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veto_pr_review

Read-only

Fetches a GitHub PR diff and runs a triple-scan (code review, security, secrets) to return a structured verdict and ready-to-post review comments.

Instructions

Fetches a GitHub PR diff and runs the full Veto triple-scan (code review + security + secrets). Returns a structured verdict and ready-to-post GitHub review comments. Set GITHUB_TOKEN env var for private repos.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pr_urlYesFull GitHub PR URL. e.g. https://github.com/owner/repo/pull/123
contextNoOptional: PR description or ticket number for extra context.
fail_onNoWhether WARN counts as a failure. Default: "fail".
agent_outputsNoPhase 2 responses from the host AI (JSON). Pass this back when prompted by the server to complete the agentic loop.
Behavior3/5

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

Annotations already provide readOnlyHint=true and openWorldHint=true, covering safety and external access. The description adds context by noting the need for GITHUB_TOKEN for private repos, which is useful. However, it does not detail other behavioral traits like error handling, rate limits, or what happens if the PR is not found. With annotations carrying the main burden, the description provides moderate additional value.

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 concise: three sentences covering purpose, output, and prerequisite. Information is front-loaded with no unnecessary words. Every sentence adds value.

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

Completeness3/5

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

Although the tool has four parameters with full schema coverage and annotations, there is no output schema, so the description should explain return values. It mentions 'structured verdict and ready-to-post GitHub review comments' but lacks detail on the structure. For a complex multi-scan tool, this is adequate but leaves gaps about the exact output format and error scenarios.

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%, so the baseline is 3. The description's parameter explanations are nearly identical to the schema descriptions (e.g., pr_url, context, fail_on, agent_outputs). It adds no new meaning beyond the schema, so the score remains at baseline.

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?

Description clearly states the tool fetches a GitHub PR diff and runs the Veto triple-scan (code review, security, secrets). It specifies the verb 'Fetches' and 'runs', and names the resource (GitHub PR). This distinguishes it from siblings like veto_code_review or veto_security_scan which are individual scans.

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

Usage Guidelines3/5

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

The description implies usage for a comprehensive scan of a PR, mentioning the need for a GITHUB_TOKEN for private repos. However, it does not explicitly state when to use this tool versus alternatives (e.g., individual scan tools) or when not to use it. The usage context is implied but lacks explicit guidance.

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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