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Antwork

by io.antwork
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report_issue

Report what looks like an Antwork defect to the Antwork team, who read every report.

For a result that contradicts what the call said it did, a user saying something did not happen, or a failure with no reason given. Not for a refusal that explains itself (limits, media_required, plan, reconnect). The calls made before it are attached by Antwork; describe what you saw.

Args: what_happened: What went wrong, in plain words, with any error text seen. expected: What should have happened instead. tool_name: The Antwork tool that misbehaved, if one did. post_id: The post involved, if any. workspace_id: Workspace ID or name, if one was involved.

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": {
      "what_happened": "<what_happened>"
    },
    "name": "report_issue"
  }
}

Input Schema

NameRequiredDescriptionDefault
contextNoThe user's underlying goal for this call, in one sentence without personal details. Used for product analytics only.
post_idNo
expectedNo
llm_modelNoThe model identifier of the calling assistant, or "unknown". Used for product analytics only.
tool_nameNo
workspace_idNo
what_happenedYes
conversation_idNoPass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request.

Output Schema

NameRequiredDescriptionDefault
_mcp_instructionsNoServer-issued metadata for this conversation.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=false and destructiveHint=false; the description adds genuinely new behavior — that a human team reads every report and that preceding calls are attached automatically, so the agent should describe observations rather than dump history. It stops short of saying what the agent gets back or any submission limits, which is minor since an output schema exists.

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?

Front-loads purpose, then eligibility, then a compact Args list — good ordering with no wasted preamble. The Args block mildly duplicates the schema and the post_id/workspace_id entries are near-tautological ('if any'), costing a little density.

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?

For an 8-parameter, low-required-count reporting tool with an output schema, the description supplies everything needed to call it correctly: triggers, exclusions, the fact that context is auto-attached, and field intent for the free-text fields.

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 only 38%, so the description must carry weight — and it does, glossing what_happened, expected, tool_name, post_id, and workspace_id with usage hints ('if one did', 'if any') that the bare schema lacks. It omits any mention of context, llm_model, and conversation_id, though those three happen to be the best-documented fields in the schema itself.

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?

Opens with a specific verb and resource: report an Antwork defect to the Antwork team. The scope is unambiguous and no sibling tool in the list (create_post, get_post_context, etc.) could be confused with it.

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?

Gives three concrete trigger conditions (result contradicts the call's claim, user says something didn't happen, failure with no reason) and an explicit exclusion list (limits, `media_required`, plan, reconnect refusals that explain themselves). This is exactly the when/when-not routing an agent needs for an escalation path.

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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