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

The description discloses several behavioral constraints beyond the annotations: it explicitly states 'No server model is invoked', indicating pure persistence without AI processing did not appear in the annotations. It also provides rules like 'do not claim bidder compliance from an RFP clause' and 'label implicit hypotheses explicitly', which define the tool's validation behavior. The annotations already signal non-read-only, idempotent, and destructive hints, and the description adds context without contradicting them.

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 a compact set of five sentences, each carrying critical information. The first sentence states the core purpose, followed by actionable constraints and a clear output behavior. No filler or redundancy is present, making it highly efficient.

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?

The description covers the purpose, input constraints, output (returns section IDs), and critical behavioral rules. It omits details like error handling or idempotency semantics, but the annotations already provide idempotentHint and destructiveHint. For a tool with 10 nested parameters and no output schema, this description is sufficiently complete to guide an agent.

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?

Despite the schema having only 10% description coverage, the description provides semantic guidance for many parameters: it tells how to fill basis and expectedRevision ('Echo ... from helvabase_read_context'), how to structure requirements ('Every requirement must reference the supplied frozen citation catalog', 'Keep originalQuote separate from interpretation'), and what to include in requirements/questions/risks. It does not explicitly describe idempotencyKey or declaredProvenance, but those are standard or self-explanatory. Overall it compensates reasonably for the low schema coverage.

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 opens with the specific verb 'Persist' and the resource 'the analysis YOU produced from the current RFP', making the tool's function immediately clear. It further distinguishes this from a generation or drafting tool by stating 'No server model is invoked' and 'Returns the section IDs to draft'. This clearly separates it from siblings like helvabase_record_document_analysis or helvabase_submit_draft.

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 provides clear workflow context: it is used after reading context via helvabase_read_context, since it instructs to 'Echo basis and expectedRevision from helvabase_read_context'. It also implies the tool is for finalizing an analysis, as it returns section IDs to draft. However, it does not explicitly name alternative tools or conditions when not to use this one, so it lacks exclusions.

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