llm_detachDetaches this chat at once, so open Bowmark pages' AI calls go back to Bowmark's own model instead of waiting for this chat.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| ok | No | True when it was accepted. | |
| reason | No | Why it was refused, when it was. |
Changes observed during successful MCP inspections.
Output schema / (root)Previous value: -nullNew value: +{
+ "additionalProperties": true,
+ "properties": {
+ "ok": {
+ "description": "True when it was accepted.",
+ "type": "boolean"
+ },
+ "reason": {
+ "description": "Why it was refused, when it was."
+ }
+ },
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare non-read-only, idempotent, non-destructive. The description adds real behavioral value with 'at once' (immediate effect) and the fallback behavior ('go back to Bowmark's own model instead of waiting for this chat'). It does not say whether the chat itself is closed or what state remains afterward, which matters for a detach operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence with the action front-loaded and the consequence trailing. The phrasing 'open Bowmark pages' AI calls' is slightly tangled and requires a second read, but no sentence is wasted.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present, return values need not be explained. However, the description leaves the lifecycle unclear: what happens to the chat after detachment and how this pairs with llm_answer/llm_poll for a reattach flow is unstated, which is the main missing piece for a state-changing tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Zero parameters, so there is nothing to disambiguate; baseline 4 applies. The description correctly implies the target chat is implicit context rather than an argument.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource: 'Detaches this chat at once'. The consequence clause (open Bowmark pages' AI calls revert to Bowmark's own model) distinguishes it from siblings like llm_answer and llm_poll, which serve calls rather than release them. Not a 5 because 'this chat' assumes context the agent must already hold.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The implied usage (stop routing AI calls for Bowmark pages through this chat) is inferable from the effect described, but there is no explicit when-to-use, no precondition, and no named alternative or sequencing relative to llm_answer/llm_poll.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.