auditing-declared-vs-used-permissions
SolidFind 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.
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
Integrates with
Similar Skills
Semantically similar based on skill content — not just same category
auditing-ai-agent-permissions
Audit 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.
skill-supply-chain-audit
Audit agent skills, plugins, prompts, manifests, scripts, dependencies, and bundled assets for provenance, prompt-injection, permission, execution, exfiltration, persistence, and update risk. Use when evaluating a third-party skill before installing, enabling, updating, publishing, or distributing it; reviewing an untrusted SKILL.md, agent configuration, MCP integration, archive, or repository; comparing a package with a known-good version; or investigating unexpected tool, network, credential, or filesystem behavior.
auditing-skill-and-mcp-instructions
Lint the natural-language instruction text of an agent skill or MCP server, not its code: the skill body, the frontmatter description, tool descriptions, and parameter text a model reads and obeys. Covers instructions hidden in comments or markup, invisible and look-alike Unicode, override phrases that countermand earlier instructions, concealment directives that tell the agent to hide an action from the user, and instructions that steer the agent to read secrets and send them out. Use when reviewing a skill, an MCP server, or a marketplace entry before trusting it, or auditing what instruction text enters an agent's context. Every word the model reads is instruction surface; a planted instruction is the finding.