Coding & Development๐คclaude๐universal
cost-model
skills/cost-model/SKILL.md
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 โ must follow exactly.
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npx skills add https://github.com/avelikiy/great_cto/tree/main/skills/cost-model--- 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 โ 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 โ must show methodology effort: low allowed-tools: Read, Write paths: - "docs/plans/**" - "docs/architecture/**" --- # Cost model โ make cost claims defensible great_cto reports cost numbers on the board. Those numbers MUST be auditable, because a wrong "7,638ร" claim killed credibility (see docs/blog/cost-dashboard-rebuild.md). This skill defines the format. ## The 4-line cost section Every PLAN-*.md and ARCH-*.md cost section follows this exact template: ```markdown ## Cost estimate **LLM**: $<low>โ<high> (<N> calls ร $<per-call avg>) **Human equiv**: $<low>โ<high> (<hours> ร $<rate>/h) **Infra delta**: $<low>โ<high>/month **Time to ship**: <hours> agent-time, <hours> wall-clock > Methodology: <one-sentence rationale for each range> ``` ### Why this exact format? 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. ## How to estimate each line ### LLM cost For each agent in the pipeline, estimate: - **Prompt tokens** = (system prompt size) + (context the agent receives) - **Completion tokens** = (typical output for that agent type) 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). ### Human equiv 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?" - Senior engineer: $120-180/hour (mid-market US/EU) - Staff engineer / specialist: $200-300/hour - Domain expert (security, compliance): $250-400/hour Estimate hours conservatively. A "small feature" the LLM does in 15 minutes might take a human 2-4 hours (it's never just the typing). ### Infra delta Only count what's NEW. If the feature adds a Redis instance, count Redis. If it adds 10MB/month of S3 storage, that's noise โ don't list. ### Time to ship Two numbers โ both useful: - **Agent-time**: wall-clock of LLM calls (typically 5-30 min) - **Wall-clock**: actual elapsed including human gates (typically hours to days) ## Sanity check before writing Before committing the section to the plan, verify: ``` ratio = human_equiv / llm_cost ``` If `ratio > 1000`, something is wrong. Common bugs: | Bug | How to detect | Fix | |---|---|---| | Wrong unit ($ vs ยข) | LLM cost ends in /M tokens not $ | Convert: tokens / 1M ร 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 | Use multi-line format from template | | Forecast vs actual mixed | LLM forecast counts toward total_llm | Separate forecast section if needed | ## Cost gates 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: ```markdown ## 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> ``` ## Anti-patterns โ **Round-number theatre.** "$0.50 LLM | $7,500 human" โ looks suspicious. Use realistic ranges: "$0.50โ1.20 | $225โ360". โ **Single point estimates.** Always provide a range. Single numbers hide uncertainty. โ **No methodology line.** Just numbers without rationale is unverifiable. โ **Hand-waved infra.** "Some hosting cost" is not a number. Either give $, or say "infra: no change." ## Example โ good ```markdown ## Cost estimate **LLM**: $0.75โ1.85 (3 tasks ร $0.25โ0.62 per Sonnet call) **Human equiv**: $225โ300 (1.5โ2h ร $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 = **162ร**. Plausible. Defensible.
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