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

Annotations provide readOnlyHint: true, so the description isn't required to state read-only, but it adds rich behavioral detail: the scope of what is read (learned profile, per-topic affinities, pinned stories with follow-ups). This goes well beyond the annotation and clarifies what the agent should expect.

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?

Front-loaded with the main verb and resource, but the single sentence is long and packed with a list. It's not bloated, but could be broken into two sentences for readability. Still efficient for the complexity.

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?

Covers all the elements the tool reads, which is a broad scope. It lacks an explicit output format description, but given no output schema and read-only nature, the agent can infer it returns the diet structure. Minor gap.

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?

No parameters exist (schema coverage 100% trivially), so the description needn't explain them. Baseline for 0 params is 4, and the description doesn't waste space on parameters.

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 'Read' and resource 'information diet' and enumerates the components it returns (schedule, length, technicality, interests, learned profile, per-topic preferences, pinned stories). It clearly distinguishes from siblings like update_information_diet by positioning itself as the read-before-change operation.

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 says 'read it before changing anything', which tells the agent when to use it (before any mutation). It implies alternatives (update_information_diet) but doesn't name them; the context is strong but lacks a direct exclusion.

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