3 entirely.

Parser gotcha: the eval: key-line itself MUST NOT carry an inline comment (strict /^eval:\s*$/); a trailing # comment on that exact line makes the parser skip the whole block and silently apply ALL defaults. Sub-key lines tolerate inline comments.

1.2 Parse Arguments

Inspect $ARGUMENTS:

  • --session <id> → pass through to --session.
  • --no-write → evaluate without appending to the journal (dry-run).
  • --verify <run-id>verification mode: skip Phases 2–4, run the CLI --verify path (see Phase 6), report MATCH/DRIFT, done.

1.3 Capture the Model Id (honest provenance)

The record's model.source records HOW the model id was captured, precisely because self-report is unreliable:

  • If $ANTHROPIC_MODEL is set in the environment, the engine reads it automatically with source: envenv wins over the flag (precedence env > flag). Do not pass --model-id in that case; let the engine resolve it.
  • Otherwise the coordinator passes its own self-reported model id: --model-id <self-reported-model-id> --model-source self-report.

Phase 2: Deterministic Run

Run the deterministic engine via its CLI. Default target is the last completed session (resolution cascade); --session overrides.

node scripts/eval-session.mjs [--session <id>] --json \
  [--model-id <self-reported-id> --model-source self-report] \
  [--no-write]
  • Do NOT pass --metrics-dir for a real run — the engine defaults to the live .orchestrator/metrics, the session being evaluated.
  • The CLI captures the eval timestamp (the one sanctioned clock read) and hands it to the engine as a parameter, so the scoring path stays clock-free and --verify-reproducible.
  • Exit codes: 0 success · 1 user error (session not found) · 2 system error. On exit 1 (e.g. "no completed session found"), surface the message and stop — do not retry with fabricated inputs.

Parse the emitted JSON record. It carries dimensions[] (5 deterministic entries), kpis{}, provenance.rubric_sha256 (non-null once rubric-v1.md exists), model, harness, and run_id. Unless --no-write was passed, the record is already appended to .orchestrator/metrics/eval.jsonl by the CLI.

Contamination check: if the human-render/summary reports a peer-overlapped window, note it — verification-evidence and gate-health will read cannot-determine for that reason (attribution is unsafe), which is correct, not a defect.


Phase 3: Judge Overlay (ONLY when eval.judge != off)

The judge runs coordinator-sideAskUserQuestion and the Agent tool are not available inside a dispatched subagent, so the judge is dispatched from the coordinator thread using the read-only agent session-orchestrator:eval-judge (model = eval.judge). Reference the API; do not reimplement scoring here:

import { runEvalJudge, mergeJudgeDimensions } from '$PLUGIN_ROOT/scripts/lib/eval/judge.mjs';
import { appendEvalRecord } from '$PLUGIN_ROOT/scripts/lib/eval/sink.mjs';

// dispatchAgent = the coordinator's Agent-tool dispatch closure targeting
// subagent_type 'session-orchestrator:eval-judge'.
const { status, dimensions } = await runEvalJudge({
  dispatchAgent,
  record,                       // the deterministic record from Phase 2
  model: EVAL_JUDGE_MODEL,      // eval.judge ('haiku' | 'sonnet')
  budget: JUDGE_BUDGET_TOKENS,  // optional
});

// mergeJudgeDimensions appends the advisory judge dimensions to the record.
const merged = mergeJudgeDimensions(record, dimensions);

// The COORDINATOR appends the enriched record (subagents never write the journal).
appendEvalRecord(merged, { path: '.orchestrator/metrics/eval.jsonl' });
  • Every judge dimension arrives advisory: true + calibration_status: "uncalibrated" (the schema firewall rejects any other shape). Keep them visibly separated from the deterministic five in the summary.
  • If runEvalJudge returns a non-ok status (e.g. dispatch failed), keep the deterministic record as-is and note the judge was unavailable — the deterministic evaluation is complete without it.
  • When --no-write was passed in Phase 2, do NOT append the merged record either.

The judge merge re-writes the record with the SAME run_id/timestamp, so a later --verify <run-id> re-scores the deterministic dimensions from source and diffs them; judge dimensions are advisory and excluded from the drift diff.


Phase 4: Report (ONLY when eval.report == html)

Render the derived HTML view from the record:

import { writeEvalReport } from '$PLUGIN_ROOT/scripts/lib/eval/report.mjs';

const res = writeEvalReport(record, { generatedAt: new Date().toISOString() });
// res.ok === true → res.path === .orchestrator/eval/reports/<run_id>.html
  • Output path: .orchestrator/eval/reports/<run_id>.html (gitignored — a derived view, rebuildable from the journal).
  • writeEvalReport NEVER throws; on res.ok === false surface the WARN reason and continue (the journal record is unaffected — the report is derived).
  • Name the report path in the chat so the operator can open it.
  • When eval.report == none, skip this phase.

Phase 5: Chat Summary

Emit a compact, honest per-dimension summary. Status lines only — no global score.

## /eval — <session_id>  (self-evaluation, aiat-llm-eval/1.0 · rubric-v1 · n=1, no CI)

Deterministic:
  verification-evidence   PASS   <one-line evidence>
  plan-fidelity           PASS   completion_rate=1.0 (score)
  gate-health             PASS   <one-line evidence>
  process-safety          PASS   <one-line evidence + guard-emission disclosure>
  efficiency-kpis         N/A    (reported: duration=…s waves=… agents=… tok_in=… tok_out=… carryover=…)

Judge (advisory, uncalibrated)  [only when eval.judge != off]:
  instruction-adherence   <verdict>   advisory
  report-quality          <verdict>   advisory

cannot-determine: <k> of 5 deterministic dimensions (<reasons>)
Report:  .orchestrator/eval/reports/<run_id>.html
Journal: .orchestrator/metrics/eval.jsonl  (appended: <yes|--no-write>)
Re-verify: node scripts/eval-session.mjs --verify <run_id>

Always report the cannot-determine share explicitly — a high abstention count is an honest signal about missing telemetry, not a failure to hide. Always print the --verify command as the reproducibility handle.


Phase 6: Verification Mode (--verify <run-id>)

When Phase 1.2 detected --verify, run ONLY:

node scripts/eval-session.mjs --verify <run-id> --json
  • Exit 0 + { match: true } → the stored record re-scores identically across all deterministic dimensions. Report MATCH with the dimension count.
  • Exit 1 + { match: false, diffs } → scoring drift. Report the per-dimension diff (id.field: stored=… fresh=…). Drift means the source data or the engine changed since the record was written — investigate, do not overwrite.
  • --verify reproduces the stored model + timestamp verbatim (no env override), so a MATCH is a real reproducibility proof of the scoring, not of model output.

Cross-Platform (Codex CLI / Cursor / Pi) — FA4

The deterministic core is pure Node CLIs (scripts/eval-session.mjs) plus Node library modules (report.mjs, sink.mjs) — they run identically on every platform. Only the judge phase needs harness-specific tooling.

  • Codex CLI / Cursor / Pi: the Agent tool (and AskUserQuestion) are unavailable, so Phase 3 (judge) is SKIPPED with a one-line note ("judge phase skipped: requires the Agent tool, unavailable on <platform>"). Phases 2, 4, 5, 6 run unchanged — they are Node-only. See skills/_shared/platform-tools.md § Agent Dispatch Pattern.
  • harness.platform on the record is resolved from $SO_PLATFORM (falls back to claude-code) inside the engine — no skill action needed.
  • The deterministic five dimensions + the HTML report + --verify are fully available on all platforms; the judge overlay is a Claude-Code-only enrichment in v1.

Anti-Patterns

  • DO NOT derive, print, or imply a global/overall/aggregate score — the record forbids one by construction and so does every report.
  • DO NOT guess or "fill in" missing data — a missing gate result, KPI, or completion_rate is cannot-determine/null, never a fabricated pass or 0.
  • DO NOT present the judge's advisory verdict as a measurement — it is uncalibrated in v1 and must stay visibly separated from the deterministic tally.
  • DO NOT treat the HTML report as authoritative — the journal is the SSOT; the report is a rebuildable derived view.
  • DO NOT skip --verify when reproducibility is in question — it is the executable proof, and its MATCH/DRIFT exit code is the source of truth.
  • DO NOT pass --metrics-dir for a real run — that points the engine at fixture data instead of the live session metrics.
  • DO NOT call runReconcile-style writes from a subagent — the coordinator owns every eval.jsonl append (PSA-007).

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.