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

With no annotations, the description carries the full burden and does well: it discloses that output is written to a cache dir with named files, that Figma responses are cached so re-runs are offline and free, and that refresh=true bypasses that cache. The notable gaps are auth requirements (a Figma token is surely needed) and error/failure behavior.

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?

Front-loaded with the core action and output set, then flags, then caching, then the follow-up tool — a sensible ordering with no filler sentences. It is on the long side for a description, though every clause conveys operative information.

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 an eight-parameter tool with no annotations and no output schema, the description covers what is produced and where, the caching model, and the verification follow-up, which is most of what an agent needs. Only prerequisite credentials and failure modes are 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 description coverage is 100% and the parameter docs are already detailed, so the baseline is 3. The prose reinforces react/next/refresh semantics but adds little the schema does not already state, and the interaction between tailwind and the other flags is left to 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?

"Fetch a Figma frame and deterministically convert it to self-contained HTML (no LLM)" gives a specific verb, resource, output format, and even the execution model. It then enumerates the exact artifacts written (generated.html, reference.png, ir.json, assets.json) and the return value, so the tool is unmistakable against figma_verify and figma_inspect.

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?

It explicitly routes the agent: react=true for a component, next=true for a runnable App Router project, and "Follow with figma_verify to see how close the render is." That is real when-to-use guidance plus a named follow-up sibling. It never says when to prefer figma_inspect instead, so the exclusion set is incomplete.

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

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

With no annotations, the description carries the burden alone; it does disclose that the operation prints an outline rather than mutating anything and describes the shape of that output. It is silent on side effects, output size/pagination for large trees, and failure behavior when dir is invalid or absent.

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?

Front-loaded with the action and its output format, followed by a short rationale-and-ordering sentence. There is some redundancy between "understand the design structure" and the enumerated fields, but nothing is wasted at length.

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?

A simple three-parameter read tool with no output schema, and the description explains what the returned outline contains and what fields it shows. That is nearly everything an agent needs, with only edge-case behavior (empty results, invalid dir) left unspecified.

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 description coverage is 100%, so dir, depth, and filter are already documented in the schema. The description adds no extra parameter meaning such as how filter interacts with depth or the default depth of 4, so the baseline of 3 applies.

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 ("Print the IR tree as an indented outline") and even enumerates the fields emitted (role, name, box, layout, text, tokens). This clearly separates it from figma_convert and figma_verify, which produce/check the IR rather than read it back.

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?

Gives explicit sequencing ("Use after figma_convert") and the motivating job ("find a specific element without reading raw Figma JSON or the whole ir.json"). It does not contrast with figma_verify or say when inspection is unnecessary, so it stops short of full when/when-not guidance.

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

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

With no annotations, the description still discloses the rendering engine, the verification checks, the return payload (diff ratio plus categorized fixes), and the side effects of writing render.png and diff.png. It also flags the read-diff.png follow-up, giving enough behavioral context for an agent to operate it.

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 front-loaded with the core action, followed by outputs, iteration, and a reading tip. Every sentence adds useful operational detail without repetition.

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 nine-parameter tool with no output schema, the description explains what is returned, what files are written, and how to iterate. It omits the schema-documented URL/running-page mode and its pixel-diff-only limitation, which keeps it from being fully complete.

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 input schema has 100% description coverage for all nine parameters, so the schema already explains dir, url, selector, threshold, includeImages, and the rest. The prose adds no parameter-level details beyond the workflow, so the baseline of 3 applies.

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 uses specific verbs and resources: render an HTML file in Chromium, pixel-diff it against the Figma reference, and check element positions with IoU, paint order, and clipping. That clearly separates it from figma_convert and figma_inspect, which handle conversion and inspection rather than rendered verification.

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?

It gives a clear iterative workflow: edit the HTML based on the correction and call again, and read diff.png when the numbers alone are insufficient. It does not explicitly name when not to use it or point to sibling tools, so it stops short of full when/when-not guidance.

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