Agent Router

wait_for_task

Wait for a platform agent task to complete and return its result.

Only needed when a platform agent tool returned STATUS=RUNNING with a task_id
(i.e. the task was still running after the initial 50s inline wait).
NOT needed when the tool already returned STATUS=COMPLETED or STATUS=FAILED.
NOT needed for a2a_call_agent — that always returns directly.

Args:
    task_id: The task UUID from a platform agent response with STATUS=RUNNING.
    max_wait_seconds: Max seconds to wait (default 45, max 300).

Input Schema

TableJSON Schema

Name	Required	Description	Default
`task_id`	Yes
`max_wait_seconds`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

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

First observedJun 16, 2026

TDQS

A4.7/5.0

Behavior4/5

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

No annotations are provided, so description carries full burden. It explains the tool blocks until completion, why it exists (initial wait insufficient), and parameter constraints (max_wait up to 300s). Could mention it returns the final result but output schema covers that.

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?

Description is concise, well-structured with a clear purpose statement, a bulleted list of usage conditions, and an Args section. Every sentence adds value with no waste.

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 async waiting nature, 2 parameters, and presence of an output schema, the description fully covers when to use, how to use, parameter meanings, and constraints. No gaps.

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 has 0% description coverage, but description compensates well: explains task_id as 'task UUID from a platform agent response with STATUS=RUNNING' and max_wait_seconds with default and max values. These add meaning beyond the raw schema.

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?

Description clearly states the tool waits for a platform agent task to complete and return its result. It distinguishes itself from sibling tools like a2a_call_agent by explicitly saying NOT needed for that, and clarifies it's only for the RUNNING status case.

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?

Provides explicit when-to-use condition (STATUS=RUNNING after initial 50s wait) and when-not-to-use (STATUS=COMPLETED/FAILED, or for a2a_call_agent). This eliminates ambiguity.

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.

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