Skip to main content
Glama

Ask the A2A agent

ask_agent
Read-only

Send a message to an A2A agent and get its reply with structured details (tool calls, citations, follow-ups). Preserves multi-turn context automatically; set new_conversation to start over.

Instructions

Send a message to the A2A agent 'the A2A agent' and get its reply. If the agent calls its own internal tools while answering, those calls are reported alongside the answer. Multi-turn context is preserved automatically across calls; set new_conversation=true to start over. Tool-using turns can take 15-60s. Also returns structured content: answer, tool_calls[{tool,text,parallel,at}], citations, followups, data, partial, context_id, turn, elapsed_ms.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesThe message / question to send to the agent.
timeout_msNoOverride the upstream request timeout (default A2A_TIMEOUT_MS, 180000).
include_historyNoReplay prior turns as context (default true).
new_conversationNoDiscard prior context and start a fresh conversation.
include_followupsNoAppend the agent's suggested follow-up questions (default true).
include_tool_callsNoAppend the agent's internal tool-call trace to the reply text (default true). The trace is always available in structured output and via get_last_trace.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv3.0.0

TDQS

A3.7/5.0
Behavior1/5

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

The description explicitly says multi-turn context is preserved automatically across calls and that new_conversation=true discards prior context, implying the tool mutates conversation state. This contradicts the readOnlyHint=true annotation, which declares no side effects. The additional latency and structured-output details are useful, but the contradiction is a serious inconsistency.

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?

The description is five sentences long, purpose-first, and each sentence adds behavior, state, latency, or output details. There is slight redundancy between the tool-call mention and the structured output list, but no filler.

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?

For a 6-parameter tool with no output schema, the description covers the operation, state semantics, latency, and return fields. However, the contradiction with readOnlyHint=true leaves the agent with mixed signals about whether the tool has side effects, so it is not fully complete.

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?

Schema description coverage is 100%, so the baseline is 3. The description adds semantic value by explaining the effect of new_conversation=true and linking the 15-60s tool-using duration to timeout considerations. It does not merely repeat the schema's parameter 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 opens with a specific action and resource: 'Send a message to the A2A agent ... and get its reply.' This clearly distinguishes it from siblings like get_last_trace, get_agent_card, and reset_conversation, which are retrieval or reset tools.

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 gives clear context for multi-turn behavior: context is preserved automatically, and new_conversation=true starts over, which tells the agent when to use that parameter. It also warns that tool-using turns can take 15-60s, setting timeout expectations. It does not explicitly route to sibling tools like get_last_trace, but the core usage guidance is present.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.