agentleFS
Sign inStart free
zedarvateszedarvates/frugal-skills/skills/metrics/SKILL.md

metrics

Skill1 starsChanged 32 days agoMITView on GitHub

Instructions for collecting component-level project metrics and separating estimated context costs from measured provider usage. Use to report LOC, duplicate groups, directive health and routing observations with their scope and evidence; do not infer savings from missing counters.

20 other projects use a version of this, 1 of them edited.

Adopted by

Most recently taken up by

Used with

Projects with it also use knowledge-graph, scan and 8 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • ddehartSkill

    knowledge-graph

    Search, capture, and query the claude-code-plugins knowledge graph. Use when asked to "capture this", "add this to the graph", "what do we know about X", "update the graph", "check the graph for X", or when a decision, pattern, or non-obvious fact surfaces mid-session that's worth recording. Also: "log an observation", "what patterns do we have about skill triggering", "any decisions on the knowledge-commons plugin", "what do we know about the commit-creator agent".

    Also in 3 projects that use this

  • rajnavakotiSkill

    scan

    Run the AI dashboard scanner and generate the HTML report.

    Also in 3 projects that use this

  • MicrosoftSkill

    retrospective

    Review how work went and improve the next round. USE WHEN asked for a retro, delays, or process lessons. DO NOT USE for code review or transcript replay.

    Also in 3 projects that use this

  • OpenAISkill

    observability

    Vercel Observability expert guidance — Drains (logs, traces, speed insights, web analytics), Web Analytics, Speed Insights, runtime logs, custom events, OpenTelemetry integration, and monitoring dashboards. Use when instrumenting, debugging, or optimizing application performance and user experience on Vercel.

    Also in 3 projects that use this

  • BlockSkill

    plan

    Draft a TDD, PRD, or lightweight plan in the conversation without committing it.

    Also in 5 projects that use this

  • 0xSeroSkill

    security

    Also in 3 projects that use this

The file

Create a free account to mount
Files
SKILL.md

metrics — quantify a project's token/cost profile

Package scope and prerequisites

This catalog ships instructions, not the executable runtime. Python modules, scripts, local services and optional tools named below must be installed separately from the upstream project. Check their availability before running commands; if they are missing, explain the prerequisite instead of claiming execution or results. The host agent may use model tokens while following these instructions.

Surfaces the numbers an audit should give you, framed around cost. A multi-stack project (website + game server + client + tools) has no single number, so everything is broken down per component.

python -m skills.metrics.cli <project>
python -m skills.metrics.cli <project> --porthos reports/<proj>/audit-report.json --json

What to report

  • LOC and duplicate-function candidates, grouped by component.
  • Declared instruction sizes and estimated resend costs with tokenizer and turn assumptions.
  • Observed backend and routing configuration, not assumed savings.
  • Runtime counters with their scope and provenance; they are not a measurement of total host usage.
  • Deep-audit summaries only when the underlying report is available and verified.

State which values are measured, estimated, or unavailable. Do not fill missing counters with zero or justify an optimization using an invented baseline.

Exposed via [[llm-mcp]] as the metrics tool. Related: [[infra-advisor]] (auto audit), [[directives-audit]], [[skill-finder]], [[bootstrap]].

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

Check your setup, free