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sanhao-global-experts

policy-rewrite-tool

Save hours every week. This policy rewrite tool toolkit gives you a battle-tested prompt and operating playbook for restaurant/brand growth. No setup, works in any LLM chatbot.

Input Schema

NameRequiredDescriptionDefault
queryNoOptional user query to scope the analysis.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden, and it discloses almost nothing: no output format, no length or style behavior, no indication of whether input text is transformed or merely used as context. The only behavioral signal is the implication that the tool returns prompt/playbook material rather than performing an action, which is a small but real hint.

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

Conciseness2/5

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

It is short, but the lead sentence "Save hours every week" is pure marketing filler and occupies the front-loaded position where the actual purpose should sit. Two of the three sentences earn nothing for an agent deciding whether to call the tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

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 annotations and no output schema, the description still needs to say what comes back and when to use it, and it says neither. The reference to restaurant/brand growth is unexplained and unsupported by the schema or name, so an agent cannot form a reliable picture of the tool's contract.

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?

There is a single optional parameter with 100% schema description coverage ("Optional user query to scope the analysis"), so the schema already does the work. The description adds nothing about how the query scopes the rewrite, leaving the baseline score appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description restates the name ("This policy rewrite tool toolkit") and then talks about a "battle-tested prompt and operating playbook for restaurant/brand growth," which never states what the tool concretely does to a policy. It gives no verb+resource specificity and never distinguishes itself from the many siblings like policy-polish-tool, policy-rewrite-tool, policy-gen-tool, or policy-write-tool. The growth/restaurant framing actively muddies the purpose implied by the name.

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

Usage Guidelines1/5

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

There is no when-to-use guidance, no when-not-to-use guidance, and no named alternative among the nine policy-* siblings. "No setup, works in any LLM chatbot" is a sales claim, not a selection cue, so an agent has no basis for routing to this tool over policy-polish-tool or policy-rewrite-tool.

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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