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

Annotations already cover the safety profile (readOnlyHint=true, destructiveHint=false), so the description's job is extra context, and it delivers two genuinely useful traits: answers are grounded in the project's saved estimate, and each call consumes daily AI quota. It stops short of saying what happens when the project has no saved estimate or whether answers include source references.

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?

Two sentences, zero filler, with the scoping constraint and context source front-loaded before the quota caveat. Nothing repeats the title or the schema.

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?

For a two-parameter read-only tool with full schema coverage and no output schema, the definition covers purpose, context source, scope of answerable topics, and cost. The only real gap is the failure mode when a project lacks a saved estimate, which an agent would want to know before calling.

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 both parameters are already documented, giving a baseline of 3. The topic list (sequencing, materials, codes, schedule, costs) does help an agent formulate the question and hints at the scope boundary, but no format, length, or phrasing guidance is added beyond the schema's maxLength/minLength.

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 specific verb and resource ('Answers a question about one Phulax project') and enumerates the domains the answer covers (sequencing, materials, codes, schedule, costs), which makes it clearly a Q&A tool rather than a raw data reader. It does not explicitly contrast itself with the closest sibling get_project, so the distinction (narrative answer vs. field retrieval) must be inferred.

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?

Usage is implied by the topic list and the 'one project' scoping, but there is no explicit when-to-use guidance and no named alternative such as get_project for raw fields or create_estimate for originating the context data. The mention of the daily AI limit hints that this should be used sparingly but does not tell the agent what to do instead.

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