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.
git clone --depth 1 https://github.com/ngocsangyem/MeowKitWrote 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/commands/ngocsangyem/meowkit/validate)<a href="https://agentmods.dev/commands/ngocsangyem/meowkit/validate"><img src="https://agentmods.dev/badge/commands/ngocsangyem/meowkit/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/commands/ngocsangyem/meowkit/validate"><img src="https://agentmods.dev/badge/commands/ngocsangyem/meowkit/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 | $0.00312 |
| Opus 5 | $0.00000 | $0.00156 |
| Sonnet 5 | $0.00000 | $0.00062 |
| Haiku 4.5 | $0.00000 | $0.00031 |
Grade A, and why
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 7d 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.
What it actually says
/validate — Deterministic Validation (Non-LLM)
Usage
/validate
Behavior
Runs deterministic validation scripts that check for anti-patterns WITHOUT using the LLM. Use this when you want certainty, not AI judgment.
Execution Steps
-
Run validation scripts. Execute the following Python scripts:
.claude/scripts/validate.py— checks for structural anti-patterns, naming convention violations, missing required files, and configuration issues..claude/scripts/security-scan.py— checks for security anti-patterns using pattern matching (regex-based, not LLM-based).
-
Collect results. Each script outputs machine-verifiable results in a structured format: file path, line number, rule violated, severity.
-
Print results. Display all findings. These are deterministic — running the same scripts on the same code will always produce the same output.
Why This Exists
LLM-based review (/mk:review, /mk:audit) is powerful but non-deterministic. /mk:validate provides a complementary layer of checks that are:
- Reproducible: same input always produces same output.
- Fast: no API calls, runs locally.
- Auditable: the rules are visible in the script source code.
Output
Machine-verifiable results from validate.py and security-scan.py. Each finding includes: file path, line number, rule violated, and severity.
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.
- 7d ago First seen · 33 lines · 0 tokens per session scan A 4618f4f568dc
validate is a command published in the GitHub repository ngocsangyem/MeowKit (14 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 312 tokens. 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 2026-09-03.
Other commands, from other repositories
techdebt
Find and report technical debt in the codebase.
ux-audit
Walk a live web app AS a real user — interaction-first methodology. Hard gates (console / network / layout-collapse), Persona Lock, Interaction Manifest enforcement, multi-pane stress, visual polish, perfection checklist, 11 scenarios (judgement-density-ordered), Top 5 + self-critique pass + smallest-possible-patch +…
sdlc-incident
Incident response and management - triage, mitigation, communication, action items.
sdlc-optimize
Performance optimization and profiling - identify bottlenecks, benchmark improvements.
sdlc-tech-debt
Tech debt paydown and strategic refactoring - prioritize improvements.
replay
Summarize one Agent Monitor session by id — header plus a concise transcript recap.