clawmetry-selfcheck

clawmetry-selfcheck is a skill for Claude Code, Codex from vivekchand/clawmetry. It costs 64 tokens per session (521 once invoked), scanned A, original, MIT.

A read-only check of an AI agent’s usage and activity records from ClawMetry, a local tool that measures agent work. It reports repeated file reads, stalled progress, loops, and spending patterns.

In plain words
What is it for?
Use it before finishing a task to inspect waste, progress, and usage, then adjust the agent’s approach when the reports show a problem.
Why use it?
It helps reveal when an agent is rereading files, repeating the same attempts, or using more resources than the task needs.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/vivekchand/clawmetry/clawmetry-selfcheck
Any agent
npx skills add vivekchand/clawmetry --skill clawmetry-selfcheck
Clone the repo
git clone --depth 1 https://github.com/vivekchand/clawmetry

Made for: Claude Code, Codex.

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.

agentmods badge for clawmetry-selfcheck

README.md
[![agentmods](https://agentmods.dev/badge/skills/vivekchand/clawmetry/clawmetry-selfcheck.svg)](https://agentmods.dev/skills/vivekchand/clawmetry/clawmetry-selfcheck)
Your own site
<a href="https://agentmods.dev/skills/vivekchand/clawmetry/clawmetry-selfcheck"><img src="https://agentmods.dev/badge/skills/vivekchand/clawmetry/clawmetry-selfcheck.svg" alt="Measured on agentmods" height="20"></a>
Per session 64 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 521 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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.

ModelPer sessionOnce invoked
Fable 5 $0.00064 $0.00521
Opus 5 $0.00032 $0.00260
Sonnet 5 $0.00013 $0.00104
Haiku 4.5 $0.00006 $0.00052

Measured 4d ago against content hash 7522d4dd6191, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

clawmetry-selfcheck 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 4d 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.

docs/skills/clawmetry-selfcheck/SKILL.md · 49 lines

What it actually says

ClawMetry self-check

ClawMetry observes AI agent sessions on this machine (read-only). Use its CLI to see your own telemetry and improve your behaviour mid-task.

All commands are read-only, exit 3 when ClawMetry has no data source running (safe to skip silently), and support --json.

The 3-step check (run before finishing a task)

# 1. Re-read tax: files you paid to read more than once
clawmetry waste --since 6h --json

# 2. Spinning check: forward progress + loop signals
clawmetry progress --json

# 3. Spend check
clawmetry usage --json

How to act on what you find

Signal Action
A file with reads > 3 in waste Stop re-reading it. Write its structure into your working notes once; use offset-ranged reads for big files.
High ratio (tokens per state-delta) in progress You are burning tokens without producing new state. Write down what you tried, change strategy.
loop_signals non-empty You repeated near-identical calls. Do not retry the same thing; diagnose instead.
Cost spike in usage Check usage --by model: are you using a bigger model than the task needs?

Digging deeper

clawmetry sessions --active                  # who is running
clawmetry sessions <SID> --transcript        # what actually happened
clawmetry sessions <SID> --cost              # where the money went (incl. sub-agents)
clawmetry sessions <SID> --errors            # error events only
clawmetry activity --follow --max-events 50  # live NDJSON event stream
clawmetry usage --efficiency                 # A-F efficiency grade

Exit codes: 0 ok, 3 no data source (skip), 4 feature needs an upgrade (stderr carries a JSON body with upgrade_url; surface it to your human).

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.

  1. 4d ago First seen · 49 lines · 64 tokens per session scan A 7522d4dd6191

Subscribe to this mod's changes

clawmetry-selfcheck is a skill published in the GitHub repository vivekchand/clawmetry (404 stars, last pushed today), licensed MIT. It adds 64 tokens to every session and 521 once invoked, about $0.0003 per session on Opus 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.

Related

Other skills, from other repositories

go-rig

Use this skill when building, reviewing, or refactoring Go code that must follow strict design discipline — ATDD/TDD workflow, explicit dependency injection, package-boundary discipline, and structured code review. Complements CLAUDE.md by focusing on process and design judgment rather than version-specific Go…

mudrii/openclaw-dashboard · 64 tokens

frontend-dashboard

Use this skill when editing the embedded dashboard frontend in this repository. It focuses on preserving the single-file embedded SPA model, keeping the UI lightweight, and avoiding unnecessary frontend tooling or dependencies.

mudrii/openclaw-dashboard · 40 tokens

go-review

Use this skill when the task is to review Go code in this repository. Focus on bugs, regressions, API compatibility, test gaps, concurrency risks, and violations of the zero-dependency and root-facade constraints.

mudrii/openclaw-dashboard · 48 tokens

project-ops

Use this skill when working on repository operations in this project, including build, test, lint, release, CI alignment, Makefile-driven checks, and operational packaging constraints.

mudrii/openclaw-dashboard · 38 tokens

frontmcp-observability

Use when adding tracing, structured logging, metrics, or monitoring to a FrontMCP server. Covers zero-config OpenTelemetry distributed tracing across all flows; the this.telemetry API for custom spans, events, and attributes in tools, plugins, agents, and skills; structured JSON logging with trace correlation and…

agentfront/frontmcp · 177 tokens

impeccable

Use when the user wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states.…

monoscope-tech/monoscope · 189 tokens