Lead Enrichment API

search_leads

Search enriched B2B leads by ICP criteria.

Returns scored companies with firmographics, tech stack signals, and buying signals.
Each lead returned counts against the monthly quota.

Args:
    industries: Filter by industry — AI, Blockchain, Fintech, Security, Healthcare, DevTools, Other
    stages: Funding stage — Pre-seed, Seed, Series A, Series B, Series C+, Public, Unknown
    regions: EU, US, APAC, MENA, Other
    min_icp_score: 0-100, minimum ICP fit score
    min_buying_intent: 0-100, minimum buying intent score
    tech_stack_contains: must match at least one signal
    max_age_days: only leads enriched within N days (1-365)
    limit: leads per response (1-100)
    sort_by: icp_score, buying_intent, employees, or enriched_at

Input Schema

TableJSON Schema

Name	Required	Default
`limit`	No
`stages`	No
`regions`	No
`sort_by`	No	icp_score
`industries`	No
`max_age_days`	No
`min_icp_score`	No
`min_buying_intent`	No
`tech_stack_contains`	No

TDQS

A3.9/5.0

Behavior3/5

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

No annotations are provided, so the description carries the full burden. It does disclose a meaningful behavioral trait ('Each lead returned counts against the monthly quota') and indicates the return type (scored companies with firmographics, tech stack signals, buying signals). However, it does not mention permissions, rate limits, error cases, or whether the operation is read-only beyond the verb 'Search'.

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

Conciseness5/5

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

The description is efficient and well-structured: a one-line purpose, two sentences on returns and quota, then a compact Args list. Every sentence adds value, and the parameter documentation is organized and scannable.

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

Completeness4/5

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

For a tool with no output schema and 9 flexible filter parameters, the description covers the high-level return content and quota impact, plus detailed parameter semantics. However, it lacks specifics about the response shape, pagination, or any error/failure modes, which would make it fully complete.

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

Parameters5/5

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

The schema has 0% description coverage, but the tool description compensates thoroughly by explaining each parameter with allowed values and semantics. For example, 'min_icp_score: 0-100, minimum ICP fit score' and 'max_age_days: only leads enriched within N days (1-365)' provide meaning far beyond the bare schema definitions.

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 'Search enriched B2B leads by ICP criteria', identifying both the action (search) and the resource (enriched B2B leads). It is specific enough to distinguish from the sibling tools (get_usage, validate_lead), though it does not explicitly call out those alternatives.

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

Usage Guidelines3/5

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

The description implies when to use the tool (when searching for B2B leads based on ICP criteria) but provides no explicit guidance about when not to use it or which sibling tool to choose instead. There is no exclusion or alternative recommendation, so it meets an 'implied usage' standard.

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

All Lead Enrichment API tools Inspect

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TDQS

A4/5.0

Disambiguation5/5

Each tool serves a distinct purpose: quota tracking, lead searching, and lead validation. There is no functional overlap, and descriptions clearly differentiate them.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern (get_usage, search_leads, validate_lead), making the API intuitive and predictable.

Tool Count5/5

Three tools is a well-scoped set for a focused lead enrichment API, covering essential operations (check usage, search, validate) without unnecessary bloat.

Completeness4/5

The surface covers core enrichment workflows (search, validate, usage). A potential minor gap is the lack of a dedicated tool to retrieve full details for a single lead by ID, but validate_lead partially addresses this.

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