Enrich Person (Apollo)

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

Beyond annotations (readOnlyHint, idempotentHint), the description discloses critical behaviors: credit consumption per enrichment, extra cost per email/phone reveal, async phone delivery via webhookUrl, GDPR restrictions on personal emails, and the user's responsibility as data controller. This adds substantial value beyond the annotation hints.

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 entire description is a single, dense paragraph that front-loads the purpose, then efficiently covers key behaviors in separate sentences. No redundant information; every sentence adds value. The structure uses capitalization and punctuation effectively to highlight important warnings.

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 13 parameters and no output schema, the description comprehensively addresses credit usage, async phone retrieval, and GDPR concerns. It lacks specifics on the return format (e.g., what fields the profile contains) but the tool's purpose of returning 'full profile' is clear. The description is thorough enough for an AI agent to handle common scenarios.

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 coverage is low (38%), and while the description explains revealPhoneNumber, webhookUrl, and their credit implications, it does not detail most parameters (name, email, domain, etc.). The meaning of these is inferable from context but not explicitly stated, leaving a gap in parameter understanding.

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 core action: 'Match one person via Apollo and return their full profile (employment history, employer, departments, seniority).' The verb 'match' and 'return' paired with the resource 'person profile' precisely defines the purpose, distinguishing it from search tools (apollo_people_search) that list many results.

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 notes credit consumption and extra costs for reveal options, implicitly guiding when to use (when a full profile is needed) and cautioning about cost. It does not explicitly list alternatives or when not to use, but the context of credit consumption and async phone delivery provides practical guidance.

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