OpenCollab MCP

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

The description adds valuable behavioral context beyond annotations: it specifies that it 'detects the user's primary language' and 'returns 10 matching good-first-issues', which are not covered by annotations. Annotations already provide safety hints (readOnly, non-destructive, idempotent, openWorld), so the bar is lower. The description doesn't contradict annotations and adds useful operational details.

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

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

The description is appropriately sized with two sentences: the first states the core functionality, and the second adds specific behavioral details. Every sentence earns its place by providing essential information without redundancy. It's front-loaded with the main purpose and efficiently structured.

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

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

Given the tool's moderate complexity (profile analysis + issue matching), rich annotations (readOnly, idempotent, etc.), and the presence of an output schema, the description is complete enough. It covers the purpose, usage context, and key behavioral traits (language detection, 10 issues). The output schema handles return values, so the description doesn't need to explain them.

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

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

Schema description coverage is 0% (the parameter 'username' has only basic validation in schema). The description doesn't mention the parameter at all, failing to compensate for the lack of schema documentation. However, with only 1 parameter, the baseline is 4, but the description provides no parameter information, so it scores lower. It implies the tool takes a GitHub username but doesn't explicitly state it.

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

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 ('analyze a GitHub profile' and 'find issues matched to that user's top skills') and resources ('GitHub profile', 'issues'). It distinguishes from siblings like 'opencollab_analyze_profile' (which only analyzes) and 'opencollab_find_issues' (which finds issues without profile analysis) by combining both functions in one step.

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

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

The description explicitly states when to use this tool: for analyzing a GitHub profile and instantly finding matched issues in one step. It implies when not to use it (e.g., if you only need analysis without issue matching, use 'opencollab_analyze_profile'; if you need issue finding without profile analysis, use 'opencollab_find_issues'). The 'All-in-one' phrasing highlights its integrated nature versus alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.