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taken

by RogueAlg0
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check_issue

Check whether a GitHub issue is already taken before volunteering. Analyzes linked PRs, assignees, claimant comments, and repo signals to return GO, TAKEN, or CAUTION.

Instructions

Check whether a GitHub issue is already taken.

Verdicts: GO (free to volunteer), TAKEN (spoken for: closed, open PR, or assignee), CAUTION (soft signal: someone expressed interest, the repo bans AI contributions, or the repo looks stale).

The payload also carries friendly_labels (first-time-contributor labels on the issue) and welcoming (repo-level signs contributions are welcome), the same markers scan_repo returns.

Args: owner: repository owner login repo: repository name issue_number: issue number to check me: your GitHub login; your own comments are ignored in the claimant scan graphql: use the GraphQL fetch path (subprocess) instead of REST persistent_session: use the persistent-session GraphQL path instead of REST

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
meNo
repoYes
ownerYes
graphqlNoFetch via one GraphQL query (gh api graphql) instead of REST. Opt-in.
issue_numberYes
persistent_sessionNoGraphQL over one persistent HTTPS connection; token from `gh auth token` held in memory only. Opt-in.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.7.2
    • addedInput schema / properties / graphql
      Added value: +{
+  "default": false,
+  "description": "Fetch via one GraphQL query (gh api graphql) instead of REST. Opt-in.",
+  "title": "Graphql",
+  "type": "boolean"
+}
    • addedInput schema / properties / persistent_session
      Added value: +{
+  "default": false,
+  "description": "GraphQL over one persistent HTTPS connection; token from `gh auth token` held in memory only. Opt-in.",
+  "title": "Persistent Session",
+  "type": "boolean"
+}
  2. First observedv0.5.0

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description takes on the full burden and handles it well: it explains verdict categories (GO, TAKEN, CAUTION), what signals produce each verdict, and that the payload includes friendly_labels and welcoming. It also discloses that the agent's own comments are ignored in the claimant scan)Skip: it does not explicitly state that the operation is read-only or describe behavior if the issue does not exist, but the disclosed detail is strong.

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 compact and well structured, starting with the core purpose and verdicts before moving to payload and parameters. Every section earns its place, and the Args block is formatted for quick parsing.

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 absence of annotations and an output schema, the description covers the return payload, verdict logic, and parameter semantics thoroughly. Minor gaps include no explicit read-only confirmation, no error behavior for invalid issue numbers, and no direct routing guidance versus sibling tools.

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

Parameters5/5

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

Schema description coverage is only 33%, and the Args section compensates by defining all six parameters with operational meaning. It adds useful nuance beyond the schema: 'me' influences the claimant scan, 'graphql' changes the fetch mechanism, and 'persistent_session' describes connection reuse and token handling.

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 states a clear verb and object: 'Check whether a GitHub issue is already taken.' It gives distinct verdicts and payload details, so the tool's purpose is specific. It does not explicitly contrast this with the sibling tools scan_repo and discover_candidates, though the single-issue scope implies the difference.

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 usage context is implied: this is a decision-support check for whether an issue is free to volunteer on, and 'same markers scan_repo returns' hints at a relationship with a sibling. However, there is no explicit guidance on when to use this tool versus discover_candidates or scan_repo, nor any exclusions or when-not-to-use conditions.

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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