Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add avelikiy/great_cto --skill cost-modelgit clone --depth 1 https://github.com/avelikiy/great_ctoWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/avelikiy/great_cto/cost-model)<a href="https://agentmods.dev/skills/avelikiy/great_cto/cost-model"><img src="https://agentmods.dev/badge/skills/avelikiy/great_cto/cost-model/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/avelikiy/great_cto/cost-model"><img src="https://agentmods.dev/badge/skills/avelikiy/great_cto/cost-model.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00059 | $0.01467 |
| Opus 5 | $0.00030 | $0.00733 |
| Sonnet 5 | $0.00012 | $0.00293 |
| Haiku 4.5 | $0.00006 | $0.00147 |
Grade A, and why
cost-model scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 159 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cost model — make cost claims defensible
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.
The 4-line cost section
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>
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).
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 159 lines · 59 tokens per session scan A e08f05349aa0
cost-model is a skill published in the GitHub repository avelikiy/great_cto (92 stars, last pushed today), licensed MIT. It adds 59 tokens to every session and 1,467 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
spec-drift
Standalone plan-vs-code audit on any branch: runs /ship Step 8's plan-completion section from disk (hash-pinned) against an explicit plan and base. Report, JSON, exit code. Never edits code.
third-lens-review
After Claude self-pitfall + Codex on a ship-worthy/architecture/RT/security/contract change: run a third external model house (distant training distribution → different blind spots) on the patched artifact, then adversarial synthesis.
quality-review
After a PRD, spec, or plan, before implementation: hunt perceived-quality pitfalls (silent failures, missing loading/empty states, error recovery, state drift) that make a product feel cheap. Complements pitfall-verification.
boundaries
Analyze Phoenix context boundaries and module coupling via mix xref. Use when checking cross-context calls, validating dependencies, before splitting modules, or reviewing architecture.
triage
Triage review findings interactively — approve, skip, or prioritize each issue. Use after /phx:review to filter findings before fixing.
review-code
Review a change along one specific quality dimension — bugs, design, simplicity, maintainability, testability, test quality, type safety, contracts, operational readiness, docs, prose value, change intent, defect-class completeness after a fix, or context-file adherence. Loads exactly one dimension reference and…