by mpecan · Agent Tool · ★ 196
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
brew install mpecan/tokf/tokf # or: cargo install tokf
brew install mpecan/tokf/tokfTaken from the project's README on GitHub.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 196 |
| Forks | 19 |
| Language | Rust |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 73/100 |
| Open Issues | 5 |
| Last Updated | 2026-09-06 |
| Created | 2026-02-18 |
| Platforms | claude-code, cli, rust |
| Est. Tokens | ~34k |
tokf tokf.net — reduce LLM context consumption from CLI commands by 60–90%. Commands like , , and produce verbose output packed with progress bars, compile noise, and boilerplate. tokf intercepts that output, applies a TOML filter, and emits only what matters — so your AI agent sees a clean signal instead of hundreds of wasted tokens. Before / After — 61 lines → 1 line: Without tokf With tokf
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Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: