update_playbook_ruleReplace the whole context document the AI agent reads before every answer (read it first with get_training_overview, and keep what should stay). Markdown, up to 40,000 characters. Admins only.
| Name | Required | Description | Default |
|---|---|---|---|
| content | Yes | The whole new context, in Markdown. |
Changes observed during successful MCP inspections.
Input schema / properties / content / descriptionPrevious value: -"The new text of the rule."New value: +"The whole new context, in Markdown."Input schema / properties / productIdRemoved value: -{
- "description": "Product id from list_products.",
- "type": "string"
-}Input schema / properties / ruleIdRemoved value: -{
- "description": "The rule id from get_training_overview.",
- "type": "string"
-}Input schema / requiredPrevious value: -[
- "ruleId",
- "productId",
- "content"
-]New value: +[
+ "content"
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already flag destructiveHint=true and idempotentHint=true, and the description goes further: it explains that the entire document is replaced (so unstated content is lost) and warns to preserve what should stay. It also discloses the 40,000-character limit and the admin-only authorization requirement, which annotations cannot express.
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?
Two compact sentences. The destructive replacement action is front-loaded, followed by the prerequisite and the size limit, with no filler.
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?
For a one-parameter tool with no output schema, the description covers the action, the workflow prerequisite, the format/size constraint, and the permission requirement — everything needed to call it correctly without risk of silent data loss.
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?
Single parameter with 100% schema coverage, so baseline is 3; the description adds real constraint by specifying the format (Markdown) and the 40,000-character ceiling, which the schema does not state. Minor gap: no mention of what happens if the limit is exceeded.
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 ('Replace the whole context document the AI agent reads before every answer'), which distinguishes it from siblings like add_playbook_rule and update_agent. The scope word 'whole' makes the replacement semantics unambiguous.
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?
Explicitly sequences the workflow ('read it first with get_training_overview, and keep what should stay') and states the access precondition ('Admins only'). It stops short of naming add_playbook_rule as the alternative for partial/rule-level edits, so the when-not half is implicit.
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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