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apis-io

by io.apis

get_region

One region: metadata + a top sample of its member providers (ranked, with the total). Use find_providers?region=slug for the full list, or view=full here. Results carry next: the sub-resources that exist for this entity and the exact tool call that retrieves each, computed from this record. Pass include_next=false to omit it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYes
viewNosummary (default) returns lean discovery records + *_count for dropped sections; full returns the whole record (use get_api / get_provider for one entity).summary
limitNoTop members to show.
contextNoOptional: 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.
include_nextNoSet false to omit the `next` affordance block.

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden and does so well: it discloses the result shape (sample, ranked, with total), the dynamic `next` affordance computed from the record, and how to suppress it. It falls short only in not describing error behavior or the exact composition of 'metadata,' but the core runtime behavior is visible.

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?

Four sentences, each carrying a distinct payload: core purpose, sibling routing, `next` behavior, and the omit flag. It is front-loaded with the primary purpose and contains no filler.

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 5 parameters, no annotations, and no output schema, the description covers the essential invocation concerns: what the result is, where the full list lives, what `next` does and how to disable it. The schema covers parameter specifics, so nothing critical is missing for a competent agent to call this correctly.

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 80%, so the schema already documents view, limit, context, and include_next semantics. The description mostly reiterates those (view=full, include_next=false) rather than adding new parameter detail, so it earns the baseline 3.

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 states a specific verb+resource: 'One region: metadata + a top sample of its member providers (ranked, with the total).' It distinguishes the tool from find_providers by explicitly routing full-list requests to that sibling, and the get_region_leaders sibling is differentiated by the 'top sample' framing.

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?

It gives explicit when-to-use guidance: 'Use find_providers?region=slug for the full list, or view=full here.' This directly resolves the most likely ambiguity for an agent choosing between a single-region summary and a full provider list. It also tells the agent when to set include_next=false.

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

B3.1/5.0
Disambiguation3/5

Most tools are clearly separated by artifact type or resource (find_mcp vs find_openapi vs get_provider vs get_api), but the sheer volume creates some genuinely confusable clusters: apis_io_search vs find_apis vs find_artifacts, and insights_adoption vs insights_dimensions vs find_company_insights. Several readiness-related tools (what_can_i_fix, simulate_fixes, readiness_gates) also share a conceptual boundary, though their descriptions do help.

Naming Consistency3/5

The dominant patterns (find_*, get_*, cohort_*, compare_*) are consistent and predictable, but the set mixes in irregular names like apis_io_search, tag_group_tags, what_can_i_fix, whats_changed, and resolve. These deviations are readable but break the otherwise regular verb_noun convention.

Tool Count2/5

106 tools is far beyond the typical well-scoped server and will impose a heavy selection burden on agents. The server covers a genuinely broad domain (catalog search, ratings, cohorts, agent readiness, lists, exports, feedback), so the count is defensible in scope, but it is still too many to navigate efficiently.

Completeness5/5

The surface is remarkably complete: search and browse, single-entity detail, comparisons, cohort analytics, agent-readiness assessment, saved searches, list management, feedback/correction flows, and full dataset exports are all covered. There are no obvious dead ends, and even minor operations like re-running saved searches or simulating fixes are present.

Resources