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-improvegit 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-improve)<a href="https://agentmods.dev/skills/reinamaccredy/maestro/maestro-improve"><img src="https://agentmods.dev/badge/skills/reinamaccredy/maestro/maestro-improve/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-improve"><img src="https://agentmods.dev/badge/skills/reinamaccredy/maestro/maestro-improve.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 | $0.00000 | $0.01227 |
| Opus 5 | $0.00000 | $0.00613 |
| Sonnet 5 | $0.00000 | $0.00245 |
| Haiku 4.5 | $0.00000 | $0.00123 |
Grade A, and why
maestro-improve 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 6d 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 — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
maestro-improve
Use when a Lead assigns improvement work on one target to a Peer. The target is the only parameter; a separate Peer challenges the returned candidate before acceptance.
A correction that stays in a transcript is spent when that session ends. The lesson record is what survives, and doctrine is the only thing a future session actually reads. This skill is the one place the two are joined: it turns filed corrections into the smallest edit that would have prevented them.
The parameter
The target names the doctrine a lesson corrects: a recipe section, the SLP
Workspace Pack in src/plugins/resources/SLP.md, a Hub template, a
skills/maestro-* file, or a repository's Workspace Protocol. Where each one
lives, and what an edit to it costs, is in
references/targets.md.
The loop
maestro lesson list --project <project> # pending only, by design
maestro lesson show <id> # the gap, the expectation, the why
- Group the pending lessons by target. Two lessons on one rule are one edit, not two, and the second one is usually what tells you which reading of the rule was ambiguous.
- Per group, propose the smallest edit that would have prevented what happened. Doctrine is read under load, so a sentence that removes an ambiguity beats a paragraph that adds a procedure. If the existing text already says it, the lesson is a rejection, not an edit.
- One commit per target group, on a branch, with the evidence ids of every lesson in the group in the message. The ids are how a later reader gets from the rule back to the incident that shaped it.
- Mark each lesson processed by pointing at that commit:
maestro lesson process <id> --commit <sha>
The improver never deletes a lesson and never edits one. Processing is a pointer, so the record of what was corrected stays readable after the doctrine it corrected has changed again.
Rejecting a lesson
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 6d ago Changed · +6 lines · -54 tokens per session a00237e3d162
- 11d ago First seen · 108 lines · 54 tokens per session scan A f6f8a1a70239
maestro-improve is a skill published in the GitHub repository ReinaMacCredy/maestro (232 stars, last pushed 5d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,227 tokens. 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
pn-github-vertical-slices
Break a plan or PRD into tracer-bullet vertical slices and create GitHub Issues via GitHub MCP (official github/github-mcp-server). Dependencies first (AFK/HITL). Use after pn-writing-plans or pn-create-prd when work must ship as Issues.
github-copilot-upgrader
Use this to update the Github Copilot CLI/SDK.
commit
Commit staged or unstaged changes with an AI-generated commit message that matches the repository's existing commit style. Use when the user asks to 'commit', 'commit changes', 'create a commit', 'save my work', or 'check in code'.
create-pr
Creates a GitHub PR with a Linear-ticket-prefixed title and a decision-led, narrative description for prisma-next. Use when the user wants to create a pull request, open a PR, or submit changes for review.
review-implement-phase
Implements triaged review actions, commits focused fixes, and posts Done plus resolves threads. Use when the user wants only the implementation phase of the review-framework workflow.
review-triage-phase
Produces canonical review actions from fetched review state and renders action markdown. Use when the user wants only triage/action-planning for the review-framework workflow.