feat(PBI-67): model + mode-selectie per ClaudeJob-kind (#169)
* feat(PBI-67/ST-1297): datamodel-velden voor job-model-selectie
Voegt 8 nieuwe optionele velden toe verspreid over Product, Task en
ClaudeJob ten dienste van de override-cascade:
task.requires_opus → job.requested_* → product.preferred_* → kind-default
Bestaande rijen krijgen NULL (Product/ClaudeJob) of false (Task) en
vallen daarmee terug op de kind-defaults uit de resolver (ST-1298).
Migration is additief: alleen ALTER TABLE ADD COLUMN, geen RENAME of
DROP. Bestaande factories en seed-script blijven werken zonder
aanpassing omdat alle nieuwe velden default-waardes hebben.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* feat(PBI-67/ST-1299): job-config snapshot bij enqueue + worker-flag-runbook
T-789: Snapshot van resolved JobConfig in ClaudeJob.requested_*
bij elke job-creatie. Helper in lib/job-config-snapshot.ts laadt
product (preferred_*) en task (requires_opus) en draait de resolver
uit lib/job-config.ts (mirror van scrum4me-mcp/src/lib/job-config.ts —
zelfde matrix, sync-comment in bestand). Toegepast op alle 5
enqueue-locaties:
- actions/user-questions.ts (PLAN_CHAT)
- actions/sprint-runs.ts × 3 (SPRINT_IMPLEMENTATION x2,
TASK_IMPLEMENTATION loop)
- actions/ideas.ts (IDEA_GRILL / IDEA_MAKE_PLAN)
Test-mocks uitgebreid met product.findUnique en task.findUnique zodat
de helper bij unit tests veilig terugvalt op kind-defaults (alle 563
tests groen).
T-790: Sectie 'Config doorgeven aan Claude Code' toegevoegd aan
docs/runbooks/worker-idempotency.md met CLI-flag-mapping en de
verwachte aanroep per kind. Forward-link naar
docs/runbooks/job-model-selection.md (volgt in T-794).
Plus: docs/plans/job-model-selection.md (de approved plan-doc).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* feat(PBI-67/ST-1300): cost-attribution voor thinking-tokens + admin UI
T-792: token-stats + token-history rekenen actual_thinking_tokens nu
mee in de totale kosten (tegen input-rate, conform Anthropic billing).
COALESCE-veilig zodat oude rijen 0 bijdragen i.p.v. NaN. Nieuwe export
`getTokenStatsByKind` aggregeert tokens en kosten per ClaudeJob.kind
zodat we relatieve uitgaven van IDEA_GRILL/IDEA_MAKE_PLAN/PLAN_CHAT/
TASK_IMPLEMENTATION/SPRINT_IMPLEMENTATION kunnen zien.
T-793: admin/jobs Kosten-tabel toont:
- Nieuwe kolom 'Thinking' (aantal verbruikte thinking-tokens)
- Mismatch-marker (rood) als requested_model afwijkt van actuele
model_id — duidt op een worker die de CLI-flag niet doorgaf.
Tooltip toont aangevraagd model. Geen Sentry/log-noise.
Page-level cost-berekening volgt dezelfde formule (input_price ×
thinking_tokens). 563 tests groen.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* docs(PBI-67/ST-1301): runbook + CLAUDE.md updates voor model/mode-selectie
T-794: Nieuwe runbook docs/runbooks/job-model-selection.md met
override-cascade, kind-default-matrix, override-voorbeelden,
auditspoor en cost-attribution-formule. 107 regels.
T-795: CLAUDE.md hardstop-bullet voor 'Model/mode per ClaudeJob'
(verwijst naar nieuwe runbook) + patterns-quickref-rij voor
job-config resolver. CLAUDE.md blijft 139 regels (≤ 150).
T-796: docs:check-links groen — 108 files, geen broken links. Twee
externe-repo verwijzingen (scrum4me-mcp/...) ge-de-linked tot plain
text omdat de check-links script de zustertree niet traverseert; de
referenties blijven leesbaar.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
Janpeter Visser
GitHub
parent
f233dd815e
commit
8c63ba377d
18 changed files with 648 additions and 9 deletions
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@ -16,10 +16,18 @@ export interface TokenJobRow {
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outputTokens: number | null
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cacheReadTokens: number | null
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cacheWriteTokens: number | null
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thinkingTokens: number | null
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costUsd: number | null
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durationSeconds: number | null
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}
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export interface TokenStatsByKindRow {
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kind: string
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jobCount: number
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totalTokens: number
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totalCostUsd: number
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}
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export interface TokenStatsResult {
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kpi: TokenKpi
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jobs: TokenJobRow[]
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@ -41,10 +49,18 @@ type RawJobRow = {
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output_tokens: number | null
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cache_read_tokens: number | null
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cache_write_tokens: number | null
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actual_thinking_tokens: number | null
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cost_usd: number | null
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duration_seconds: number | null
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}
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type RawByKindRow = {
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kind: string
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job_count: bigint
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total_tokens: bigint
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total_cost: number | null
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}
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const EMPTY_KPI: TokenKpi = { totalTokens: 0, totalCostUsd: 0, avgCostPerJob: 0, jobCount: 0 }
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export async function getTokenStats(userId: string, sprintId: string): Promise<TokenStatsResult> {
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@ -53,18 +69,20 @@ export async function getTokenStats(userId: string, sprintId: string): Promise<T
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const [kpiRows, jobRows] = await Promise.all([
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prisma.$queryRaw<RawKpiRow[]>`
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SELECT
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COALESCE(SUM(cj.input_tokens + cj.output_tokens + cj.cache_read_tokens + cj.cache_write_tokens), 0) AS total_tokens,
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COALESCE(SUM(cj.input_tokens + cj.output_tokens + cj.cache_read_tokens + cj.cache_write_tokens + COALESCE(cj.actual_thinking_tokens, 0)), 0) AS total_tokens,
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SUM(
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cj.input_tokens * mp.input_price_per_1m / 1000000.0
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+ cj.output_tokens * mp.output_price_per_1m / 1000000.0
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+ cj.cache_read_tokens * mp.cache_read_price_per_1m / 1000000.0
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+ cj.cache_write_tokens * mp.cache_write_price_per_1m / 1000000.0
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+ COALESCE(cj.actual_thinking_tokens, 0) * mp.input_price_per_1m / 1000000.0
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) FILTER (WHERE cj.input_tokens IS NOT NULL) AS total_cost,
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AVG(
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cj.input_tokens * mp.input_price_per_1m / 1000000.0
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+ cj.output_tokens * mp.output_price_per_1m / 1000000.0
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+ cj.cache_read_tokens * mp.cache_read_price_per_1m / 1000000.0
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+ cj.cache_write_tokens * mp.cache_write_price_per_1m / 1000000.0
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+ COALESCE(cj.actual_thinking_tokens, 0) * mp.input_price_per_1m / 1000000.0
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) FILTER (WHERE cj.input_tokens IS NOT NULL) AS avg_cost,
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COUNT(*) FILTER (WHERE cj.input_tokens IS NOT NULL) AS job_count
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FROM claude_jobs cj
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@ -85,11 +103,13 @@ export async function getTokenStats(userId: string, sprintId: string): Promise<T
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cj.output_tokens,
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cj.cache_read_tokens,
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cj.cache_write_tokens,
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cj.actual_thinking_tokens,
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CASE WHEN cj.input_tokens IS NOT NULL THEN
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cj.input_tokens * mp.input_price_per_1m / 1000000.0
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+ cj.output_tokens * mp.output_price_per_1m / 1000000.0
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+ cj.cache_read_tokens * mp.cache_read_price_per_1m / 1000000.0
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+ cj.cache_write_tokens * mp.cache_write_price_per_1m / 1000000.0
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+ COALESCE(cj.actual_thinking_tokens, 0) * mp.input_price_per_1m / 1000000.0
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END AS cost_usd,
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EXTRACT(EPOCH FROM (cj.finished_at - cj.claimed_at)) AS duration_seconds
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FROM claude_jobs cj
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@ -122,8 +142,54 @@ export async function getTokenStats(userId: string, sprintId: string): Promise<T
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outputTokens: r.output_tokens,
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cacheReadTokens: r.cache_read_tokens,
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cacheWriteTokens: r.cache_write_tokens,
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thinkingTokens: r.actual_thinking_tokens,
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costUsd: r.cost_usd != null ? Number(r.cost_usd) : null,
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durationSeconds: r.duration_seconds != null ? Number(r.duration_seconds) : null,
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})),
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}
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}
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// PBI-67: per-kind aggregatie. Toont totaal tokens + kosten per ClaudeJob.kind
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// binnen één sprint zodat we de relatieve uitgaven van IDEA_GRILL vs
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// TASK_IMPLEMENTATION etc. kunnen zien. Voor jobs zonder sprint-koppeling
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// (idea-jobs) blijven we filteren op user_id + sprint_id; idea-jobs zonder
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// task vallen buiten deze view.
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export async function getTokenStatsByKind(
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userId: string,
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sprintId: string,
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): Promise<TokenStatsByKindRow[]> {
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if (!sprintId) return []
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const rows = await prisma.$queryRaw<RawByKindRow[]>`
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SELECT
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cj.kind::text AS kind,
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COUNT(*) FILTER (WHERE cj.input_tokens IS NOT NULL) AS job_count,
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COALESCE(SUM(
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cj.input_tokens + cj.output_tokens + cj.cache_read_tokens + cj.cache_write_tokens
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+ COALESCE(cj.actual_thinking_tokens, 0)
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), 0) AS total_tokens,
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SUM(
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cj.input_tokens * mp.input_price_per_1m / 1000000.0
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+ cj.output_tokens * mp.output_price_per_1m / 1000000.0
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+ cj.cache_read_tokens * mp.cache_read_price_per_1m / 1000000.0
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+ cj.cache_write_tokens * mp.cache_write_price_per_1m / 1000000.0
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+ COALESCE(cj.actual_thinking_tokens, 0) * mp.input_price_per_1m / 1000000.0
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) FILTER (WHERE cj.input_tokens IS NOT NULL) AS total_cost
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FROM claude_jobs cj
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JOIN tasks t ON cj.task_id = t.id
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JOIN stories s ON t.story_id = s.id
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LEFT JOIN model_prices mp ON mp.model_id = cj.model_id
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WHERE cj.user_id = ${userId}
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AND s.sprint_id = ${sprintId}
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AND cj.status = 'DONE'
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GROUP BY cj.kind
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ORDER BY total_cost DESC NULLS LAST
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`
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return rows.map((r) => ({
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kind: r.kind,
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jobCount: Number(r.job_count),
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totalTokens: Number(r.total_tokens),
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totalCostUsd: Number(r.total_cost ?? 0),
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}))
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}
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