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

No annotations are supplied, so the description carries the full disclosure burden. It does disclose the return content (headwords plus grammatical reading across case, number, gender, person, tense, mood) and hints at ambiguity via "could belong to", but it says nothing about behavior when no analysis is found, how candidates are ordered, or handling of macrons versus plain vowels.

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 sentence with the input condition front-loaded and examples embedded inline; nothing is redundant or padded.

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 no output schema, the description wisely summarizes the return payload, which is the most important missing piece. Gaps remain around no-match behavior and output shape, but for a one-parameter read-only analysis tool it is largely sufficient.

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% for the single parameter, so the baseline is 3. The description adds some value through extra examples ("band", "gōdra") implying macronized input is accepted and that forms may coincide with modern English words, but it offers no syntax or normalization details beyond the schema.

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 states a specific operation on a specific resource: take an inflected Old English form and return candidate headwords plus a grammatical reading. It is immediately distinguishable in practice from lookup_headword and inflect, but it never names those siblings, so the differentiation is left to inference.

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?

"Given any inflected form" sets an implicit input precondition and the examples clarify the expected shape of the input. There is no explicit statement of when to prefer this over lookup_headword or inflect, nor any exclusion for non-Old-English or already-lemmatized input.

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