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 sharpdeveye/maestro --skill diagnosegit clone --depth 1 https://github.com/sharpdeveye/maestroWrote 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/sharpdeveye/maestro/diagnose)<a href="https://agentmods.dev/skills/sharpdeveye/maestro/diagnose"><img src="https://agentmods.dev/badge/skills/sharpdeveye/maestro/diagnose/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/sharpdeveye/maestro/diagnose"><img src="https://agentmods.dev/badge/skills/sharpdeveye/maestro/diagnose.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 | $0.00027 | $0.01359 |
| Opus 5.5 | $0.00011 | $0.00544 |
| Sonnet 5.5 | $0.00005 | $0.00272 |
| Haiku 4.5 | $0.00003 | $0.00136 |
Grade A, and why
diagnose 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 1mo 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 — 141 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.
Perform a systematic diagnostic scan across 5 dimensions. For each dimension, score 1-5 and provide specific findings.
Dimension 1: Prompt Quality (1-5)
Evaluate:
- Structure (4-zone pattern: role, context, instructions, output)
- Output schema definition (explicit vs. implicit)
- Instruction clarity (specific vs. vague)
- Edge case handling (addressed vs. ignored)
- Anti-patterns present (wall of text, contradictions, implicit format)
Dimension 2: Context Efficiency (1-5)
Evaluate:
- Context budget allocation (planned vs. ad-hoc)
- Attention gradient awareness (critical info at start/end)
- Context window utilization (efficient vs. wasteful)
- State management (explicit vs. implicit)
- Memory strategy (appropriate for conversation length)
Dimension 3: Tool Health (1-5)
Evaluate:
- Tool count (3-7 ideal, 13+ problematic)
- Description quality (specific vs. vague)
- Error handling (graceful vs. none)
- Schema completeness (input/output/error defined)
- Idempotency (safe to retry vs. side-effect prone)
- Scope attribution: Distinguish between project-configured tools (e.g., custom scripts, project MCP servers) and agent-level tools (e.g., built-in IDE tools, global MCP servers). Only flag tool overhead for tools the project can actually control
Dimension 4: Architecture Fitness (1-5)
Evaluate:
- Topology appropriateness (single vs. multi-agent justified)
- Agent boundaries (clear vs. overlapping)
- Handoff protocols (structured vs. ad-hoc)
- Observability (decisions logged vs. black box)
- Cost awareness (budgeted vs. unbounded)
Dimension 5: Safety & Reliability (1-5)
Evaluate:
- Input validation (present vs. absent)
- Output filtering (PII, content policy) — scope contextually: data flowing between a user's own frontend and backend (e.g., authenticated sessions, internal APIs) is lower risk than data exposed to external services or third-party APIs
- Cost controls (ceilings set vs. unbounded)
- Error recovery (fallbacks vs. crash)
- Evaluation strategy (golden tests vs. "it seems to work")
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.
- 1mo ago First seen · 141 lines · 27 tokens per session scan A 0c7859636631
diagnose is a skill published in the GitHub repository sharpdeveye/maestro (591 stars, last pushed 5mo ago), licensed MIT. It adds 27 tokens to every session and 1,359 once invoked, about $0.0001 per session on Opus 5.5. 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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