Company Intelligence Tools — Zinin M2M Hub

Competitor Change Rollup

competitor-change-rollup

One card per competitor summarising what changed across several signals in the past week. Partial cards are marked partial and list which signals are missing. — $0.08/call, x402 (USDC on base).

Input Schema

TableJSON Schema

Name	Required	Description
`domain`	Yes	The competitor's domain to watch, e.g. "stripe.com".
`baseline_key`	No	A name for this watch, in case you want to run more than one watch on the same domain with different settings. Defaults to the domain itself.
`role_keywords`	No	Highlight when this competitor is hiring for roles matching these words (passed to our company-hiring-radar Actor).
`company_name_override`	No	By default this Actor guesses the company's ATS token / name from the domain itself (e.g. "stripe.com" -> "stripe") for the hiring and funding checks — this is a best-effort heuristic, not a verified identity, and CAN be wrong (see README). Set this if you know the real ATS token or legal name.

TDQS

A4.3/5.0

Behavior5/5

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

The description adds meaningful behavior beyond annotations: it discloses the cost ($0.08/call), the partial-card behavior, and the listing of missing signals. This is valuable operational context that annotations do not provide.

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?

Two sentences, front-loaded with purpose, and includes pricing in the second sentence. Every clause earns its place with no fluff.

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?

The description mentions 'several signals' but does not enumerate them or explain what 'changed' means in the output. Since there is no output schema, the description should compensate more, especially because the schema hints at hiring/funding signals that are not described. The tool's composition behavior is left implicit.

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%, and the schema itself contains detailed parameter descriptions (e.g., domain, baseline_key, role_keywords, company_name_override). The description does not add parameter-level meaning, so a baseline 3 is appropriate.

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's verb ('summarising') and resource ('what changed across several signals in the past week'). The phrase 'One card per competitor' distinguishes it from sibling tools like counterparty-risk-rollup, which targets risk, not general competitor changes.

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?

It provides a clear usage context: weekly competitor monitoring (past week). However, it does not explicitly state when not to use it or point to alternatives, so it stops short of a 5.

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

A4/5.0

Disambiguation4/5

Most tools have clearly distinct purposes, but some overlap exists between company-lookup and company-registry-enricher, and between individual signal tools and composite rollups. The descriptive names help differentiate, but the boundary between one-off screenings and alert/rollup tools requires careful reading.

Naming Consistency4/5

Tool names follow a consistent pattern of hyphenated lowercase nouns (e.g., company-lookup, funding-alert, sanctions-screening). The one exception, pricing_info, uses an underscore, creating a minor deviation from the otherwise uniform naming style.

Tool Count4/5

With 20 tools, the server is on the higher end of typical scope but justified for a comprehensive company intelligence bundle. Each tool covers a distinct or complementary aspect of company research, so the count feels purposeful rather than bloated.

Completeness5/5

The toolset covers company lookup, registry, hiring, funding, sanctions, litigation, patents, contacts, new company detection, and email verification—a broad and well-rounded surface for due diligence and sales intelligence. Composite tools like intent-signal-aggregator and lead-list-qualifier tie these together effectively, leaving no major dead ends.

Resources

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