ICP Pre-Qualification (Pre-Enrichment Filter)

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

The description discloses that the tool uses only locally-available signals (no external API calls), explains mutation behavior with auto_disqualify, and specifies return values (counts, reasons, credit savings). Annotations already indicate readOnlyHint=false and idempotentHint=true, and the description complements these without contradiction.

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 a concise 6-sentence paragraph with no redundancy. It progresses logically: purpose, behavioral notes, usage example, return info. Every sentence adds value.

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?

The description covers key aspects: purpose, behavior, usage with siblings, and returns. However, it lacks details on the exact return structure and estimation method for credit savings. Given the complexity of nested criteria, these minor gaps prevent a perfect score.

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?

With 100% schema coverage, baseline is 3. The description adds value by explaining the AND logic for criteria and the use of required_tech_stack with Detecto. It provides context beyond schema descriptions, justifying a 4.

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 explicitly states it filters leads against an Ideal Customer Profile before enrichment, providing a specific verb+resource+scope. It distinguishes from sibling tools like lead_enrich and lead_score by emphasizing pre-enrichment filtering and saving credits.

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 clear when-to-use guidance (before enrichment), explains the auto_disqualify behavior, and suggests chaining with Detecto's detect_platform. It also clarifies default behavior when lead_ids is omitted, effectively covering usage context.

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