get_outreach_approval| Name | Required | Description | Default |
|---|---|---|---|
| agent_id | No | The agent whose effective settings to read. When omitted, reads the current agent's settings if this chat is tied to one, otherwise the account-wide settings. |
Changes observed during successful MCP inspections.
Input schema / properties / agent_idAdded value: +{
+ "anyOf": [
+ {
+ "type": "integer"
+ },
+ {
+ "type": "null"
+ }
+ ],
+ "default": null,
+ "description": "The agent whose effective settings to read. When omitted, reads the current\nagent's settings if this chat is tied to one, otherwise the account-wide settings."
+}Input schema / properties / task_idRemoved value: -{
- "anyOf": [
- {
- "type": "integer"
- },
- {
- "type": "null"
- }
- ],
- "default": null,
- "description": "The agent (task) whose effective settings to read. When omitted, reads the current\nagent's settings if this chat is tied to one, otherwise the account-wide settings."
-}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true, and the description adds useful non-obvious context: pending_approval is a normal state produced by these settings, not a failure, and it explains override vs account-wide resolution. It stops short of disclosing other behavioral details like permissions or performance, but the read-only annotation plus this context covers the main surface.
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?
The summary is front-loaded with the core purpose, followed by a practical diagnostic cue and clear optional-parameter guidance, and the returns section is compact and useful. No sentences are 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?
Given one optional parameter, a readOnlyHint annotation, and no output schema, the description is complete: it explains scope resolution, return structure, value semantics, and the practical meaning of the settings. An agent has everything needed to call it correctly and interpret the result.
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?
The schema already documents `agent_id` at 100% coverage, and the description's parameter guidance mostly restates the schema's meaning (specific agent vs account-wide vs current agent). Since the schema carries the semantic load, the description adds no substantial new parameter insight beyond the baseline.
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?
The description clearly identifies a specific verb and resource: reading per-subtype outreach approval settings, and it differentiates the read semantics from the sibling setter by noting the returned settings are the gating that holds messages in pending_approval. It does not explicitly name `set_outreach_approval` or another alternative, so it falls just short of full sibling differentiation.
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?
It gives a clear when-to-use: read this before diagnosing a pending_approval message as stuck, and it explains the optional `agent_id` decision. It does not explicitly state when not to use it or direct to an alternative setter, so not a 5.
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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