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

Although annotations already declare readOnlyHint/openWorldHint=false/destructiveHint=false, the description goes well beyond them: it discloses filtering rules ("Only confirmed terms, and only those whose source you may open"), a licensing constraint ("Only where the company's plan includes AI"), and the 'links' relationship kinds returned. That is substantial behavioral context beyond the annotation set.

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?

The core purpose and the when-to-use instruction are front-loaded in the first sentences, and most clauses carry real information. It is dense and slightly over-stuffed with parenthetical nesting, so it falls short of maximal conciseness, but nothing is clearly redundant.

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 carries the return-value burden and does: it explains the definition, where it is defined, spelling variants, the links structure, and what an empty result means. With only two well-documented parameters, this is complete enough to call correctly.

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 the schema already documents 'word' and 'project'; baseline is 3. The description adds meaning beyond it by describing matching behavior ("Matches the term or any of its spellings, case aside, then terms that begin so") and the read-scope constraint, which directly clarifies how the 'word' input is interpreted.

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?

The description names a concrete resource (a project's own definition of a word, code, or notion), gives examples, and explicitly distinguishes itself from the sibling 'term_graph' ("term_graph has the whole picture"). An agent can tell exactly what this returns without opening the schema.

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?

It prescribes when to use it ("Ask it before guessing at a word you do not know in an issue or a page"), points to the alternative for the full picture, and states the fallback behavior when the result is empty ("ordinary word, or ask a person"). Exclusions and alternatives are both covered.

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