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find_apis

Paginated, sortable list of APIs across providers — filter by tag, provider, artifact type, industry, region, or rating band. Use apis_io_search first for a cross-type overview.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoFree text over name + description.
areaNo
bandNoRating bands: exemplar, strong, developing, thin, minimal.
pageNo
sortNoOrder results. Default: relevance with a query, composite (quality) when browsing. `demand` = Fortune-1000 adoption, scoped to the query.
tagsNoTag slugs.
viewNosummary (default) returns lean discovery records + *_count for dropped sections; full returns the whole record (use get_api / get_provider for one entity).summary
limitNo
matchNoany
fieldsNoReturn exactly these top-level keys (overrides view).
publicNoOnly providers callable publicly with no signup (onboarding=open). (providers only)
regionNo
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.
pricingNoAccess model — pricing: free, freemium, free-trial, paid, enterprise. (providers only)
try_nowNoOnly providers a developer can start using at no cost right now (free/trial + self-serve/open). (providers only)
industryNo
min_scoreNo
providersNo
onboardingNoAccess model — how to start: open (no key), self-serve, approval. (providers only)
artifact_typesNo

TDQS

A3.6/5.0
Behavior2/5

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

No annotations are present, so the description must carry the full burden of behavioral disclosure. It only mentions pagination and sortability, but does not state that the operation is read-only, how filters combine (match any/all is in schema but not explained), what happens on empty results, or response structure. The behavioral traits are minimal and rely heavily on the schema.

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 with zero filler. The purpose is front-loaded (paginated, sortable list, filters), and the routing advice is placed at the end. Every sentence earns its place, and the description is appropriately sized for a complex tool.

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

Completeness2/5

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

For a tool with 20 parameters, no output schema, and no annotations, the description is too thin. It doesn't mention pagination mechanics (page/limit), that some filters are provider-only, what 'view' or 'fields' do, or return format. It leaves several parameters unexplained and provides only a high-level overview plus a sibling routing note.

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 55%, so the description should partially compensate. It does summarize primary filter categories, which maps to parameters like tags, providers, artifact_types, industry, region, and band, adding a high-level grouping. However, it does not explain undocumented parameters such as area, min_score, context, or provider-only flags. This is adequate but not comprehensive.

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 and resource: 'Paginated, sortable list of APIs across providers'. It lists distinctive filters (tag, provider, artifact type, industry, region, rating band) that differentiate it from sibling find_* tools. The reference to apis_io_search as a cross-type alternative explicitly distinguishes it from that sibling, so an agent can tell them apart.

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 instruction 'Use apis_io_search first for a cross-type overview' gives a clear condition for selecting an alternative tool. It implies that this tool is for API-specific searches. However, it doesn't explicitly mention when to use this tool versus other find_* tools (e.g., find_providers) beyond the one contrast, so it's clear but not exhaustive.

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