Company Intelligence Tools — Zinin M2M Hub

Sanctions List Update Alert

sanctions-update-alert

Re-screens a saved watchlist against sanctions lists and returns only the entries whose status changed since the previous check. The first run creates the baseline and says so. — $0.05/call, x402 (USDC on base).

Input Schema

TableJSON Schema

Name	Required	Description
`names`	Yes	Person or company names to watch against the OFAC SDN and EU consolidated sanctions lists, one per row. Every scheduled run re-screens these same names and reports ONLY what changed since a previous run of this watch: a new hit, a hit that disappeared, or an existing hit's score/program/alias shifting.
`minScore`	No	Only consider candidate matches scoring at or above this (0 = everything, 1 = only a full token match). Kept soft on purpose — a missed hit is worse than a false one.
`max_items`	No	Caps how many new-hit / changed-hit rows a single run will deliver and charge for, even if more were found.
`baseline_key`	No	A name for THIS watch, so you can run several independent screening watches from one Actor (e.g. "vendor-list", "new-hires") without one overwriting another's memory of what's already been seen. Each name is scoped to YOUR OWN Apify account. The prefilled value is only there so this Actor's own daily test run has a stable, obviously-a-test name; replace it with your own watch name.

TDQS

A4.4/5.0

Behavior5/5

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

Beyond annotations (readOnly=false, etc.), the description discloses statefulness ('The first run creates the baseline and says so'), the selective return of only changed entries, and pricing ('$0.05/call'). It also clarifies the 'saved watchlist' behavior, which adds meaningful context beyond what annotations convey.

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 and immediately delivers the core function, then adds essential pricing and state nuances. It is front-loaded with the verb and purpose, with zero wasted words.

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?

Given there is no output schema, the description explains the return semantics ('only the entries whose status changed') and the first-run baseline, which covers the essential workflow. However, it does not specify the output structure (e.g., fields like name, score, program) beyond what is implied by the input schema, leaving a minor gap for an agent.

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 input schema already provides rich descriptions for all four parameters. The tool description does not add parameter-level meaning beyond saying 'saved watchlist,' which ties to baseline_key. This meets the baseline for high schema coverage but does not go further.

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 uses a specific verb ('Re-screens') and clearly defines the resource ('a saved watchlist against sanctions lists') and the exact scope ('returns only the entries whose status changed since the previous check'). It also distinguishes itself from the sibling tool 'sanctions-screening' by focusing on change detection rather than initial screening.

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 clearly implies this is for ongoing monitoring, noting the first run creates a baseline and that only changed entries are returned. However, it does not explicitly name alternatives or say 'use this instead of sanctions-screening when you need change alerts,' so it lacks explicit when-not guidance.

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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