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Standardized cost-estimation framework for great_cto plans. Forces explicit LLM cost, infra cost, human-supervision time, and the (defensible) human-equivalent comparison. Output format is parsable by the board's /api/cost path — must follow exactly.
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npx skills add https://github.com/TuYv/ccpm --skill cost-modelコマンドは1行のまま表示されます。コピー前に横へスクロールして全体を確認してください。
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Use when auditing a paid ad account for incremental contribution, wasted spend, or measurement integrity before scaling; runs a typed 20-item ROAS profile with verified vetoes and a SHIP/FIX/BLOCK/UNDECIDED gate on own exported data. Not for campaign structure design — use campaign-architect; not for creative production — use ad-creative-builder. 付费广告账户审计/ROAS评分
Use when the user asks to "write ad copy", "generate RSA headlines", or "build ad creative at volume"; produces ad units — RSA headlines/descriptions, hooks, and an angle matrix — message-matched to the destination landing page. Not for scoring an ad account — use ad-account-auditor; not for the post-click page — use landing-optimizer; not for organic articles — use content-writer. 广告创意/广告文案/RSA标题
Use when the user asks to "design an A/B test", "set up a creative/landing test", "run an incrementality test", or "is this result statistically and practically material?"; produces a hypothesis, variant matrix, sample-size/duration/power plan, and a documented effect/uncertainty read from own exported results. It applies only a precommitted owner-approved action rule; the statistical helper never chooses a business action. Not for producing variants — use ad-creative-builder; not for reading back one shipped change — use paid-measurement-loop. 广告AB测试设计/实验设计/显著性判定/增效测试
SOC 職業分類に基づく
SKILL.md を表示中
| name | cost-model |
| description | Standardized cost-estimation framework for great_cto plans. Forces explicit LLM cost, infra cost, human-supervision time, and the (defensible) human-equivalent comparison. Output format is parsable by the board's /api/cost path — must follow exactly. |
| when_to_use | Apply when: - pm is writing PLAN-*.md and the Cost section is required - architect is forecasting LLM burn for a new feature (gate:cost for AI archetypes) - any report claims a savings ratio — must show methodology |
| effort | low |
| allowed-tools | Read, Write |
| paths | ["docs/plans/**","docs/architecture/**"] |
great_cto reports cost numbers on the board. Those numbers MUST be auditable, because a wrong "7,638×" claim killed credibility (see docs/blog/cost-dashboard-rebuild.md). This skill defines the format.
Every PLAN-.md and ARCH-.md cost section follows this exact template:
## Cost estimate
**LLM**: $<low>–<high> (<N> calls × $<per-call avg>)
**Human equiv**: $<low>–<high> (<hours> × $<rate>/h)
**Infra delta**: $<low>–<high>/month
**Time to ship**: <hours> agent-time, <hours> wall-clock
> Methodology: <one-sentence rationale for each range>
The board's getCostHistory() parser anchors on line-start "LLM" and
"Human" labels. Mid-line references are ignored to prevent the
$240-trap regression. Stick to the template.
For each agent in the pipeline, estimate:
Quick reference for Sonnet 4 ($3/M in, $15/M out):
| Agent | Typical prompt | Typical output | Per-call cost |
|---|---|---|---|
| architect | 14k | 1.5k | ~$0.06 |
| pm | 6k | 0.6k | ~$0.03 |
| senior-dev | 8k | 0.8k | ~$0.04 |
| qa-engineer | 11k | 0.5k | ~$0.04 |
| reviewer (avg) | 8-12k | 0.6k | ~$0.04 |
| security-officer | 12k | 1k | ~$0.05 |
| devops | 9k | 0.8k | ~$0.04 |
For Haiku ($0.80/M / $4/M), divide by ~4. For Opus 4 ($15/M / $75/M), multiply by ~5.
Sum across the pipeline stages that actually fire (use gatesFor() and
reviewersFor() from archetypes.ts to know the count).
The human cost to do the SAME work without agents. This is the "if I hired a senior engineer, how long would this task take, at what rate?"
Estimate hours conservatively. A "small feature" the LLM does in 15 minutes might take a human 2-4 hours (it's never just the typing).
Only count what's NEW. If the feature adds a Redis instance, count Redis. If it adds 10MB/month of S3 storage, that's noise — don't list.
Two numbers — both useful:
Before committing the section to the plan, verify:
ratio = human_equiv / llm_cost
If ratio > 1000, something is wrong. Common bugs:
| Bug | How to detect | Fix |
|---|---|---|
| Wrong unit ($ vs ¢) | LLM cost ends in /M tokens not $ | Convert: tokens / 1M × price |
| Counting savings not spend | "Human time saved" not "Human cost" | Use cost of doing it, not value of skipping |
| Mid-line label pollution | Plan has "$X LLM | $Y human" on one line |
| Forecast vs actual mixed | LLM forecast counts toward total_llm | Separate forecast section if needed |
For AI archetypes (mlops, ai-system, agent-product), the pipeline
opens gate:cost after architect's forecast. CTO must approve the
projected monthly burn before senior-dev starts.
Use the GATE template:
## Gate:cost forecast
| Production volume | Monthly LLM cost |
|---|---|
| 1K req/day | $X |
| 10K req/day | $Y |
| 100K req/day | $Z |
Recommended monthly cap: $<cap>
Triggers above cap: <what alerts fire, who gets paged>
❌ Round-number theatre. "$0.50 LLM | $7,500 human" — looks suspicious. Use realistic ranges: "$0.50–1.20 | $225–360".
❌ Single point estimates. Always provide a range. Single numbers hide uncertainty.
❌ No methodology line. Just numbers without rationale is unverifiable.
❌ Hand-waved infra. "Some hosting cost" is not a number. Either give $, or say "infra: no change."
## Cost estimate
**LLM**: $0.75–1.85 (3 tasks × $0.25–0.62 per Sonnet call)
**Human equiv**: $225–300 (1.5–2h × $150/h, mid-market senior)
**Infra delta**: $0/month (uses existing Express + Postgres)
**Time to ship**: ~15min agent-time, ~3h wall-clock (1 human gate)
> Methodology: tasks sized by line-count estimate; per-call cost from
> historical Sonnet 4 averages on this archetype's plans.
Ratio = 300/1.85 = 162×. Plausible. Defensible.