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 zeuikli/claude-pilot-suite --skill sonnet-pilotgit clone --depth 1 https://github.com/zeuikli/claude-pilot-suiteWrote 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/zeuikli/claude-pilot-suite/sonnet-pilot)<a href="https://agentmods.dev/skills/zeuikli/claude-pilot-suite/sonnet-pilot"><img src="https://agentmods.dev/badge/skills/zeuikli/claude-pilot-suite/sonnet-pilot/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/zeuikli/claude-pilot-suite/sonnet-pilot"><img src="https://agentmods.dev/badge/skills/zeuikli/claude-pilot-suite/sonnet-pilot.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00143 | $0.04298 |
| Opus 5 | $0.00072 | $0.02149 |
| Sonnet 5 | $0.00029 | $0.00860 |
| Haiku 4.5 | $0.00014 | $0.00430 |
Grade A, and why
sonnet-pilot 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 10d 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 — 300 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sonnet Pilot — Quality-First Execution Playbook
Thesis
Deep context engineering + precise delegation = quality floor protection + predictable escalation.
Augment Code eval (2026-04): Best-quality AGENTS.md provides performance gain equivalent to one model tier (Haiku→Sonnet or Sonnet→Opus effective). Bad documentation is worse than no documentation, by ~30%. AgentOpt (arxiv 2604.06296): On HotpotQA, strongest planner alone (Opus full stack) = 31.71%; weak planner + strong solver (layered delegation) = 74.27%. Individual model capability does NOT predict ensemble performance.
What this SKILL actually does (empirically validated, A/B/C benchmark, n=5 wiki tasks, Opus 4.7 graded):
- Sonnet + SKILL = 283/300; Sonnet Plain = 283/300; Opus = 286/300
- SKILL net gain on routine extraction = 0: on structured wiki tasks, Sonnet already performs near-Opus without this playbook
- SKILL value = floor protection on hard tasks: complex tasks with ambiguous requirements, multi-step agentic, cross-module design — where Sonnet without structure tends to miss assumptions, skip self-review, or produce over-engineered output
→ Think of this SKILL as insurance: no observable premium on easy days; prevents 10–30% quality loss on hard days. → If your tasks are mostly "extract facts from a structured document" → you may not see measurable gain; activate this for complex implementation and agentic tasks. → Sonnet as planner + advisor()/reviewer (Opus) on-demand > Opus full-stack for most tasks.
Cost ratio: Sonnet ($3/$15) vs Opus ($15/$75). Quality first does NOT mean always-Opus; Opus only fires when quantitative gates trigger.
Per-Session Pre-flight (run once per session)
1. Reference Pattern Technique
| ❌ Abstract description | ✅ Point to a file |
|---|---|
| "Write a validation module" | "Follow the pattern in src/auth/validator.ts" |
| "Add a hook similar to useUser" | "Pattern: hooks/useUser.ts:42-78" |
| "Reference the deploy flow we used last time" | "Follow <your-playbook>.md Step 3-6" |
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.
- 10d ago First seen · 300 lines · 143 tokens per session scan A 7cd8331e901e
sonnet-pilot is a skill published in the GitHub repository zeuikli/claude-pilot-suite (24 stars, last pushed 4mo ago), licensed MIT. It adds 143 tokens to every session and 4,298 once invoked, about $0.0007 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 2026-08-30.
Other skills, from other repositories
bun-sqlite
Use for bun:sqlite, SQLite operations, prepared statements, transactions, and queries.
cloudflare-email-routing
Cloudflare Email Routing for receiving/sending emails via Workers. Use for email workers, forwarding, allowlists, or encountering Email Trigger errors, worker call failures, SPF issues.
bun-http-server
Use when building HTTP servers with Bun.serve, handling requests/responses, implementing routing, creating REST APIs, or configuring fetch handlers.
api-testing
HTTP API testing for TypeScript (Supertest) and Python (httpx, pytest). Test REST APIs, GraphQL, request/response validation, authentication, and error handling.
bun-jest-migration
Use when migrating from Jest to Bun's test runner, import compatibility, mocks, and config.
bun-test-mocking
Use for mock functions in Bun tests, spyOn, mock.module, implementations, and test doubles.