Search the skill radar
Search by skill, publisher, category, or trust summary — then use the runtime filters to find cards with live test evidence. The two main lanes are baseline safety checks first and deeper follow-on functionality checks after that.
✨ Quick picks
🏷 Categories
🧾 Evidence level: source-scanned means local source evidence; catalog-only means thinner metadata-first coverage.
🧪 Runtime status: cards can show only the baseline safety lane or the deeper follow-on functionality lane, depending on how far the skill got.
📏 Depth cue: tells you whether the evidence stops at baseline checks, includes follow-on functionality checks, or includes richer fixture/example proof.
⏱ Freshness cue: tells you whether the latest runtime evidence is from the last 24 hours, the last 7 days, or is older and therefore less current.
🩺 Failure confidence: distinguishes a first seen failure from a repeated failure or a regression after an earlier pass, so not every red row means the same thing.
Results
oktk
LLM Token Optimizer - Reduce AI API costs by 60-90%. Compresses CLI outputs (git, docker, kubectl) before sending to GPT-4/Claude. AI auto-learning included. By Buba Draugelis 🇱🇹
+ 2 more
token-optimizer-qsmtco
Reduce OpenClaw token usage and API costs through smart model routing, heartbeat optimization, budget tracking, and multi-provider fallbacks. Use when token costs are high, API rate limits are being hit, or hosting multiple agents at scale. Includes ready-to-use scripts for task classification, usage monitoring, and optimized heartbeat scheduling. All operations are local file analysis only - no network requests, no code execution. See SECURITY.md for details.