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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explains that the tool is 'Executable — fetches the URL or parses the raw Lottie JSON, runs 10 checks server-side. No browser needed.' It also discloses the exact return JSON structure and the meaning of valid/score. It does not cover possible error conditions (e.g., invalid URL, timeouts) or authentication, but for a validation tool with read-only behavior, the core transparency is strong.

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 longer than typical, but every sentence contributes value: purpose, standards, check details, rationale for the validator's existence, usage, when-not-to-use, execution model, return format, and parameter guidance. It is front-loaded with the core purpose and structured logically. While it could be trimmed slightly, the length is justified by the complexity of the tool and the absence of annotations or an output 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?

Given that there is no output schema and no annotations, the description fully compensates by defining the return shape ({ checks[{id, name, status, detail}], valid, score }), the specific checks (m01-m10), and the standards involved. It also explains why the validator exists (DTCG spec gap) and how it differs from designesy_score. This is a complete and self-contained description for an agent to select and invoke the tool 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?

The schema already documents both parameters (url and lottie_file) with descriptions, so the baseline is 3. The description adds meaningful semantics beyond the schema: it explains that url is for fetching a remote Lottie file, lottie_file is for an inline JSON string, and critically, 'Provide exactly one.' This clarifies the mutual exclusivity, which is not enforced by the schema (required is empty). This additional guidance lifts the score above baseline.

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 starts with a specific verb ('Validate') and resource ('a Lottie animation file'), and clearly states the two standards it validates against (Lottie spec v1.0.1 and Designesy motion standards). It explicitly mentions returning 10 checks (m01-m10) with PASS/FAIL/WARN, and distinguishes itself from sibling tools by noting it validates a single Lottie file rather than full-site scoring (which designesy_score handles).

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 explicit when-to-use guidance: 'Use this to verify a motion/animation asset is well-formed AND accessible — the only validator that checks both.' It also gives a clear when-not-to-use condition and names the alternative: 'When NOT to use: for full-site motion scoring (not a single Lottie file), use designesy_score.' Additionally, it instructs the caller to 'Provide exactly one' of url or lottie_file, which is critical operational guidance.

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