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a2a_call_agent

Call any public A2A-compatible agent directly by its endpoint URL.

Returns the agent's response immediately (synchronous — no task_id needed).
Get agent_url values from discover_agents (look for ENDPOINT in results).
Works with any agent on a2aregistry.org or any A2A JSON-RPC endpoint.
Free, no login required.

Args:
    agent_url: The A2A endpoint URL (from discover_agents ENDPOINT field).
    message: The message or task to send to the agent.
    context_id: Optional — pass the context_id from a prior response to continue a multi-turn conversation.
    timeout_seconds: Seconds to wait for a response (default 30, max 120).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
messageYes
agent_urlYes
context_idNo
timeout_secondsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden and does well. It discloses synchronous behavior ('Returns the agent's response immediately'), mentions no login required, and includes timeout handling. It doesn't cover potential errors or rate limits, but for a free public tool, the key behaviors are transparent.

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 front-loaded with the core purpose, then behavior, then sourcing, then free/no-login, then parameter arguments. Each sentence adds value, and the structure is logical and scannable. It's appropriately sized for the tool's complexity.

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

Completeness5/5

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

Given the tool's moderate complexity, the description covers everything an agent needs: how to obtain the URL, what to send, optional context continuation, timeout settings, and free access. The output schema handles return value explanations, so the description is complete for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate, and it excels. Every parameter is explained: agent_url (from discover_agents ENDPOINT field), message (message or task), context_id (optional, for multi-turn), and timeout_seconds (default 30, max 120). This fully compensates for the lack of schema descriptions.

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's purpose: 'Call any public A2A-compatible agent directly by its endpoint URL.' It uses a specific verb (call) and resource (agent), and distinguishes itself from siblings like discover_agents (which finds endpoints) and other agent tools. The scope is well defined.

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 provides practical guidance: 'Get agent_url values from discover_agents (look for ENDPOINT in results),' and notes it works with any agent on a2aregistry.org or any A2A JSON-RPC endpoint. It also mentions it's synchronous with no task_id, implying when to use it vs async tools, though it doesn't explicitly state when not to use alternatives.

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

C2.7/5.0
Disambiguation3/5

Several tools overlap in purpose, particularly the research/analysis agents (constructivecritic, firstprinciplesanalyst, scientificresearchagent, researchagent) and the three reasoningdelegation agents, which differ only by effort level. Some tools like 'exploitagent' and 'testagent' have vague descriptions that don't clarify distinct roles. However, many tools are clearly distinct (e.g., campbuddy vs. smart_fridge___nutrition), and the core router tools (discover_agents, a2a_call_agent, wait_for_task) are well-defined.

Naming Consistency2/5

Naming is inconsistent: some tools use snake_case (a2a_call_agent, discover_agents, wait_for_task) while most others are camelCase or concatenated lowercase (browsernavigationagent, campbuddy, reasoningdelegationhigh). There's also odd naming like 'smart_fridge___nutrition' with triple underscore, and simple names like 'testagent' and 'exploitagent'. No consistent convention exists across the set.

Tool Count4/5

With 24 tools, this is near the upper limit but still reasonable for an agent router that hosts many pre-defined specialized agents. The core router functions (discover, call, wait) are supplemented by a diverse set of agent tools. It's borderline heavy but each tool represents a distinct agent or action, so it's acceptable.

Completeness4/5

The router functionality is well-covered: discovery (discover_agents), synchronous calling (a2a_call_agent), asynchronous handling (wait_for_task), and skill lookup (search_skills/get_skill) for extension. Missing are explicit cancellation or task management tools, but core workflows are supported. The presence of domain-specific agents (campbuddy, silpo_home_restaurant) doesn't detract from router completeness.

Resources