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mint_recommend

Recommend an actor you've worked with by assigning a trust score from 1 to 5 in a specific context, updating their on-chain reputation.

Instructions

Recommend another actor you've worked with, in a named context, 1–5. Updates the recommended actor's trust score. FREE.

Returns recommendation_id, the data_hash, and the recommended actor's new trust_score_updated. You can't recommend yourself; each (you, them, context) triple is unique.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteNooptional free-text, e.g. "Best for Fanuc + Siemens mixed fleets".
scoreYesinteger 1–5.
contextYeswhat you're endorsing them for, e.g. "cross-oem normalization".
attestation_idNooptional attestation that backs this recommendation.
recommended_mint_idYesthe actor you're endorsing ("MINT-xxxxxx").
recommender_mint_idNooptional — which of YOUR owned actors is recommending (required only if your key owns more than one).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations, the description discloses key behavioral traits: it updates the recommended actor's trust score (mutation), returns recommendation_id, data_hash, and updated trust score, and imposes uniqueness constraints. However, it does not mention any destructive potential or required permissions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very concise, using only a few sentences with the main action first, followed by key behaviors and constraints. No superfluous text.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite no annotations, the description covers purpose, return values, constraints, and mutation behavior. With an output schema present, the description is sufficiently complete for an agent to correctly select and invoke this tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the description does not need to elaborate on parameters. It adds marginal value by reinforcing the score range and mentioning 'FREE', but does not deepen understanding beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a clear specific verb ('Recommend') and resource ('another actor'), and sets it apart from siblings like 'attest', 'discover', 'rate', 'register', 'verify' by focusing on endorsing a known actor with a score and context.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description states constraints (cannot recommend self, unique triple) and mentions the tool is free, but does not provide guidance on when to use this tool versus alternatives like 'mint_rate' or 'mint_attest', which could have overlapping purposes.

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

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