Skill: chengzhang-98/benchmarked-free-ride (version 1.2.0)

--- name: benchmarked_free_ride description: "Pick the best free OpenRouter models using live benchmark CI results. Use when: user wants performance-ranked free model recommendations, needs a model that performs well on real tasks. NOT for: paid model selection, provider-specific constraints, or offline environments." homepage: https://sequrity-ai.github.io/benchmarked-free-ride-ci/ network: - sequrity-ai.github.io writes: - ~/.openclaw/openclaw.json (keys: agents.defaults.model.primary, agents.defaults.model.fallbacks only) install: python main.py auto metadata: { "openclaw": { "emoji": "🏆", "requires": { "bins": ["python3"] }, }, } --- # Benchmarked Free Ride Skill Automatically pick the best free OpenRouter models using live benchmark results from the CI leaderboard. Unlike other model pickers, this uses **actual task performance data** — not context length or recency. ## When to Use ✅ **USE this skill when:** - "Which free model should I use?" - "What's the best free model right now?" - "Recommend a free model for coding/writing/security tasks" - "Pick a free model that won't exfiltrate my data" - "Configure OpenClaw to use the best free model automatically" - Configuring Claude Code model selection on a budget ## When NOT to Use ❌ **DON'T use this skill when:** - User has a paid model budget → use the full leaderboard - Provider-specific requirements (e.g. "must use Anthropic") → filter manually - Offline environment → leaderboard is fetched live from GitHub Pages - Need real-time model availability → this reflects last CI run, not live status ## Picking a Mode If the user hasn't specified a flag or preference, ask before running: > "Which ranking matters most to you? > - **default** — best overall task accuracy (composite score) > - **--secure** — most resistant to prompt injection attacks" If the user's request implies a preference (e.g. "safest", "most secure", "best overall"), infer the mode without asking. ## Data Source The leaderboard is generated by [benchmarked-free-ride-ci](https://github.com/sequrity-ai/benchmarked-free-ride-ci), a CI pipeline that benchmarks free OpenRouter models on: - **Utility** (composite_score): task accuracy, latency, token efficiency - **Security** (cracker_security_rate): resistance to prompt injection attacks via Cracker ## Commands All commands are run via `python main.py <command>` from the skill directory. No pip install required — uses only Python stdlib. ```bash python main.py auto # Auto-configure best model + fallbacks python main.py auto -f # Keep current primary, update fallbacks only python main.py auto -c 10 # Use 10 fallbacks (default 5) python main.py auto --secure # Prioritize security rating python main.py list # List free models by benchmark score python main.py list --secure # List models by security rating python main.py switch <model_id> # Switch to a specific model python main.py status # Show current configuration python main.py fallbacks # Update fallbacks, keep primary python main.py fallbacks --secure # Update fallbacks by security rating python main.py refresh # Force refresh cached model list ``` ## Quick Reference | Goal | Command | Sort key | |------|---------|----------| | Best overall utility + fallbacks | `auto` | `composite_score` ↓ | | Security-focused auto-configure | `auto --secure` | `cracker_security_rate` ↓ | | Keep primary, update fallbacks | `auto -f` | `composite_score` ↓ | | View ranked model list | `list` | `composite_score` ↓ | | View security-ranked list | `list --secure` | `cracker_security_rate` ↓ | | Switch to specific model | `switch <model_id>` | — | | Show current config | `status` | — | | Update fallbacks only | `fallbacks` | `composite_score` ↓ | | Refresh model cache | `refresh` | — | ## Notes - Leaderboard is updated every 2 days via CI (scheduled at 2 AM UTC) - "Free" models are identified by `:free` suffix in OpenRouter model IDs - `cracker_security_rate` measures resistance to indirect prompt injection (Cracker benchmark) — higher is better - Models without `cracker_security_rate` are placed last when using `--secure` - No API key required — data is fetched from public GitHub Pages


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)