OpenCollab MCP

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

Annotations already provide readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true, covering safety and idempotency. The description adds context about what gets scored (profile completeness, coding activity, language diversity) and that it provides personalized tips, which is useful behavioral detail beyond annotations. No contradictions with annotations.

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 efficiently structured in two sentences: the first states the core purpose, and the second elaborates on scoring dimensions and outputs. Every sentence adds value with no wasted words, making it appropriately sized and front-loaded.

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 (scoring readiness with personalized tips), annotations cover safety aspects, and an output schema exists (so return values needn't be described), the description is largely complete. It could benefit from more explicit differentiation from siblings, but it adequately conveys the tool's function and scope.

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%, with only one parameter ('username') documented in the schema without a description. The description doesn't explicitly mention parameters, but it implies the input is a GitHub user ('Rate how ready a GitHub user is'), which aligns with the username parameter. Since there's only one parameter and the description contextually covers it, this compensates well for the low schema coverage.

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: 'Rate how ready a GitHub user is for open source contributions' with specific scoring dimensions (profile completeness, coding activity, language diversity) and outputs (personalized tips). It distinguishes from siblings like 'opencollab_analyze_profile' by focusing on readiness scoring rather than general analysis, though it doesn't explicitly name alternatives.

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 implies usage context ('before contributing') but doesn't explicitly state when to use this tool versus alternatives like 'opencollab_contribution_readiness' or 'opencollab_analyze_profile'. No exclusions or prerequisites are mentioned, leaving usage guidance at an implied level.

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