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find_asyncapis

AsyncAPI (event-driven) specifications across the catalog. Event/streaming APIs. Filter by q / tags / providers; include=["content"] inlines bodies. Use find_artifacts for cross-type search.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoFree text over name + description.
pageNo
tagsNoTag slugs.
limitNo
matchNoany
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.
includeNo
versionNoAsyncAPI spec version, e.g. 2.6.0 or 3.0.0.
providersNo

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations provided, the description carries full behavioral disclosure burden. It mentions key behaviors like filtering by q/tags/providers and that include=["content"] inlines bodies, but does not disclose pagination behavior, response format, default match logic, or other operational details. Some transparency but incomplete.

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 concise sentences, front-loaded with the resource type and purpose, then filters and alternative. No waste, every phrase earns its place.

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?

Despite the tool having 9 parameters and no annotations or output schema, the description covers only the core filter options and one behavioral detail (include). It omits pagination, match semantics, version usage, and expected response structure, leaving the agent under-informed for a fairly complex find tool.

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 low (44%), so the description must compensate. It adds meaning for the include parameter (inlines bodies) not present in the schema, and reiterates q/tags/providers, but leaves many parameters (page, limit, match, context) undescribed in both schema and description. Partial compensation for the gaps.

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 finds AsyncAPI (event-driven) specifications, specifies the resource type and scope, and distinguishes it from find_artifacts by noting that find_artifacts is for cross-type search. This is a specific verb+resource with sibling differentiation.

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 explicitly names find_artifacts as an alternative for cross-type search, giving the agent a clear condition for when to use this tool vs. another. It implies this tool is only for AsyncAPI spec type, providing basic routing 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

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