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get_issue

Retrieve detailed GitHub issue information including labels, assignees, bounties, and linked pull requests to understand context before working on tasks.

Instructions

Use this when you need full issue context before working on it (labels, assignees, bounties, linked PRs). Returns number, title, state, author, description, comments count, labels, assignees, bounties, created_at, updated_at, closed_at, and closed_by. Requires 'owner', 'name', and 'issue_iid'. See also: list_issues, comment_on_issue, update_issue.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ownerYesRepository owner (username or DAO name)
nameYesRepository name
issue_iidYesIssue number (IID)
Behavior3/5

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

With no annotations provided, the description carries the full burden. It compensates by enumerating all returned fields (number, title, state, etc.), which clarifies the output structure. However, it omits error behavior (e.g., issue not found), authentication requirements, or rate limiting details.

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?

Four tightly constructed sentences with zero redundancy: usage context, return payload, requirements, and sibling references. Information is front-loaded and every clause earns its place.

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 lack of output schema, the description adequately compensates by listing all returned fields. Minor deduction for mentioning 'linked PRs' in the usage sentence without explicitly confirming them in the return field list (though they may be implied in the context).

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 description coverage is 100%, establishing a baseline of 3. The description notes that owner, name, and issue_iid are required but adds no semantic meaning beyond what the schema already provides (e.g., no format guidance or examples for issue_iid).

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 identifies the resource (issue) and scope (full context including labels, assignees, bounties). It distinguishes from siblings via the 'See also' reference to list_issues and by emphasizing 'full issue context' versus listing operations.

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?

Explicitly states when to use ('when you need full issue context before working on it') and names three specific alternatives (list_issues, comment_on_issue, update_issue), clearly establishing this tool's niche for detailed retrieval versus listing or modification.

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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