feat(ms-ai-architect): Spor D steg 2 — score-skill CLI (--json/--gate/--skill) (TDD)

Byggekloss for både SessionStart-surfacing og lifecycle-gate (D3).

- eval.mjs: ekstraher buildReport() (eksportert, testbar) ut av main() —
  samler hele korpus-rapporten (deterministisk + K10 + merget judge-cache).
- lib/skill-score.mjs: formatScoreReport() (ren) — sortert forbedringsrapport
  med score, status, floored/provisional/ujudget-tags og ⚑gulv-markering.
- score-skill.mjs (NY CLI): buildReport → scoreReport → render/json/gate.
  --skill scorer hele korpuset (K10 trenger alle søsken) men rapporterer/gater
  kun den valgte → inkrementell enkelt-skill-scoring for D3 lifecycle-gate.
- docs/development.md: ny «Skill-kvalitetsscore (Spor D)»-seksjon.

Live baseline: advisor 91, governance/security 96 (OK); engineering +
infrastructure 89 (floored av K10-gulv) UNDER mål. Gate exit=1.

Tester: kb-eval 134→142 (+8). validate 239, kb-update 316 uendret grønt.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
This commit is contained in:
Kjell Tore Guttormsen 2026-06-23 17:16:44 +02:00
commit c1a09062d4
5 changed files with 249 additions and 7 deletions

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@ -93,6 +93,21 @@ Et parallelt, uavhengig spor fra sitemap-discoveren: oppdage at Microsoft har pu
Slug→skill-mapping er config i `domain-taxonomy.json` (`course_products`), ikke hardkoding. `last_full_enum`-kadens (≥30 d) styrer når `removed` beregnes (kun full-enumerering — aldri inkrementelt).
### Skill-kvalitetsscore (Spor D — objektiv 0100-score per skill)
Måler skill-kvalitet deterministisk mot Anthropics «Skill authoring best practices». Rubrikken K1K10 (`eval.mjs`) + de fem ekstra deterministiske sjekkene N1N5 aggregeres til én 0100-score per skill via **vektet delpoeng med hardt gulv** på de bærende kriteriene (K1 trigger-presisjon, K10 søsken-overlapp): feiler ett gulv-kriterium kappes scoren under målet (89), uansett øvrig form. Mål: **alle 5 skills ≥90 %**. Full spec: [`skill-quality-scoring-plan.md`](skill-quality-scoring-plan.md).
```bash
node scripts/kb-eval/score-skill.mjs # human-rapport: score + sortert forbedringsliste per skill
node scripts/kb-eval/score-skill.mjs --json # maskin-output (scoreReport: target/scored/below)
node scripts/kb-eval/score-skill.mjs --gate 90 # non-zero exit hvis noen skill < 90
node scripts/kb-eval/score-skill.mjs --skill ms-ai-advisor # scope til én skill (inkrementelt)
```
Arkitektur: `eval.mjs buildReport()` (disk: deterministisk + K10 + merget operatør-gated judge-cache) → `lib/skill-score.mjs` (REN: `scoreSkill`/`scoreReport`/`formatScoreReport`, ingen disk). N1 name-validitet · N2 description ≤1024 · N3 refs én nivå dypt · N4 TOC i ref-filer >100 linjer · N5 forward-slash-stier. Judge-kriterier (K1/K4/K7/K8/K9) degraderer pent: mangler judge → ekskluderes fra teller+nevner, scoren merkes `provisional` (K1-gulv kan ikke håndheves), K10-gulvet (deterministisk) gjelder alltid.
**Korpus-invariant (roadmap):** Hele korpuset skal holde ≥90 % til enhver tid. Ved skill-endring (create/update/merge/split via `apply-skill-op.mjs`) re-scores **kun** den endrede skillen inkrementelt (men hele korpuset evalueres siden K10 trenger alle søsken-descriptions), og `--gate 90` håndhever terskelen via operatør-gate.
### E2E-regresjonstester
```bash
# Kjør alle E2E-suiter

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@ -334,11 +334,12 @@ export function attachSiblingOverlap(skills, promptSet, { threshold = K10_OVERLA
return skills;
}
function main() {
const args = process.argv.slice(2);
const jsonOut = args.includes('--json');
const doWrite = args.includes('--write');
/**
* Assemble the full corpus report: per-skill deterministic eval (incl. N1-N5) +
* cross-skill K10 sibling-overlap + merged operator-gated judge cache. This is
* the object the score-skill CLI consumes via scoreReport(). Reads disk.
*/
export function buildReport() {
const skillNames = readdirSync(SKILLS_DIR, { withFileTypes: true })
.filter((e) => e.isDirectory() && existsSync(join(SKILLS_DIR, e.name, 'SKILL.md')))
.map((e) => e.name)
@ -360,11 +361,20 @@ function main() {
for (const s of skills) if (jr[s.name]) s.judge = jr[s.name];
}
const report = {
return {
rubric: 'K1-K10',
note: 'Deterministic: K2,K3,K5,K6,refCountConsistency,K10(siblingScopeOverlap). LLM-judge (operator-gated): K1,K4,K7,K8,K9.',
note: 'Deterministic: K2,K3,K5,K6,refCountConsistency,K10(siblingScopeOverlap),N1-N5. LLM-judge (operator-gated): K1,K4,K7,K8,K9.',
skills,
};
}
function main() {
const args = process.argv.slice(2);
const jsonOut = args.includes('--json');
const doWrite = args.includes('--write');
const report = buildReport();
const skills = report.skills;
if (doWrite) {
mkdirSync(OUT_DIR, { recursive: true });

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@ -249,3 +249,35 @@ export function scoreReport(report, opts = {}) {
const below = scored.filter((s) => !s.meetsTarget);
return { target, scored, below };
}
/**
* Render a human-readable quality report (pure). Each skill shows its score and
* status; below-target skills list their sorted improvements (biggest weighted
* loss first). Returns a multi-line string.
* @param {{target: number, scored: object[]}} result scoreReport() output
*/
export function formatScoreReport(result) {
const target = result?.target ?? TARGET;
const scored = result?.scored || [];
const below = scored.filter((s) => !s.meetsTarget);
const lines = [];
lines.push(`Skill-kvalitet — ${scored.length} skills, mål ≥${target} % (${below.length} under mål)`);
lines.push('');
for (const s of scored) {
const tags = [];
if (s.floored) tags.push('floored');
if (s.provisional) tags.push('provisional');
if (!s.judged) tags.push('ujudget');
const status = s.meetsTarget ? 'OK' : 'UNDER MÅL';
const tagStr = tags.length ? ` [${tags.join(', ')}]` : '';
lines.push(`${s.name} ${s.score}/100 ${status}${tagStr}`);
if (!s.meetsTarget) {
for (const imp of s.improvements) {
const floor = imp.floor ? ' ⚑gulv' : '';
lines.push(`${imp.key} ${imp.label}${floor} (${imp.detail}) [-${imp.pointsLost.toFixed(2)}] → ${imp.fix}`);
}
}
lines.push('');
}
return lines.join('\n');
}

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@ -0,0 +1,72 @@
#!/usr/bin/env node
// score-skill.mjs — Skill-quality score CLI (Spor D, step 2).
//
// Runs the eval pipeline (buildReport: deterministic K2/K3/K5/K6/refCount/N1-N5
// + cross-skill K10 + merged operator-gated judge cache), scores every skill via
// the PURE lib (scoreSkill/scoreReport), and reports a 0-100 quality score with
// a sorted improvement list. The corpus invariant is: every skill stays >=90 %.
//
// Usage:
// node scripts/kb-eval/score-skill.mjs # human summary
// node scripts/kb-eval/score-skill.mjs --json # machine output (scoreReport)
// node scripts/kb-eval/score-skill.mjs --gate 90 # non-zero exit if any skill < 90
// node scripts/kb-eval/score-skill.mjs --skill <name> # scope output to one skill
// # (still scores the full corpus
// # so K10 sibling-overlap is correct)
//
// K10 requires every sibling description, so even single-skill (incremental)
// scoring evaluates the whole corpus and then filters the reported set — this is
// the building block for the lifecycle-gate in apply-skill-op.mjs.
//
// Zero dependencies. Pure scoring lives in lib/skill-score.mjs.
import { fileURLToPath } from 'node:url';
import { buildReport } from './eval.mjs';
import { scoreReport, formatScoreReport, TARGET } from './lib/skill-score.mjs';
function argValue(args, flag) {
const i = args.indexOf(flag);
return i !== -1 && i + 1 < args.length ? args[i + 1] : null;
}
function main() {
const args = process.argv.slice(2);
const jsonOut = args.includes('--json');
const gateRaw = argValue(args, '--gate');
const gate = gateRaw !== null ? Number(gateRaw) : null;
const skillFilter = argValue(args, '--skill');
const target = Number.isFinite(gate) ? gate : TARGET;
const full = scoreReport(buildReport(), { target });
// Scope the reported/gated set to one skill if requested (scoring already ran
// over the whole corpus, so K10 is computed correctly).
let scored = full.scored;
if (skillFilter) {
scored = scored.filter((s) => s.name === skillFilter);
if (scored.length === 0) {
process.stderr.write(`score-skill: ukjent skill '${skillFilter}'. Tilgjengelig: ${full.scored.map((s) => s.name).join(', ')}\n`);
process.exitCode = 2;
return;
}
}
const below = scored.filter((s) => !s.meetsTarget);
const result = { target, scored, below };
if (jsonOut) {
process.stdout.write(JSON.stringify(result) + '\n');
} else {
process.stdout.write(formatScoreReport(result) + '\n');
if (gate !== null) {
process.stdout.write(below.length === 0
? `✓ Gate ≥${target}: alle ${scored.length} skills består.\n`
: `✗ Gate ≥${target}: ${below.length} skill(s) under mål — ${below.map((s) => s.name).join(', ')}.\n`);
}
}
if (gate !== null && below.length > 0) process.exitCode = 1;
}
if (process.argv[1] && fileURLToPath(import.meta.url) === process.argv[1]) {
main();
}

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@ -0,0 +1,113 @@
// tests/kb-eval/test-score-skill.test.mjs
// Tests for the score-skill CLI building blocks (Spor D, step 2):
// - eval.mjs buildReport() assembles the full corpus report (deterministic +
// K10 sibling-overlap + merged judge cache).
// - lib/skill-score.mjs formatScoreReport() renders the sorted improvement
// report (pure).
// - the score-skill.mjs CLI: --json emits the scoreReport, --gate sets a
// non-zero exit when any skill is below target, --skill scopes the output.
import { test } from 'node:test';
import assert from 'node:assert/strict';
import { execFileSync } from 'node:child_process';
import { fileURLToPath } from 'node:url';
import { dirname, join } from 'node:path';
import { buildReport } from '../../scripts/kb-eval/eval.mjs';
import { scoreReport, formatScoreReport } from '../../scripts/kb-eval/lib/skill-score.mjs';
const __dirname = dirname(fileURLToPath(import.meta.url));
const CLI = join(__dirname, '..', '..', 'scripts', 'kb-eval', 'score-skill.mjs');
test('buildReport — assembles the full corpus with N1-N5 on every skill', () => {
const report = buildReport();
assert.ok(Array.isArray(report.skills) && report.skills.length === 5, `got ${report.skills?.length} skills`);
for (const s of report.skills) {
const d = s.deterministic;
assert.ok(d.N1_nameValidity && d.N4_refToc, `${s.name} missing N1/N4`);
assert.ok(d.K10_siblingScopeOverlap, `${s.name} missing K10 (sibling overlap not attached)`);
}
});
test('scoreReport — over the real corpus returns a score per skill and a below-target set', () => {
const result = scoreReport(buildReport());
assert.equal(result.target, 90);
assert.equal(result.scored.length, 5);
for (const s of result.scored) {
assert.ok(Number.isFinite(s.score), `${s.name} score not finite`);
assert.equal(typeof s.meetsTarget, 'boolean');
}
// below = subset that does not meet the target
assert.ok(result.below.every((s) => !s.meetsTarget));
});
test('scoreReport — a synthetic below-target skill lands in below[]', () => {
const synthetic = {
skills: [
// one perfect-ish, one with a failing K10 floor (capped below 90)
{
name: 'good', deterministic: {
K2_descriptionFormat: { pass: true }, K3_bodyLength: { bodyLines: 100, pass: true },
K5_progressiveDisclosure: { namedRatio: 0.5, pass: true }, K6_routingTable: { pass: true },
refCountConsistency: { consistent: true }, K10_siblingScopeOverlap: { maxCombined: 1, pass: true, threshold: 7 },
N1_nameValidity: { pass: true }, N2_descriptionLength: { pass: true },
N3_refNestingDepth: { pass: true }, N4_refToc: { ratio: 1, pass: true, withToc: 1, largeFiles: 1 },
N5_forwardSlashPaths: { pass: true },
}, judge: null,
},
{
name: 'bad', deterministic: {
K2_descriptionFormat: { pass: true }, K3_bodyLength: { bodyLines: 100, pass: true },
K5_progressiveDisclosure: { namedRatio: 0.5, pass: true }, K6_routingTable: { pass: true },
refCountConsistency: { consistent: true }, K10_siblingScopeOverlap: { maxCombined: 9, pass: false, threshold: 7, worstSibling: 'good' },
N1_nameValidity: { pass: true }, N2_descriptionLength: { pass: true },
N3_refNestingDepth: { pass: true }, N4_refToc: { ratio: 1, pass: true, withToc: 1, largeFiles: 1 },
N5_forwardSlashPaths: { pass: true },
}, judge: null,
},
],
};
const result = scoreReport(synthetic);
assert.equal(result.below.length, 1);
assert.equal(result.below[0].name, 'bad');
});
test('formatScoreReport — renders skill names, the target, and improvement fixes', () => {
const result = scoreReport(buildReport());
const text = formatScoreReport(result);
assert.match(text, /ms-ai-advisor/);
assert.match(text, /90/); // the target appears
// at least one improvement fix line is rendered for a below-target skill
if (result.below.length > 0) {
assert.ok(/↳|→/.test(text), 'expected improvement bullets in the report');
}
});
test('CLI --json — emits a parseable scoreReport with five scored skills (exit 0)', () => {
const out = execFileSync('node', [CLI, '--json'], { encoding: 'utf8' });
const parsed = JSON.parse(out);
assert.equal(parsed.scored.length, 5);
assert.equal(parsed.target, 90);
});
test('CLI --skill — scopes the output to a single skill', () => {
const out = execFileSync('node', [CLI, '--skill', 'ms-ai-advisor', '--json'], { encoding: 'utf8' });
const parsed = JSON.parse(out);
assert.equal(parsed.scored.length, 1);
assert.equal(parsed.scored[0].name, 'ms-ai-advisor');
});
test('CLI --gate — non-zero exit path: an unreachable target fails the gate (corpus-independent)', () => {
let code = 0;
try {
execFileSync('node', [CLI, '--gate', '101'], { encoding: 'utf8', stdio: 'pipe' });
} catch (e) {
code = e.status;
}
assert.equal(code, 1, 'no skill can score 101 -> gate must fail');
});
test('CLI --gate — zero exit path: a target of 0 passes the gate (corpus-independent)', () => {
// exits 0; execFileSync throws only on non-zero, so reaching here is the pass
execFileSync('node', [CLI, '--gate', '0'], { encoding: 'utf8', stdio: 'pipe' });
assert.ok(true);
});