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prospect_iq

Analyze sales prospects by scoring web presence, tech stack, and contact readiness across 7 data sources to identify qualified leads.

Instructions

Sales intelligence: web presence, tech stack, social signals, contact readiness. 7 data sources scored 0-100. Price: $0.40 USDC on Base.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYesDomain to analyze (e.g. example.com)
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: it aggregates data from '7 data sources', provides scores '0-100', and has a cost ('Price: $0.40 USDC on Base'). However, it doesn't mention rate limits, authentication needs, error handling, or what happens with invalid domains, leaving gaps for a tool with financial implications.

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

Conciseness4/5

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

The description is appropriately sized and front-loaded with the core purpose ('Sales intelligence'). The second sentence adds useful details (data sources, scoring, price) without redundancy. However, the price information could be more integrated with the purpose, and there's minor room to tighten phrasing.

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

Completeness3/5

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

Given the tool's complexity (sales intelligence with scoring and cost), no annotations, and no output schema, the description is moderately complete. It covers the purpose, data sources, scoring, and cost, but lacks details on output format, error cases, or performance characteristics, which are important for a paid tool with no structured output documentation.

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

Parameters3/5

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

The input schema has 100% description coverage, with the single parameter 'domain' well-documented. The description doesn't add any parameter-specific information beyond what the schema provides (e.g., no examples of valid domains beyond the schema's 'e.g. example.com'), so it meets the baseline of 3 for high schema coverage without compensating value.

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

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool performs 'Sales intelligence' with specific capabilities: analyzing web presence, tech stack, social signals, and contact readiness. It provides a specific verb ('Sales intelligence') and resource (domain analysis), though it doesn't explicitly differentiate from sibling tools like 'company_xray' or 'domain_shield' which might have overlapping domains.

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

Usage Guidelines2/5

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

The description mentions 'Sales intelligence' which implies usage in sales contexts, but provides no explicit guidance on when to use this tool versus alternatives like 'company_xray' or 'domain_shield'. There are no when/when-not statements or named alternatives, leaving the agent to infer usage from the general domain.

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

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