mesa_avu_from_term

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

With no annotations, the description carries the full burden and does disclose the key side-effect profile ('Pure transformation', no iRODS write) plus the exact output structure (attribute/value/unit). It omits whether an OLS network lookup occurs and any error behavior, leaving a modest gap.

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?

A single dense sentence with the transformation and the no-write constraint front-loaded; every clause earns its place with no filler.

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?

There is no output schema, so the description correctly compensates by describing the returned triple. Combined with the thorough input schema this is nearly complete, though OLS lookup/fallback behavior is left to the schema.

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 description coverage is 100%, so all five parameters are already documented, including the iri/curie/label interplay. The description's attribute='<ontology>.<snake_case_label>' and unit=<CURIE> mapping adds useful framing but mostly restates what the schema already conveys.

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 precise verb and transformation ('turn an OLS term + user value into the canonical AVU triple') and even spells out the resulting triple shape. The phrase 'without writing to iRODS' cleanly separates it from the write-oriented sibling mesa_avu_apply_term.

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 'Pure transformation ... without writing to iRODS' framing tells the agent this is for computing an AVU triple rather than persisting one, implicitly steering toward mesa_avu_apply_term for writes. It never names the alternative explicitly or states exclusions, so it stops short of a full 5.

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