auditing-ai-agent-permissions
SolidAudit what an AI agent is actually allowed to do versus what its task needs. Covers excessive agency (tools, scopes, and autonomy beyond the job), missing human-in-the-loop gates on irreversible actions, over-broad credentials and their blast radius, sandbox and code-interpreter escape, unfiltered egress, and unbounded resource or spend (denial-of-wallet). Use when granting an agent a tool or scope, reviewing an agent's permission posture, or deciding which actions need approval. The model's restraint is not a control; permissions are.
Install
Quality Score: 80/100
Skill Content
Details
- Author
- UnboundCompute
- Repository
- UnboundCompute/security-agent-skills
- Created
- 5 days ago
- Last Updated
- yesterday
- Language
- N/A
- License
- MIT
Similar Skills
Semantically similar based on skill content — not just same category
agent-tool-permissions
Configure what a coding agent may do without asking, balancing autonomy against the cost of an unwanted action. Use when setting up an agent's permissions for a project.
auditing-agent-behavior
Audit an agent for risky behavior before it ships, the way you would red-team it, but automated. An auditor agent runs many multi-turn scenarios against your target agent from seed instructions you write, and a judge model scores the transcripts for deception, sycophancy, oversight subversion, power-seeking, and cooperation with misuse. Covers writing seed instructions that probe your agent's real risks, adapting the scoring rubric to your domain, and reading flagged transcripts. Use this when someone wants to red-team or safety-test an agent, asks how to find deceptive or manipulable behavior, audits a model or agent before deployment, or compares behavior across model versions. Trigger on "red-team my agent," "audit agent behavior," "test for deception," "alignment testing," and similar. This is auditing behavior for safety; measuring task success is build-agent-evals, and stopping objective-gaming is reward-hacking-and-inoculation.
auditing-declared-vs-used-permissions
Find the consent gap in an agent skill or MCP server: the distance between the permissions and capabilities it declares and what its bundled code and instructions actually exercise. Covers over-broad grants a skill requests but never uses, capabilities it exercises without declaring, and grants that are used but still wider than the task needs. Read the declared surface in frontmatter or manifest, inventory the real behavior, and diff the two in both directions. Use when reviewing a skill or server before install, or auditing least privilege across an agent's installed set. An over-broad or undeclared grant is the finding.