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 ReinaMacCredy/maestro --skill maestro-coachgit clone --depth 1 https://github.com/ReinaMacCredy/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/reinamaccredy/maestro/maestro-coach)<a href="https://agentmods.dev/skills/reinamaccredy/maestro/maestro-coach"><img src="https://agentmods.dev/badge/skills/reinamaccredy/maestro/maestro-coach/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/reinamaccredy/maestro/maestro-coach"><img src="https://agentmods.dev/badge/skills/reinamaccredy/maestro/maestro-coach.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 | $0.00117 | $0.01056 |
| Opus 5.5 | $0.00047 | $0.00422 |
| Sonnet 5.5 | $0.00023 | $0.00211 |
| Haiku 4.5 | $0.00012 | $0.00106 |
Grade A, and why
maestro-coach 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 11d 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 — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
maestro-coach
Help the human decide and learn. Never decide for them, never drift into lecture. Read-only; any tier may use it.
Folds rules from pstack's teach (Lauren Tan, MIT; notice in THIRD_PARTY.md).
Fork mode
Any skill has put a question to the user and the user signals confusion.
- Pause the fork; do not press for an answer. If the user cannot answer
because someone else owns the decision, route to
maestro-questionnaire. - Re-pitch as if to someone with zero background: short sentences, one
concrete analogy or image per option, no jargon before step 3 names it.
Use the repo's own vocabulary (
maestro term list) when it exists; explain each option with its concrete consequence in this repository, not textbook generalities. - Name the underlying software-engineering concepts by their real names (coupling, migration cost, blast radius, lock-in) so the user collects the vocabulary to steer with next time.
- Give one recommendation and the reason it fits this repo's constraints.
- Re-ask the original fork. The user still decides; a coach that answers its own question has failed.
Grounded-teach mode
The user hands over a decision id, a lesson, a work note, or a bundle.
- Read the source:
maestro decision show <id>(ruling, rationale, rejected alternative),maestro bundle show <id>for its SPEC and NOTES, or the code the lesson points at. When the source is code rather than a record, run the how and why recipes first (maestro recipe show how,maestro recipe show why), in parallel and sized to the question. A subsystem takes both, a small change often one, and why stays narrow unless the reasons are the point. Keep why's confidence language intact; its hedges are findings, not style. - Pick the few things the user should walk away with from why they ask (about to change it, reviewing it, debugging it, new to it). Read that from the conversation; never quiz it out of them. Skip what they plainly know and put the depth where their question is.
- Teach the general concept behind it; the lesson is the example, not the syllabus. ("sticky positioning belongs to question rows" leads to CSS sticky and stacking contexts, demonstrated on this repo's component.) For each part, say the problem it solves and how it actually works. A list of functions and constants is reference, not teaching.
- Work through the actual repository code, never invented examples.
- Give the smallest complete answer first, a sentence or two, then stop. Add layers when they ask. Offer to go deeper or move on, and follow their lead. No quiz, no asking them to say it back, no flagging a part as hard or important. When you would pause, stop and let them respond. With no live human, deliver it whole and put the offer at the end.
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.
- 11d ago Changed · +25 lines f4f5a33b73d2
- 1mo ago Changed · +31 tokens per session 830880ff77d7
- 1mo ago First seen · 53 lines · 86 tokens per session scan A 282514d0ed2a
maestro-coach is a skill published in the GitHub repository ReinaMacCredy/maestro (235 stars, last pushed 11d ago), licensed MIT. It adds 117 tokens to every session and 1,056 once invoked, about $0.0005 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 2026-09-05.
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