An analysis tool for reviewing a project's command history and decision records. It produces a scorecard showing how often skills run, how often they finish successfully, and how commands flow into one another.

Use it to inspect Maestro audit and decision logs, compare completion rates, find common command sequences, and measure follow-up or abandonment patterns.

It helps identify skills that fail frequently, are rarely used, or commonly lead to unfinished work. This gives maintainers evidence for improving or removing workflow commands.

reflect — Skill for Claude Code by sharpdeveye/maestro

Install

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.

Any agent

npx skills add sharpdeveye/maestro --skill reflect

Clone the repo

git clone --depth 1 https://github.com/sharpdeveye/maestro

Made for: Claude Code.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/sharpdeveye/maestro/reflect/github.svg)](https://agentmods.dev/skills/sharpdeveye/maestro/reflect)

Your own site

<a href="https://agentmods.dev/skills/sharpdeveye/maestro/reflect"><img src="https://agentmods.dev/badge/skills/sharpdeveye/maestro/reflect/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/sharpdeveye/maestro/reflect"><img src="https://agentmods.dev/badge/skills/sharpdeveye/maestro/reflect.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 19 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 878 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

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	$0.00019	$0.00878
Opus 5.5	$0.00008	$0.00351
Sonnet 5.5	$0.00004	$0.00176
Haiku 4.5	$0.00002	$0.00088

Measured 1mo ago against content hash ed59b6c99782, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

reflect 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.

source/skills/reflect/SKILL.md · 108 lines

How it starts

The opening of the file, as written. The whole thing — 108 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.

Analyze the Maestro audit trail and decision log to produce a skill-effectiveness scorecard. This tells you which commands work, which fail, and where your workflow needs attention.

Data Sources

Read these files from the project root:

.maestro/audit.jsonl — every command invocation with duration, cost, and outcome
.maestro/decisions.jsonl — decisions made with outcomes and next steps

If neither file exists, respond: "No audit data found. Run commands with Maestro to start tracking, then come back."

Analysis Dimensions

1. Usage Frequency

Which commands run most/least?
Are any commands never used? (candidates for removal)

2. Completion Rate

What % of invocations complete successfully?
Which commands fail most often?

3. Command Flow

What are the most common command sequences (A → B)?
Which commands lead to follow-ups vs. abandonment?
Abandonment rate per command (no follow-up within 30 min)

4. Cost Distribution

Total estimated cost across all commands
Cost per command (average)
Most/least expensive commands

5. Duration Analysis

Average duration per command
Outliers (unusually slow invocations)

Output Format

╔══════════════════════════════════════════╗
║          MAESTRO EFFECTIVENESS           ║
╠══════════════════════════════════════════╣
║ Commands Run         __ (__ unique)      ║
║ Completion Rate      __%                 ║
║ Most Used            /_____ (__×)        ║
║ Most Abandoned       /_____ (__% ⚠️)     ║
║ Avg Duration         __s                 ║
║ Total Cost           ~$__.__             ║
╠══════════════════════════════════════════╣
║           STRONGEST PIPELINES            ║
╠══════════════════════════════════════════╣
║ /_____ → /_____    __×                   ║
║ /_____ → /_____    __×                   ║
╠══════════════════════════════════════════╣
║           COST PER COMMAND               ║
╠══════════════════════════════════════════╣
║ /_____    $__.__/run  ████░░  avg        ║
║ /_____    $__.__/run  █░░░░░  cheap      ║
║ /_____    $__.__/run  █████░  costly     ║
╚══════════════════════════════════════════╝

INSIGHTS:
1. [Data-driven observation with recommended action]
2. [Data-driven observation with recommended action]
3. [Data-driven observation with recommended action]

Read the full file on GitHub · 108 lines

Changes

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 · 108 lines · 19 tokens per session scan A ed59b6c99782

Subscribe to this mod's changes

reflect is a skill published in the GitHub repository sharpdeveye/maestro (591 stars, last pushed 5mo ago), licensed MIT. It adds 19 tokens to every session and 878 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.

Analytics and metrics Building agents Claude Code agent-orchestration ai ai-agents ai-workflows analysis codex

reflect

Getting it into your agent

Wrote this? Show the measurements

What it costs to keep this loaded

Grade A, and why

Nothing flagged

How it starts

MANDATORY PREPARATION

Data Sources

Analysis Dimensions

Output Format

What this file has done since we first saw it

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