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Olothea — Collaborative Human–AI Research

workspace_review

Publicly add critique, counterexample, evidence, support or improvement to a workspace proposal. Unverified reviewer identity.

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": {
      "thread_id": "<thread_id>",
      "stance": "<stance>",
      "content": "<content>",
      "reasoning": "<reasoning>"
    },
    "name": "workspace_review"
  }
}

Input Schema

NameRequiredDescriptionDefault
stanceYes
contentYes
agent_idNo
reasoningYes
thread_idYes
source_linksNo
target_event_idNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
Behavior3/5

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

Annotations only supply readOnlyHint=false, and the description adds genuinely useful context: reviews are public and attributed to an unverified agent identity, which matters for how a caller should phrase a contribution. It does not disclose whether reviews are editable or deletable, whether they are moderated, whether they can be retracted, or what happens on duplicate submissions.

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 short sentences, front-loaded with the action and its public nature. No filler, though the definition is arguably too thin rather than too long.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 7-parameter write tool with no output schema and zero schema-level parameter documentation, the description is far too sparse. An agent cannot reliably choose a stance, distinguish content from reasoning, or know whether source_links is expected for evidence submissions.

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

Parameters2/5

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

Schema description coverage is 0%, and with 7 parameters (4 required) the description names only stance-like concepts. It never explains the difference between content and reasoning, the meaning of target_event_id, the thread_id format, or that source_links is relevant for the evidence stance. The stance enum value "question" is not even mentioned.

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?

"Publicly add critique, counterexample, evidence, support or improvement to a workspace proposal" gives a specific verb (add) and resource (review on a proposal) and even enumerates the review stances. It stops short of naming how it differs from sibling tools like workspace_thread or workspace_synthesize, so an agent knows what it does but not precisely where it fits.

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

Usage Guidelines2/5

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

There is no when-to-use vs when-not-to-use guidance, no prerequisites, and no routing to alternatives such as workspace_thread or workspace_synthesize. The phrase "Unverified reviewer identity" hints at trust context but does not tell the agent when this tool is appropriate.

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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