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by com.readyapis

Company Buyer Signal

company_signal
Read-onlyIdempotent

Composite B2B buyer-signal score (0-100) for a company. Joins curated identity + live SEC EDGAR filings + DNS/DMARC + WHOIS + curated hiring signals into one explainable score tuned by buyer profile (enterprise_sales, smb_sales, investor_research, vendor_diligence). Returns overall score, tier, verdict, six sub-scores with notes, tech-stack hint, and SEC activity summary.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainNoCompany domain (e.g. apple.com). One of domain or ticker is required.
tickerNoStock ticker (e.g. AAPL). Used when domain is not provided.
buyer_profileNoBuyer profile that tunes the sub-score weights.enterprise_sales
include_filingsNoFetch live SEC EDGAR filings (adds ~400ms upstream).

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, covering the safety profile. The description adds context about data sources and the returned fields, but doesn't disclose any extra behavioral traits like rate limits or auth requirements, which would push it higher.

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 two sentences, front-loaded with the main purpose and followed by key details. No wasted words; every clause adds value.

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?

With no output schema, the description explicitly lists all return components (overall score, tier, verdict, sub-scores, tech-stack hint, SEC summary). It also explains the tuning by buyer profile and the optional filings parameter. The description is complete enough for an agent to invoke correctly, though it lacks edge-case or error-handling details.

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?

Schema description coverage is 100%, so the baseline is 3. The description does not add extra meaning beyond the schema; it mentions buyer_profile values and include_filings, but the schema already explains these. No additional parameter semantics are provided.

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

Purpose5/5

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

The description clearly states the tool computes a composite B2B buyer-signal score (0-100) for a company, specifying the data sources (identity, SEC EDGAR, DNS/DMARC, WHOIS, hiring signals) and the output. This distinguishes it from siblings like compliance_signal or company_enrich by focusing on buyer intent.

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

Usage Guidelines4/5

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

The description gives clear context on what the tool is for (buyer signals tuned by buyer_profile) and its output, making it obvious when to use it. However, it does not explicitly exclude alternatives or mention when not to use it, which would be needed for a perfect score.

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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TDQS

B3.2/5.0
Disambiguation2/5

Multiple tools have genuinely blurry boundaries: company_change vs company_changes differ only by singular/plural yet serve different purposes, company_domain vs company_classify vs company_lookup_auto all accept a domain, geo_zip_lookup vs geo_enrich vs geo_zip_batch all return ZIP profiles, and email_validate subsumes much of email_disposable and email_free_provider. The domain prefixes help narrow search space, but within many domains an agent cannot reliably predict which tool is the right one.

Naming Consistency4/5

All 129 tools uniformly follow a snake_case [domain]_[topic] convention (company_, fx_, geo_, dns_, weather_, tax_), which is highly predictable and consistent. Minor deviations include the confusing company_change/company_changes pair, and inconsistent suffix usage (_batch appears on address_validate_batch, company_domains_batch, geo_zip_batch but not on equivalent lookup tools elsewhere).

Tool Count1/5

129 tools far exceeds the 50+ extreem-mismatch threshold, bundling roughly 28 unrelated data domains (weather, fx, tax, ccompany, dns, jobs, flight, email, phone, tax...) into a single MCP surface. Even focusing on one domain forces the agent to load an enormous unrelated tool list; this should be split into many smaller domain-specific servers.

Completeness4/5

Per-domain coverage is impressively thorough: weather spans current/forecast/hourly/historical/normals/marine/route/air-quality, fx covers rates/convert/historical/volatility/correlation/strenth, and company includes lookup/enrichment/networks/timeline/peer-comparison plus six buyer-tuned signals with profile-introspection tools. Minor gaps like flight being historical-only and smtp probes skipping major email providers are documented scope decisions rather than dead ends.

Resources