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

With no annotations, the description carries the burden of behavior disclosure. It communicates that the tool returns static recommended instructions, hints at idempotence with 'Call this once', and explains that the output is suitable to paste into other LLM clients. It could be more explicit about being side-effect-free, but the read-only nature is strongly implied.

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 description is a single focused sentence without filler. It front-loads the core return value and then immediately adds actionable usage context, earning every word.

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 zero-parameter tool with no output schema and no annotations, the description provides everything needed: what the tool returns, when to call it, and how to use the result. Nothing essential is missing.

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 tool has zero parameters, so there is nothing to document. A score of 4 reflects the baseline for parameterless tools, since no semantic burden falls on the description.

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 states a specific action and resource: 'Returns the recommended instructions for using mindpm effectively.' This clearly distinguishes it from all sibling tools, none of which serve as a meta-instruction provider.

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 description explicitly tells an agent when to invoke the tool ('Call this once if you are unsure how to use mindpm') and when to share output with a user. No alternative tool is needed, so the absence of when-not guidance is not a gap.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.