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by io.apis
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request_check

INFLUENCE — ask APIs.io to (re)check something. Use it when a listing is wrong or stale, when a score looks incorrect, or to get a company profiled that is not in the catalog yet. A check can target a PROVIDER (the default) or a slice of the catalog: an industry, a tag, an area, or a company's estate — for an industry roster missing an obvious member, a tag that has drifted, or an area whose ranking looks wrong. This does NOT score anything on the spot: a check means re-running the enrichment pipeline against the live surface, which a person does by hand. You get a request id back immediately; poll check_status with it, and if you supply a contact email you are notified when the status changes. A slug we do not already hold is never refused — for ANY target type it is queued as a request to ADD that thing, whether that is a company nobody has catalogued, a new industry, or an estate nobody here has thought of. Near matches come back alongside it in did_you_mean, so a typo is visible without the request being dropped. Priced B4 (human work) — included in Influence; otherwise $99.00 as a one-off with its own receipt, never from a prepaid balance. If this is your own company and our data about it is wrong, report_correction is free. See apis://prices.

Input Schema

NameRequiredDescriptionDefault
urlNoThe company or developer-portal URL — use this when there is no listing yet. Providers only; a url cannot name an industry.
kindNorecheck an existing listing, profile a new company, or correct a specific fact.
slugNoThe target slug — a provider (e.g. stripe), or an industry/tag/area/estate slug when target_type says so.
notesNoWhat is wrong, or what to look at. The more specific, the faster it is worked.
contactNoEmail to notify when the status changes. Optional; without it there is nothing to notify, so keep the id.
contextNoOptional: one sentence on why you are asking. Never used to rank; read only if a result is wrong.
target_typeNoWhat `slug` names. Defaults to provider. `estate` is named for the company the estate roots at (e.g. cisco).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / context / description
      Previous value: -"Optional: why you are asking. One sentence — the task you are trying to complete, or what you expect to get back. Never included in the answer and never used to rank; it is read only when a result turns out to be wrong, which is when knowing the intent is what makes the report actionable."New value: +"Optional: one sentence on why you are asking. Never used to rank; read only if a result is wrong."
  2. Changed3 schema fields changed
    • changedInput schema / properties / slug / description
      Previous value: -"apis.io provider slug, if it is already listed (e.g. stripe)."New value: +"The target slug — a provider (e.g. stripe), or an industry/tag/area/estate slug when target_type says so."
    • addedInput schema / properties / target_type
      Added value: +{
+  "description": "What `slug` names. Defaults to provider. `estate` is named for the company the estate roots at (e.g. cisco).",
+  "enum": [
+    "provider",
+    "industry",
+    "tag",
+    "area",
+    "estate"
+  ],
+  "type": "string"
+}
    • changedInput schema / properties / url / description
      Previous value: -"The company or developer-portal URL — use this when there is no listing yet."New value: +"The company or developer-portal URL — use this when there is no listing yet. Providers only; a url cannot name an industry."
  3. Added

TDQS

A4.8/5.0
Behavior5/5

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

Goes well beyond the annotations: it clarifies that no scoring happens on the spot (human-run pipeline), returns a request id for polling via check_status, supports email notification, never refuses unknown slugs (queues an ADD), surfaces did_you_mean on typos, and documents pricing (B4/$99) and that it never draws from a prepaid balance. Annotations supply only the safety triad, so this added operational detail is high value.

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?

Purpose and target semantics are front-loaded, and every sentence carries operational detail. It is long (roughly ten sentences) and the pricing/notification clauses could be tightened, but almost none of it is filler given the absence of an output schema.

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

Completeness5/5

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

With no output schema and 7 optional parameters, the description compensates by describing what comes back (request id, did_you_mean), how to follow up (check_status, contact email), and the cost model. An agent has everything needed to call it and handle the result.

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

Parameters4/5

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

Schema coverage is already 100%, so the baseline is 3, but the description adds real meaning: url is provider-only and cannot name an industry, slug is interpreted according to target_type, target_type defaults to provider, and estate is named for the rooting company. This effectively disambiguates the enum interplay between slug and target_type.

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?

Starts with a specific verb+resource ('ask APIs.io to (re)check something') and immediately enumerates the concrete cases (wrong/stale listing, incorrect score, uncatalogued company). It is clearly separable from siblings like report_correction and claim_listing, which are named or implicitly contrasted.

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

Usage Guidelines5/5

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

Explicitly states when to use it, gives the target taxonomy (provider by default, or industry/tag/area/estate), and routes the 'my own company is wrong' case to report_correction as a free alternative. This is close to a decision rule, not just context.

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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