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Save a policy to acknowledge

hr_save_policy
Idempotent

A policy people must read and confirm (an AI use policy, a code of conduct, a security policy), in Markdown, for everyone or some departments. Changing its title or text makes a new version, which needs confirming again. Send it with hr_send_policy. $0.001. Costs $0.001 per call; nothing if it fails.

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": {
      "name": "<name>",
      "title": "<title>",
      "text": "<text>"
    },
    "name": "hr_save_policy"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYesLike ai-use-policy.
textYes
titleYes
departmentsNoOnly these departments; everyone if left out.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior5/5

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

Adds real behavior beyond the annotations: Markdown payload format, department scoping, the versioning rule (editing title or text creates a new version requiring re-confirmation), and failure-cost handling. The versioning rule is the key thing an agent cannot get from readOnlyHint/idempotentHint/destructiveHint, and it is consistent with idempotentHint=true.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Most sentences earn their place, but pricing is stated twice ('$0.001.' then 'Costs $0.001 per call; nothing if it fails'), which is pure waste. The opening is also a noun phrase fragment rather than a verb-fronted statement, so the action is not front-loaded as strongly as it could be.

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 3-required-param mutation with annotations but no output schema, the description covers format, scoping, versioning side effects, cost, and the follow-up tool. It omits authorization requirements and what happens to existing acknowledgements when a new version is created, which would be the remaining useful detail.

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?

At 50% schema coverage, the description adds the Markdown format for 'text' and confirms the 'everyone if left out' default for departments, but says nothing about the 'name' slug constraints (pattern, max 80 chars, like ai-use-policy) or about title/text length limits. It partially compensates but leaves two undocumented parameters unaddressed.

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?

The description identifies the resource precisely (a read-and-confirm policy in Markdown, scoped to everyone or some departments) and names a sibling that consumes it (hr_send_policy). It never opens with a clean verb like 'Save/create', so the action itself has to be inferred from the title, which keeps it short of a 5.

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?

Explicitly routes the agent to the next step: 'Send it with hr_send_policy', which distinguishes saving from distribution. It gives no when-not guidance or prerequisites (e.g. whether you must be an admin, whether hr_save_document is the alternative for non-acknowledgement documents), so it stops at clear context without exclusions.

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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