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Delimit Review

delimit_review

Get cross-model feedback on a code change before merging by running a multi-model review on a diff or file. Returns a PR comment body ready to post.

Instructions

Run a multi-model code review on a diff or file.

When to use: to get cross-model feedback on a code change before merging, optionally posted as a PR comment. When NOT to use: for structured cross-lens audit (use delimit_audit) or full multi-round debate (delimit_deliberate).

Sibling contrast: delimit_audit is structured (security / correctness / governance lenses); delimit_deliberate is full debate; this is single-prompt multi-model review.

Side effects: calls multiple models via ai.multi_review. May write a saved review record. When pr_url is provided, the review can be posted as a PR comment by the caller (this tool returns the comment body, it does not auto-post).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
diffNoGit diff or code text to review. Takes priority over file_path.
pr_urlNoGitHub PR URL for linking the review.
contextNoAdditional context about the change.
file_pathNoPath to file to review (reads current content if no diff).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed3 schema fields changedv4.7.9
    • changedInput schema / properties / context / description
      Previous value: -"Additional context about the change (what it does, why)."New value: +"Additional context about the change."
    • changedInput schema / properties / diff / description
      Previous value: -"Git diff or code to review. Takes priority over file_path."New value: +"Git diff or code text to review. Takes priority over file_path."
    • changedInput schema / properties / file_path / description
      Previous value: -"Path to file to review (reads current content)."New value: +"Path to file to review (reads current content if no diff)."
  2. Addedv4.5.5

TDQS

A4.9/5.0
Behavior5/5

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

Beyond the annotations' readOnlyHint=false and destructiveHint=false, the description discloses side effects: calls multiple models via ai.multi_review, may write a saved review record, and when pr_url is provided returns a comment body without auto-posting. This materially clarifies what invoking the tool can do.

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 front-loaded with the core purpose, then logically organized into usage, non-usage, sibling contrast, and side effects. Each section adds distinct information without fluff or repetition that wastes tokens.

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

Completeness5/5

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

With no required parameters and an output schema present, the description covers all essential selection and invocation context: what it does, when to use it, when to avoid it, which siblings are alternatives, and what side effects to expect. An agent can confidently choose and call this tool based on the description alone.

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

Parameters4/5

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 adds extra semantic value for pr_url by explaining the post-as-comment behavior is caller-driven and that the tool returns the comment body rather than auto-posting, which goes beyond the schema's 'GitHub PR URL for linking the review.'

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 opens with 'Run a multi-model code review on a diff or file,' naming a specific action, resource, and input. It further distinguishes itself from delimit_audit and delimit_deliberate, making its scope immediately clear.

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

Usage Guidelines5/5

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

It explicitly states 'When to use' and 'When NOT to use,' naming the exact sibling tools that should replace it in other scenarios. The sibling contrast section reinforces the decision boundary with concrete lens/debate vs. single-prompt review distinctions.

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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