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call_agent

Get immediate answers from a specialist agent for debugging, UI design, or documentation tasks. Synchronous call returns the response before you continue.

Instructions

Synchronous single agent call (BLOCKING, 30-120s).

⚠️ STOP: Choose the Right Tool First

Decision Tree:

  1. Need to run explore/researcher? → Use call_agent_async (NEVER this tool)

  2. Need multiple agents in parallel? → Use call_agent_async × N, NOT call_agents_batch

  3. Need advisor advice or must verify result immediately? → Use this tool

Why async for search agents?

  • explore/researcher may take 30-120s each

  • Blocking wastes your time waiting

  • Async lets you continue working while agents search

Available Agents

  • advisor: Read-only consultation agent. High-IQ reasoning specialist for debugging hard problems and high-difficulty architecture design.

  • researcher: Specialized codebase understanding agent for multi-repository analysis, searching remote codebases, retrieving official documentation, and finding implementation examples.

  • explore: Contextual grep for codebases. Answers "Where is X?", "Which file has Y?", "Find the code that does Z".

  • frontend-ui-ux-engineer: A designer-turned-developer who crafts stunning UI/UX even without design mockups. Code may be a bit messy, but the visual output is always fire.

  • document-writer: A technical writer who crafts clear, comprehensive documentation. Specializes in README files, API docs, architecture docs, and user guides.

Agent → Tool Mapping

Agent

Tool

Reason

advisor

call_agent

Need result immediately

researcher

call_agent_async

Search task, run in background

explore

call_agent_async

Search task, run in background

frontend-ui-ux-engineer

call_agent

Need result immediately

document-writer

call_agent

Need result immediately

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cwdYesWorking directory for the agent (required)
agentYesThe agent to use: advisor | researcher | explore | frontend-ui-ux-engineer | document-writer
imagesNoBase64 encoded images (only for multimodal-looker)
promptYesThe prompt/task for the agent
contextNoAdditional context
Behavior4/5

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

No annotations are present, so the description carries the full burden. It discloses that the call is blocking, takes 30-120s, and that advisor is read-only. However, it does not describe the return value shape, error behavior, or whether the agent can mutate files, which limits full transparency.

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 front-loaded with the key blocking behavior and then uses headers, a decision tree, and a table for efficient scanning. It is somewhat long, but most content earns its place by directly informing tool selection; the 'Why async for search agents?' section is slightly redundant with the decision tree.

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?

Given there is no output schema and no annotations, the description does substantial work by covering routing, agent roles, and timing expectations. It lacks an explicit statement of the return value or post-call behavior, which would make it fully complete. Overall, it is highly informative but has a notable gap.

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 coverage is 100%, so the baseline is 3. The description adds significant semantic value by detailing each agent's role and pairing them with the appropriate call mode. It does not enrich prompt/context/images beyond the schema, but the agent-level detail meaningfully helps invocation.

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 'Synchronous single agent call (BLOCKING, 30-120s)', which precisely names the action, resource, and blocking behavior. It clearly distinguishes from async siblings by stating what this tool is used for versus call_agent_async, and the mapping table reinforces the exact agent-to-tool pairing.

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

Usage Guidelines5/5

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

The decision tree provides explicit when-to-use and when-not-to-use guidance, including 'NEVER this tool' for explore/researcher and alternatives like call_agent_async and call_agents_batch. The Agent → Tool Mapping table further clarifies which agents should use this tool synchronously.

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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