lexicon_add

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

The description discloses critical behavioral traits beyond the annotations: persistence ('the lexicon is a preference kept beside the project, not an edit'), non-reversibility ('Undo does not revert it'), scope ('Display only; the transcript and `verify` are untouched'), and matching behavior ('Every occurrence'). This complements the destructiveHint and idempotentHint annotations rather than contradicting them, and no contradiction is present.

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 description is dense but every sentence earns its place: core purpose first, then matching rules, undo behavior, removal alternative, and kind distinction. It is well-structured with a clear separation of concerns, and nothing is redundant or 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?

Given the tool's complexity (five params, two modes, persistence semantics, undo interaction), the description covers all necessary ground: what it does, when to use it, how to remove entries, what is untouched, and how `plan` can be used safely. An output schema exists, so return-value details are not required. Nothing an agent needs to decide on or invoke this tool is missing.

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% with rich descriptions for all five parameters. The description adds some contextual guidance, such as 'Whole words, one or several: a multi-word key merges its words into one caption word' and the narrowing tactic, but this largely repeats what the schema already states. Baseline 3 is appropriate because the schema carries the semantic load.

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 opening sentence states a specific verb and resource: 'Keep a standing spelling correction: captions print `canonical` wherever whisper wrote `heard`.' It names the exact mapping behavior and distinguishes itself from siblings by explicitly addressing `lexicon_rm` and the `kind="say"` alternative for `vo_synth`. An agent can tell what this tool does and how it differs from related tools.

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 clear when-to-use context: 'The fix for a caption that shows whisper's spelling' — and provides explicit exclusions and alternatives: 'Remove an entry with `lexicon_rm`' and 'kind="say" is `vo_synth`'s pronunciation respelling instead.' It also steers users toward `plan` over executing destructive changes, which is practical guidance.

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