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

Annotations already declare readOnlyHint=true and idempotentHint=true, but the description adds substantial behavioral context beyond that: 'This server never requests your sample, analysis notes, or indicators and instructs your AI to keep them local.' This privacy-preserving behavior is critical for the agent's trust assessment. It also explains the deferral behavior for certain topics, which is not obvious from the schema.

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 two sentences, front-loaded with the core purpose. The first sentence names the resource and lists topics. The second sentence packs important usage notes (deferral, pairing, privacy) without redundancy. Every sentence earns its place; no unnecessary words.

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 read-only tool with no output schema, the description gives enough context: it clarifies that topics defer, how field_id works, and that results flow locally. It doesn't enumerate the full topic list (the schema does), and it doesn't describe the output format, but given the simplicity of the tool, this is sufficient. Slightly more detail on return value could bump it to 5, but not necessary.

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 input schema provides full descriptions for both parameters (topic enum and field_id), so the baseline is 3. The description adds value by explaining the relationship between topic and field_id ('Pair the 'fields' topic with field_id') and noting that topic defaults to a 'summary' overview. This enriches the schema semantics, especially for the field_id parameter that only has meaning in a specific topic context.

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 opens with a specific action and resource: 'Get Lenny Zeltser's expert malware analysis report writing guidelines.' It clearly distinguishes this from sibling tools by naming the exact domain (malware analysis) and topic set, and even notes that some topics defer to another tool, get_security_writing_guidelines. This makes the tool's purpose unmistakable.

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 provides explicit usage context: it states which topics (tone, words, structure, executive_summary) should be deferred to a different tool, and it instructs pairing the 'fields' topic with field_id for single-field guidance. It does not explicitly compare against other malware_* siblings, but the deferral and pairing instructions give clear when-to-use and when-not-to-use guidance.

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