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buygit_deep_audit

Run a multi-vendor supply-chain audit on any GitHub repo or BuyGit catalog entry. Spawns Socket, OpenSSF, and TruffleHog checks in parallel and returns combined findings.

Instructions

Federated audit — spawns Socket / OpenSSF / TruffleHog companion MCPs in parallel and combines their findings with our catalog signals. The only MCP that one-shots a multi-vendor supply-chain check (vs. the user installing 4 MCPs and asking each separately). Companion MCPs that are not installed surface as federation_failures[] with operator hints. Soft-fails per-companion — always returns SOMETHING agent-actionable.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slug_or_urlYesEither a BuyGit slug (catalog row) or a github.com/{owner}/{repo} URL (live probe). Slug matches `^[a-z0-9-]+$`; URL matches `https?://github.com/owner/repo`.
federate_withNoWhich companion MCPs to chain. Defaults to all three.
timeout_msNoPer-companion hard timeout in milliseconds.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
targetYes
buygit_auditYesOur own audit (either catalog row or live GitHub probe).
federation_resultsYes
verdictNoOne-line aggregate (safe / review / risky / unverified).
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description must cover behavior. It discloses that companion MCPs are spawned in parallel, soft-fails per companion, and always returns something agent-actionable. It also explains that missing companions surface as federation_failures with hints. Could mention auth or rate limits but is sufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a tight paragraph of four sentences, front-loaded with the core purpose. Every sentence adds value, with no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity and that an output schema exists, the description covers the main aspects: federated execution, handling of missing companions, and guaranteed actionable output. It could specify the output structure but is acceptable.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with good parameter descriptions. The description does not add significant additional meaning beyond the schema for parameters. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool does a federated audit across Socket, OpenSSF, and TruffleHog in parallel, combining their findings with catalog signals. It distinguishes from siblings by emphasizing it is the only MCP that one-shots a multi-vendor supply-chain check, avoiding separate installations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly tells when to use this tool (for a combined multi-vendor check) and contrasts with alternatives (installing and querying four separate MCPs). It does not explicitly list when not to use it, but the context is clear enough for an agent.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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