OSINT MCP Server

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the data source ('Apollo.io') but doesn't describe key behaviors such as rate limits, authentication requirements, pagination, error handling, or what the output looks like. For a tool with no annotation coverage, this leaves significant gaps in understanding how it operates.

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 and front-loaded: the first sentence states the purpose clearly, followed by a concise parameter list. There's no wasted text, and the structure is easy to parse. It could be slightly improved by integrating parameter explanations more seamlessly, but overall it's efficient.

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 that there's an output schema (which covers return values), no annotations, and 0% schema description coverage, the description is moderately complete. It explains the purpose and parameters but lacks behavioral context and usage guidelines. For a tool with four parameters and no annotations, it should do more to compensate, but the output schema helps mitigate some gaps.

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%, so the description must compensate. It lists and briefly explains all four parameters ('organization', 'domain', 'titles', 'limit'), adding meaning beyond the bare schema. However, it doesn't provide details on parameter interactions (e.g., if both 'organization' and 'domain' are required), formats, or constraints, leaving some ambiguity.

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: 'Find people at a company using Apollo.io.' It specifies the verb ('Find'), resource ('people at a company'), and data source ('Apollo.io'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'osint_person_enrich' or 'osint_linkedin_find', which might have overlapping functionality.

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context for usage, or comparisons to sibling tools like 'osint_company_enrich' or 'osint_person_research'. The agent must infer usage from the purpose alone, which is insufficient for optimal tool selection.

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