Borrowing it
Nothing to install: this file belongs to diillson/chatcli. 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/diillson/chatcli/main/.agent/skills/lint-and-validate/SKILL.mdgit clone --depth 1 https://github.com/diillson/chatcliWrote 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/diillson/chatcli/lint-and-validate)<a href="https://agentmods.dev/skills/diillson/chatcli/lint-and-validate"><img src="https://agentmods.dev/badge/skills/diillson/chatcli/lint-and-validate/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/diillson/chatcli/lint-and-validate"><img src="https://agentmods.dev/badge/skills/diillson/chatcli/lint-and-validate.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 | $0.00000 | $0.00450 |
| Opus 5.5 | $0.00000 | $0.00180 |
| Sonnet 5.5 | $0.00000 | $0.00090 |
| Haiku 4.5 | $0.00000 | $0.00045 |
Grade A, and why
lint-and-validate 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.
This is a copy
84% identical to lint-and-validate — 4 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Lint and Validate Skill
MANDATORY: Run appropriate validation tools after EVERY code change. Do not finish a task until the code is error-free.
Procedures by Ecosystem
Node.js / TypeScript
- Lint/Fix:
npm run lintornpx eslint "path" --fix - Types:
npx tsc --noEmit - Security:
npm audit --audit-level=high
Python
- Linter (Ruff):
ruff check "path" --fix(Fast & Modern) - Security (Bandit):
bandit -r "path" -ll - Types (MyPy):
mypy "path"
The Quality Loop
- Write/Edit Code
- Run Audit:
npm run lint && npx tsc --noEmit - Analyze Report: Check the "FINAL AUDIT REPORT" section.
- Fix & Repeat: Submitting code with "FINAL AUDIT" failures is NOT allowed.
Error Handling
- If
lintfails: Fix the style or syntax issues immediately. - If
tscfails: Correct type mismatches before proceeding. - If no tool is configured: Check the project root for
.eslintrc,tsconfig.json,pyproject.tomland suggest creating one.
Strict Rule: No code should be committed or reported as "done" without passing these checks.
Scripts
| Script | Purpose | Command |
|---|---|---|
scripts/lint_runner.py |
Unified lint check | python scripts/lint_runner.py <project_path> |
scripts/type_coverage.py |
Type coverage analysis | python scripts/type_coverage.py <project_path> |
What ships with it
2 files 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.
- 1mo ago First seen · 46 lines · 0 tokens per session scan A 00497ead822b
lint-and-validate is a skill published in the GitHub repository diillson/chatcli (93 stars, last pushed yesterday), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 450 tokens. A static security scan graded it A with 0 findings. It is 84% identical to lint-and-validate, differing in 4 lines, and is treated as a copy.
Other skills, from other repositories
error-recovery
A guide to detecting and recovering from failures in long-running AI agents. It covers API outages, bad tool calls, broken conversation state, stalled streams, repeated loops, retries, fallback models, and circuit breakers that stop repeated failure.
coding-agent-harness
A guide to building the surrounding system that lets an AI agent safely work on code. This system provides tools, rules, tests, feedback, permissions, and ways to undo changes.
04-audit
Audit a codebase read-only across seven quality pillars into one ranked report. Use when the user wants to assess, health-check, or audit a codebase or one pillar. Not for fixing findings, reviewing a change, or checking a feature works.
07-refactor
Improve code across four axes (cleanup, performance, security, architecture) by scanning and fixing, or applying a pushed audit report. Use when the user wants to refactor, optimize, harden, or remove code. Not for read-only diagnosis or adding tests.
03-assert
Assert the work behaves by iterating the project's coding assertions until they pass, plus optional architecture and frontend facets. Use to validate an implementation. Not for reviewing or writing tests.
08-debug
Reproduce and fix a known bug, or find an unknown root cause by hypothesis validation. Use when the user wants to fix a bug, find why something breaks, or reopen a stuck investigation. Not for building a feature or reviewing a diff.