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AIWorkhub

AIWorkhub

by shrec
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

aiworkhub_agent_collect_result

Read-only

Collect a worker request's bounded log output and review-readiness evidence so you can inspect raw results before deciding whether to request a folded review packet.

Instructions

READ-ONLY: collect bounded worker output and review-readiness evidence.

Use this for one request's raw output and readiness; use aiworkhub_review_packet for the folded review evidence before deciding.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "request_id": "<request_id>"
    },
    "name": "aiworkhub_agent_collect_result"
  }
}

Input Schema

NameRequiredDescriptionDefault
request_idYesId of the launched worker request to collect output for.
max_log_bytesNoMaximum bytes of worker log tail to return; defaults to the server's log-tail limit.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.12.67
    • addedInput schema / properties / max_log_bytes / description
      Added value: +"Maximum bytes of worker log tail to return; defaults to the server's log-tail limit."
    • addedInput schema / properties / request_id / description
      Added value: +"Id of the launched worker request to collect output for."
  2. First observedv0.1.0

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the leading 'READ-ONLY' is largely restating structured data. The description adds a little useful context by noting the output is bounded (matching max_log_bytes) and by framing the result as readiness evidence, but it says nothing about behavior when the request is unknown, unfinished, or when the log tail is truncated. With annotations carrying the safety profile, this is adequate but thin.

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 tight sentences with the safety signal and the resource scope front-loaded, followed by the routing rule. Nothing is wasted, though the trailing clause 'before deciding' reads as a dangling fragment and could be tightened.

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?

An output schema exists, so return values need no explanation, and annotations cover the safety profile. The description supplies the one thing structured fields cannot — that this returns raw per-request output while aiworkhub_review_packet returns folded evidence — leaving only minor gaps around error and truncation behavior.

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

Parameters3/5

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

Schema description coverage is 100%, and both request_id and max_log_bytes carry their own descriptions in the schema. The description only hints at the bounding behavior via 'bounded worker output' and adds no format or semantics beyond what the schema already documents, so the baseline 3 applies.

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 gives a concrete verb ('collect') and a specific resource ('bounded worker output and review-readiness evidence'), and it explicitly contrasts this tool with the sibling aiworkhub_review_packet. The phrase 'review-readiness evidence' is somewhat jargon-heavy, but the scope ('one request's raw output') is unambiguous enough to separate it from nearby agent tools.

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?

It states both sides of the routing decision: use this tool for a single request's raw output and readiness, and use aiworkhub_review_packet for the folded review evidence before deciding. That names the alternative and the condition that selects it, so an agent doesn't need to infer the boundary.

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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