Borrowing it
Nothing to install: this file belongs to jhd3197/CachiBot. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/jhd3197/CachiBot/main/.claude/skills/lint-fix/SKILL.mdgit clone --depth 1 https://github.com/jhd3197/CachiBotWrote 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/jhd3197/cachibot/lint-fix)<a href="https://agentmods.dev/skills/jhd3197/cachibot/lint-fix"><img src="https://agentmods.dev/badge/skills/jhd3197/cachibot/lint-fix/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/jhd3197/cachibot/lint-fix"><img src="https://agentmods.dev/badge/skills/jhd3197/cachibot/lint-fix.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00046 | $0.01260 |
| Opus 5 | $0.00023 | $0.00630 |
| Sonnet 5 | $0.00009 | $0.00252 |
| Haiku 4.5 | $0.00005 | $0.00126 |
Grade A, and why
lint-fix 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 9d 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 — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Lint Fix — Full Project Lint & Type Sweep
Run every linter the project uses, collect all violations, and fix them in a single pass. Handles Python (ruff + mypy) and TypeScript (eslint) together.
Instructions
Phase 0 — Run All Linters
Run all four checks in parallel and collect their output:
ruff check cachibot/— lint errors (E501, F841, etc.)ruff format --check cachibot/— formatting driftmypy cachibot/— type errors (only incachibot/, NOT transitive errors from prompture or other installed packages)cd frontend && npx eslint src/— TypeScript lint (errors only, warnings are informational)
Parse each tool's output into a list of { tool, file, line, code, message } findings.
Important: When parsing mypy output, discard any finding whose file path is
outside cachibot/ (e.g., errors in installed packages like prompture). Also
discard import-not-found errors for prompture.* and tukuy.* modules — those are
expected when the editable installs are out of sync and are not CachiBot bugs.
If zero findings remain after filtering, tell the user everything is clean and stop.
Phase 1 — Auto-Fix What Tools Can
Run the auto-fixers first to knock out the easy ones:
ruff check --fix cachibot/— auto-fix simple lint issuesruff format cachibot/— reformat any drifted filescd frontend && npx eslint src/ --fix— auto-fix simple TS issues
Phase 2 — Fix Remaining Violations
Re-run the linters from Phase 0 to see what remains after auto-fix.
For each remaining finding, apply the appropriate fix strategy:
ruff E501 (line too long)
- If the long line is a string literal inside a dict/list, wrap it with
implicit string concatenation using parentheses:
"description": ( "First part of the string" " second part of the string" ), - If the long line is a function call or dict literal, break it into multi-line format.
- If the long line is an import, use multi-line import with parentheses.
- Never shorten user-facing strings by removing words — prefer wrapping.
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.
- 9d ago First seen · 130 lines · 46 tokens per session scan A f9a148f40b7c
lint-fix is a skill published in the GitHub repository jhd3197/CachiBot (19 stars, last pushed 6mo ago), licensed MIT. It adds 46 tokens to every session and 1,260 once invoked, about $0.0002 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.
Other skills, from other repositories
goclaw
Use this skill when administering, operating, or debugging a GoClaw gateway through the GoClaw CLI/runtime package. It covers CLI discovery, safe command inspection, gateway health/config diagnostics, agents, skills, MCP/tools, runtime packages, credentials, traces, sessions, channels, providers, cron/jobs, and…
debug
Enable debug logging for this session and help diagnose issues.
node-connect
Diagnose OpenClaw node connection and pairing failures for Android, iOS, and macOS companion apps. Use when QR/setup code/manual connect fails, local Wi-Fi works but VPS/tailnet does not, or errors mention pairing required, unauthorized, bootstrap token invalid or expired, gateway.bind, gateway.remote.url, Tailscale…
ai-core/debug-logging
Pluggable, category-toggleable debug logging for TanStack AI activities. Toggle with debug: true | false | DebugConfig on chat(), summarize(), generateImage(), generateSpeech(), generateTranscription(), generateVideo(). Categories: request, provider, output, middleware, tools, agentLoop, config, errors. Pipe into…
ha-logs
A read-only troubleshooting skill for querying Hope Agent’s local SQLite databases, which store logs, conversations, and background-job status.
ha-self-diagnosis
Self-understanding and issue reporting for Hope Agent itself. Use when the user asks how Hope Agent works internally, asks about its own source code/docs/runtime behavior, reports a bug/failure/slowness/crash, asks to diagnose logs, or asks to create/submit a GitHub issue for a bug, feature request, or improvement…