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prakhar1605

OpenCollab MCP

by prakhar1605

opencollab_check_issue_availability

Read-onlyIdempotent

Check if a GitHub issue is available for contribution by verifying assignees and linked pull requests.

Instructions

Check if a GitHub issue is still available — no one has claimed it or opened a PR for it.

Checks assignees and linked pull requests to determine availability.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already provide safety and idempotency hints (readOnlyHint: true, destructiveHint: false, idempotentHint: true, openWorldHint: true). The description adds valuable behavioral context beyond annotations: it specifies the availability criteria ('checks assignees and linked pull requests') and clarifies what 'available' means ('no one has claimed it or opened a PR for it'). This enhances transparency without contradicting annotations.

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 appropriately sized and front-loaded: the first sentence states the core purpose, and the second adds critical behavioral details. Both sentences earn their place by providing essential information without redundancy. The structure is efficient and zero-waste.

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?

Given the tool's moderate complexity (checking issue availability), rich annotations (covering safety and idempotency), and the presence of an output schema (which handles return values), the description is complete enough. It explains the tool's purpose, usage context, and behavioral criteria, leaving no significant gaps for the agent to understand its function.

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 0%, meaning parameter descriptions are missing in the schema. The tool description does not mention any parameters or their semantics (owner, repo, issue_number). However, since there is only one parameter (a nested object with three properties), the baseline is 4, but the description fails to compensate for the schema gap, resulting in a score of 3 due to lack of parameter guidance.

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 states the tool's purpose with specific verbs ('check if a GitHub issue is still available') and resources ('GitHub issue'), distinguishing it from siblings like 'opencollab_find_issues' (which finds issues) or 'opencollab_stale_issue_finder' (which finds stale issues). It explicitly defines availability criteria ('no one has claimed it or opened a PR for it'), making the purpose unambiguous.

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

Usage Guidelines4/5

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

The description provides clear context for when to use this tool: to check issue availability based on assignees and linked pull requests. However, it does not explicitly mention when NOT to use it or name specific alternatives among siblings (e.g., 'opencollab_find_issues' for finding issues regardless of availability). The guidance is implicit but sufficient for basic usage.

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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