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 agentmods add skills/sharpdeveye/maestro/zero-defectnpx skills add sharpdeveye/maestro --skill zero-defectgit clone --depth 1 https://github.com/sharpdeveye/maestroWhat 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 | $0.00033 | $0.00925 |
| Opus 5 | $0.00016 | $0.00463 |
| Sonnet 5 | $0.00007 | $0.00185 |
| Haiku 4.5 | $0.00003 | $0.00093 |
Grade A, and why
zero-defect 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 yesterday.
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 — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MANDATORY PREPARATION
Invoke /agent-workflow — it contains workflow principles, anti-patterns, and the Context Gathering Protocol. Follow the protocol before proceeding — if no workflow context exists yet, you MUST run /teach-maestro first.
Activate maximum precision mode for the current session. This command establishes execution-time discipline — not for the workflow design, but for how the agent itself operates. Every response, every code change, every claim must pass the zero-defect gate.
This is model-agnostic. It works with Claude, Gemini, GPT, Codex, or any AI agent.
The 8 Precision Rules
Follow these for the entire session after this command is invoked:
| # | Rule | Why |
|---|---|---|
| 1 | Read before writing — Re-read the relevant code/context before every modification | Prevents edits based on stale mental models |
| 2 | Verify before claiming — Run verification before any success claim | Prevents false completion reports |
| 3 | One logical change at a time — Avoid sprawling multi-file edits that compound errors | Reduces cascading failures |
| 4 | State uncertainty explicitly — Say "I'm not sure about X" instead of guessing | Prevents confident hallucination |
| 5 | Check every import and reference — Verify that every function, variable, and module exists | Prevents "symbol not found" errors |
| 6 | Dry-run mentally before committing — Trace the code path for both happy path and edge cases | Catches logic errors before they ship |
| 7 | Never hallucinate APIs — Only use functions, methods, and parameters that exist in the codebase or documentation | Prevents non-existent API calls |
| 8 | Re-derive, don't recall — For math, logic, or complex reasoning, work it out fresh instead of from memory | Prevents confident but wrong answers |
The Pre-Commit Gate
Before claiming ANY work is complete, pass every item:
- Code compiles / lints clean (run the actual command)
- Tests pass (run the actual command)
- Every new import/dependency actually exists
- Every function call uses the correct signature and arguments
- Edge cases considered (null, empty, boundary values, error states)
- No hardcoded values that should be configurable
- Error handling present for every external call
- Output matches what was requested (re-read the original request)
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.
- yesterday First seen · 84 lines · 33 tokens per session scan A 49023ea5fd9d
zero-defect is a skill published in the GitHub repository sharpdeveye/maestro (415 stars, last pushed 4mo ago), licensed MIT. It adds 33 tokens to every session and 925 once invoked, about $0.0002 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.
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