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Request pull request changes at exact head

gh_request_pr_changes

Submit a formal GitHub CHANGES_REQUESTED review to request changes on a pull request, verifying the reviewer login and head SHA. Guarantees a single immutable review submission.

Instructions

Additive write: submit exactly one formal GitHub CHANGES_REQUESTED review for the supplied exact pull-request head through the server-configured reviewer principal. The exact expected reviewer login is a compare-only precondition and cannot select credentials. The review POST is attempted once and immutable review-ID readback verifies state, actor, head, and body. It cannot approve, merge, dismiss reviews, or replay an ambiguous mutation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYesNon-empty Markdown body explaining the requested changes.
repoYesGitHub repository name without the owner prefix.
ownerYesGitHub repository owner or organization login.
numberYesPull request number on which to request changes.
expected_head_shaYesExact pull-request head SHA that was independently reviewed.
expected_reviewer_loginYesExact reviewer actor login expected from the server-configured reviewer principal. This is a compare-only precondition and never selects credentials.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
bodyYes
stateYes
actionNorequest_changes
authorNo
numberYes
messageYes
warningNo
review_idYes
commit_shaYes
request_idNo
submitted_atNo
write_completedYes
readback_completedYes
precondition_checkedYes
state_matches_requestedYes
Behavior4/5

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

The description discloses that the operation is an 'additive write' and mentions preconditions like 'compare-only' and 'immutable readback', which aligns with the annotations (readOnlyHint=false, destructiveHint=false). It could elaborate on potential side effects, but the core write nature is transparent.

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

Conciseness2/5

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

The description is excessively verbose and repetitive, using phrases like 'exact' and 'compare-only precondition' multiple times. This redundancy impedes quick comprehension and violates conciseness, despite being structurally presented as a single cohesive paragraph.

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?

The description covers the main action and exclusions but lacks details about return values or error handling. While an output schema exists (so return explanation isn't mandatory), the description could benefit from clarifying expected outcomes or failure modes. It's adequate but not comprehensive.

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?

All six parameters have detailed descriptions that add meaningful context beyond their names, such as 'expected_reviewer_login' being tied to a 'server-configured reviewer principal'. This enriches the schema's baseline coverage, justifying a score above the default 3.

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

Purpose4/5

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

The description clearly states it submits a formal GitHub CHANGES_REQUESTED review, which distinguishes it from sibling tools like approve or comment. The phrase 'exactly one' adds specificity, but the verbose wording could be simplified without losing meaning.

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 provides exclusions (cannot approve, merge, dismiss) but does not give positive guidance on when to prefer this tool over alternatives. It lacks explicit scenarios or conditions for use, relying on implicit inference from the exclusions.

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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