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GitHub PR Issue Analyser

by saidsef
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Github Create Pr

github_create_pr

Creates a GitHub pull request and applies labels automatically, with options for draft status and custom labels to streamline PR management.

Instructions

Creates a new pull request. Labels are applied in a second call, since the create endpoint takes none, and they come back under labels so a set the token could not write is visible.

Workflow and conventions: github_get_skill('pr-management').

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
baseYes
bodyYes
headYes
draftNo
titleYes
labelsNoLabels to apply, with the 'mcp' tracking label appended unless mcp_label is False. Omit to leave the pull request unlabelled
mcp_labelNoAppend the 'mcp' tracking label to labels. Pass False to opt out
repo_nameYes
repo_ownerYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv42.1.1
    • changedInput schema / properties / labels / description
      Previous value: -"Labels to apply, with mcp appended. Omit to leave the pull request unlabelled"New value: +"Labels to apply, with the 'mcp' tracking label appended unless mcp_label is False. Omit to leave the pull request unlabelled"
    • addedInput schema / properties / mcp_label
      Added value: +{
+  "default": true,
+  "description": "Append the 'mcp' tracking label to labels. Pass False to opt out",
+  "type": "boolean"
+}
  2. Addedv42.0.0

TDQS

B3.4/5.0
Behavior4/5

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

Annotations cover the basic safety profile (readOnly false, destructive false, etc.), and the description adds meaningful behavior beyond that: labels are applied in a second call because the create endpoint accepts none, and the response exposes whether the token could write labels. This is useful non-obvious context, though auth and rate-limit details are omitted.

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

Conciseness4/5

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

The description is concise and front-loads the purpose in the first sentence. The label-handling detail is useful but phrased awkwardly, and the skill pointer is terse. There is no filler, but the second sentence could be clearer.

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

Completeness2/5

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

With nine parameters and only 22% schema coverage, the description leaves much to inference. It helps on label behavior but does not explain required fields, preconditions, or the overall workflow, instead pointing to an external skill. The output schema exists, so return values are covered, but the description is not complete enough for a tool of this complexity.

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

Parameters2/5

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

Schema description coverage is only 22%, so the description bears the burden of explaining parameters. It adds some semantics around the labels parameter (second-call application and failure visibility), but the six required parameters—repo_owner, repo_name, title, body, head, base—and mcp_label are entirely undescribed in the description.

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 first sentence states clearly that the tool creates a new pull request, using a specific verb and resource. This distinguishes it from sibling create tools like github_create_issue and github_create_milestone without merely restating the tool name.

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

Usage Guidelines2/5

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

There is no explicit guidance on when to use this tool versus alternatives such as github_update_pr or github_create_issue. The reference to github_get_skill('pr-management') defers to an external skill rather than stating when to choose this tool, and no prerequisites or exclusions are mentioned.

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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