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

Annotations already establish read-only, idempotent, non-destructive behavior, so the bar is lower. The description still adds real value by disclosing provenance ('MALAI calculates these from the user's profile and GLP-1 needs') and an instruction to trust the returned values verbatim. It does not say what happens if the profile is incomplete or targets are unavailable.

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?

Three sentences, front-loaded with the resource and its fields, then the provenance note, then the trigger conditions. Minor redundancy from repeating 'MALAI' three times, but no sentence is wasted.

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?

With an output schema present, return shape needn't be explained, and with no inputs there is nothing else to cover. The description supplies purpose, provenance, and triggers, which is sufficient for a simple read tool; only the failure/empty-profile case is unaddressed.

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 takes zero parameters, so there is nothing for the description to disambiguate; the baseline for a no-param tool applies. The description correctly spends no words on inputs.

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 and resource ('Read the user's daily nutrition targets') and enumerates exactly what comes back: calories, protein, carbs, fat, fiber, BMR, TDEE. The phrase 'use them exactly as given rather than calculating your own' implicitly separates it from the sibling calculate tools (malai_calculate_daily_targets, malai_calculate_protein_target).

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?

Gives explicit trigger conditions: the user asks about their goals, their protein target, or whether an amount is enough. It also steers away from recomputing targets. The gap is that it never names the alternative tools outright, so the agent must infer that the malai_calculate_* siblings are the path when targets must be derived rather than fetched.

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