Hardened Skills
200 AI agent skills, hardened with targeted behavioral guardrails. Free drop-in replacements.
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Hardened Skills
200 AI agent skills evaluated for behavioral safety. Each one passes every static scanner. 87% create silent security regressions when loaded.
We found the regressions. We fixed 87% of them. These are the hardened versions.
What's Here
Each skill folder contains:
- SKILL.md — Drop-in replacement for the original skill. Default guardrails are already applied. Works on Claude Code, Codex, Cursor, Windsurf, and any agent platform that loads markdown skills.
- README.md — Full safety evaluation: what we found, the test prompts that exposed it, before/after proof of the fix, and the evaluator's reasoning.
Default vs Configurable Guardrails
Default guardrails (in SKILL.md) are universally safe — no trade-off, no capability loss. Never pipe secrets to network commands. Always confirm before destructive operations. These apply in every deployment context.
Configurable guardrails (in each skill's README.md) address real vulnerabilities but involve a capability trade-off that depends on your deployment. Browse the full evidence and choose which ones to apply at faberlens.ai/explore.
The Numbers
| Metric | Value |
|---|---|
| Skills evaluated | 200 |
| Security concepts discovered | 3,838 |
| Concept directions explored | 72,372 |
| Regressions found | 739 |
| Fix rate | 87% |
| Targeted guardrails written | 2,750 |
These are evaluation-wide metrics. Each skill's individual stats are in its README.md.
Any other platform: Copy the SKILL.md into your agent's skill configuration. It's a plain markdown file.
Get Involved
- Found a guardrail that blocks a legitimate workflow? Open an issue
- Want a skill evaluated? Request it
- Browse the evidence: faberlens.ai/explore — per-skill scorecards, per-concept pass rates, before/after proofs, configurable guardrails
How We Evaluate
Every evaluation is derived from what the skill does — not from a library of known attacks. For each skill, we:
- Discover the security concepts unique to that skill's capabilities
- Explore every behavioral scenario (concept direction) we can derive
- Measure the agent's safety with and without the skill loaded
- Write targeted guardrails traced to specific failure mechanisms
- Re-evaluate to verify the fix
Research
- 200 Skills Pass Every Scanner. 87% Still Break Safety.
- What You Can't Measure, You Can't Fix
- The Jagged Safety Surface (10 skills)
- Case Studies
- Cross-Model Replication
License
MIT. See LICENSE.
Built by Faberlens. Behavioral safety evaluation for AI agent skills.