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/oyi77/1ai-skillsWrote 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/oyi77/1ai-skills/lint)<a href="https://agentmods.dev/commands/oyi77/1ai-skills/lint"><img src="https://agentmods.dev/badge/commands/oyi77/1ai-skills/lint/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/oyi77/1ai-skills/lint"><img src="https://agentmods.dev/badge/commands/oyi77/1ai-skills/lint.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 | $0.00111 |
| Opus 5 | $0.00000 | $0.00056 |
| Sonnet 5 | $0.00000 | $0.00022 |
| Haiku 4.5 | $0.00000 | $0.00011 |
Grade A, and why
lint 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.
What it actually says
/lint — Lint and fix skill content quality
Run content linter on skills and auto-fix common issues.
Steps
- Run
python3 scripts/lint-skills.py— content linting - Run
python3 scripts/lint-skills.py --write— auto-fix mode - Check for:
- Missing YAML frontmatter fields
- Inconsistent formatting
- Template placeholder text
- Missing sections
- Description quality
- Report fixes applied and remaining issues
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 · 16 lines · 0 tokens per session scan A 0a47f8bfaf42
lint is a command published in the GitHub repository oyi77/1ai-skills (12 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 111 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 2026-08-30.
Other commands, from other repositories
audit-accessibility
Audit web page or component for WCAG accessibility compliance.
validate-pipeline
Validate data pipeline configuration and data quality rules.
refly-login
Authenticate with Refly.
animal-handling
/volumes/vixinssd/wizardsoftheghosts/generated/openclaw/animal-handling/SKILL.md.
calm-emotions
/volumes/vixinssd/wizardsoftheghosts/generated/openclaw/calm-emotions/SKILL.md.
detect-thoughts
/volumes/vixinssd/wizardsoftheghosts/generated/openclaw/detect-thoughts/SKILL.md.