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AgentCV

List AgentCV platform hubs

list_platforms
Read-onlyIdempotent

The platform hubs of agentcv.ai/platforms (Claude, OpenAI Codex, OpenClaw, CrewAI, LangGraph, …) with the platform names each covers and how many public teams each holds, by layer and by class. AgentCV is independent and not affiliated with any platform. Read-only.

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
noteYes
platformsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint=false, so the safety profile is covered and the trailing 'Read-only.' is redundant. The description does add useful behavioral context: this is a curated, fixed catalog of external platform hubs rather than user-generated data, plus an independence disclaimer. It says nothing about result size, ordering, or caching, so the value added is modest.

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?

Two sentences, resource named first, with the payload described immediately after. The independence/trademark disclaimer is defensible but is the one element that doesn't help an agent decide or invoke; everything else earns its place.

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?

A zero-parameter, read-only listing tool with an output schema, so return-format detail is not required. The description covers scope and payload adequately. The only gap is workflow placement relative to search_teams and get_team, which matters because all five siblings operate over adjacent data.

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?

The tool takes zero parameters and the description correctly introduces no parameter discussion. There is no schema surface for the description to explain beyond the grouping dimensions it mentions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names the concrete resource (the platform hubs of agentcv.ai/platforms) and enumerates the payload: platform names covered and public team counts, broken down by layer and class. Examples (Claude, OpenAI Codex, OpenClaw, CrewAI, LangGraph) make the scope unmistakable. It stops short of explicitly contrasting itself with siblings like search_teams, which keeps it from a 5.

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

Usage Guidelines2/5

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

There is no when-to-use guidance, no stated relationship to sibling tools such as search_teams or list_use_cases, and no indication that this is a discovery entry point that feeds later filtered queries. The agent must infer the tool's role in a workflow from the resource description alone.

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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