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find_channels

AsyncAPI event channels across the catalog. Individual event channels (topics/streams). 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
protocolNoAsyncAPI version the channel is defined in.
providersNo

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations provided, the description must carry the behavioral burden. It discloses that results are event channels, that filtering by q/tags/providers works, and that include=['content'] inlines bodies. But it omits pagination behavior, default limits, match semantics, protocol filtering, and response shape, so coverage is only partial.

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 punchy sentences. It front-loads the core purpose and scope, then lists filters and the alternative tool with no filler. Every sentence adds actionable information.

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

Completeness3/5

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

Given 9 parameters, no output schema, and no annotations, the description is insufficiently complete. It clarifies the primary filters and one include option but leaves pagination, match mode, protocol, and result format unexplained. An agent could still call it, but would miss important call options.

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 at 44%, so the description must compensate. It adds meaning for the include parameter ('inlines bodies') and confirms providers is a filter, but it does not explain page, limit, match, or protocol. The description covers some parameters but leaves several undocumented.

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: 'AsyncAPI event channels across the catalog' and clarifies they are individual channels (topics/streams). This clearly distinguishes the tool from broad artifact search and related siblings like find_artifacts, giving the agent an unambiguous selection basis.

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?

It explicitly says 'Use find_artifacts for cross-type search', providing an exclusion for when not to use this tool. It also lists the main filters (q, tags, providers) and the include option, giving clear context for invocation. However, it does not contrast with find_asyncapis or other channel-adjacent tools, so a small gap remains.

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.

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