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

With no annotations provided, the description carries the full burden and does a solid job: it discloses the side effect (the recommended actor's trust score is updated), the cost (FREE), two hard constraints (no self-recommendation, triple uniqueness), and the return fields. It does not say what happens on a duplicate triple (error vs. overwrite), which is the main remaining ambiguity.

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 short, front-loaded sentences: purpose first, then side effect and return values, then constraints. Slightly awkward line breaks and the redundant repetition of return data already in the output schema keep it from a 5.

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?

Given an output schema exists and parameter documentation is complete, the description need only cover behavior and constraints — which it does, including mutation side effect, cost, and uniqueness rules. Missing only duplicate-handling behavior and an explicit comparison to the rate/attest siblings.

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?

Schema coverage is 100%, so 3 is the baseline; the description earns a bump by explaining that the (you, them, context) combination is the uniqueness key, which is composite-key semantics the schema does not express. The optional recommender_mint_id and attestation_id fields are left to the schema, which documents them adequately.

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 — recommending another actor in a named context with a 1–5 score — which is unambiguous. It implicitly separates itself from mint_rate and mint_attest by using 'recommend' and 'worked with', but it never names those siblings or draws the line explicitly.

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 gives real operating constraints: you cannot recommend yourself, and each (you, them, context) triple is unique, plus 'FREE' signals no cost. However, it never says when to prefer this over mint_rate or mint_attest, which are the obvious adjacent endorsement mechanisms among the siblings.

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