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Polyrank

by io.github.polyrank
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Lab assistant: reply in a chat

polyrank_lab_reply

Spends the account's AI credits: ask the user before calling, then pass confirm: true. Send the next message in one of your Lab assistant chats (409 while it is still answering). Spends AI credits like polyrank_lab_ask and waits the same way for the answer. Needs POLYRANK_API_KEY.

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": {
      "id": "<id>",
      "message": "<message>",
      "confirm": "<confirm>"
    },
    "name": "polyrank_lab_reply"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYes
confirmYesRequired: true, and only after the user agreed to this call in the conversation.
messageYes
wait_secondsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / confirm
      Added value: +{
+  "const": true,
+  "description": "Required: true, and only after the user agreed to this call in the conversation.",
+  "type": "boolean"
+}
    • changedInput schema / required
      Previous value: -[
-  "id",
-  "message"
-]New value: +[
+  "id",
+  "message",
+  "confirm"
+]
  2. First observed

TDQS

A4.1/5.0
Behavior5/5

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

Beyond the annotations (readOnlyHint=false, destructiveHint=false, idempotentHint=false), the description discloses the key cost behavior (spends the account's AI credits), a human-in-the-loop consent requirement, an auth prerequisite (POLYRANK_API_KEY), and the 409-while-busy concurrency behavior. These are exactly the traits an agent cannot infer from the structured fields.

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?

Four short sentences, front-loaded with the highest-stakes fact (credit spend plus the confirm requirement) before mechanics and auth. Dense and mostly waste-free, though the credit/wait parallel to polyrank_lab_ask is stated twice in slightly different words.

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?

For a 4-parameter, non-idempotent, open-world-false tool with no output schema, the description covers cost, consent, auth, and the busy-state error, and implies the answer is returned after waiting. It leaves the chat-id source and message length constraints unstated, which is a minor but real gap.

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 coverage is only 25% – only confirm carries a description. The description reinforces confirm: true and the consent rule, and "waits the same way for the answer" gestures at wait_seconds, but id (which chat) and message content/length limits are left entirely to the schema. Partial compensation for a low-coverage schema, so a mid score.

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?

"Send the next message in one of your Lab assistant chats" states a specific verb (send) and resource (message in an existing Lab chat), and the parenthetical 409 note makes clear this continues a chat rather than starting one. It implicitly separates itself from polyrank_lab_ask by saying it "spends AI credits like polyrank_lab_ask," but it never explicitly frames the start-vs-continue distinction.

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

Usage Guidelines4/5

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

Gives a concrete precondition (ask the user before calling, then pass confirm: true) and a runtime condition (409 while the assistant is still answering), which tells the agent both when to call and what to do when it fails. It stops short of an explicit "use polyrank_lab_ask instead when you want to start a new chat" exclusion.

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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