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

With no annotations, the description carries the full burden. It discloses the return format (APOM tree), compact vs full format, internal selector registration, cache refresh requirement, token efficiency, and clickTarget legend. It doesn't discuss potential errors or side effects, but as a read tool this is reasonably transparent.

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 well-structured, front-loading the core purpose. Every sentence provides useful information (format, IDs, refresh, efficiency, legend). It's longer than typical, but the content earns its place given the tool's complexity.

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 tool with 9 parameters and no output schema, the description explains the return structure, element ID usage, refresh semantics, and format options. It gives enough context for an agent to use it effectively. Minor gaps exist around error behavior and full debug format details, but overall it's complete enough.

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 the baseline is 3. The description adds some context beyond the schema (e.g., refresh after clicks, compact format), but doesn't need to re-explain parameters since the schema already documents them effectively.

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 states 'PRIMARY tool for reading page state' with a specific verb and resource, and distinguishes it from sibling tools like screenshot and getElementDetails. It clearly conveys the tool's role and scope.

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?

Provides clear context on when to use (primary read tool), and includes actionable guidance like 'Use refresh:true after clicks' and using element IDs with click/type tools. It does not explicitly name alternatives or when-not-to-use, but the 'PRIMARY' positioning and efficiency note imply the intended usage.

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?

No annotations are provided, so the description bears the full burden. It discloses that the tool appends to existing files and describes two Page Object modes, but omits the 'generate' mode behavior (separate POM creation) and does not detail failure conditions or side effects beyond appending. This is adequate but has clear gaps.

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 concise, front-loaded sentences that immediately state the primary purpose and then provide key usage distinctions. No wasted words.

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?

With 12 parameters and full schema coverage, the description captures the core workflow (append to existing, use export for new) and key mode differences. It doesn't explain all modes, but the schema fills in details. No output schema is needed for an append operation.

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%, giving a baseline of 3. The description adds meaningful context for targetFile (must exist) and clarifies pageObjectMode values like 'generate-integrated' and 'use-existing', going beyond the schema's simple descriptions.

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 clearly states the tool appends scenario code to an existing file, using a specific verb and resource. It also distinguishes from the sibling tool by explicitly directing users to exportScenarioAsCode for new files.

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?

Provides explicit alternative guidance: 'Use exportScenarioAsCode for new files' and implies this tool is for existing files. Also explains Page Object integration modes, giving clear context for when to use different configurations.

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 full burden of behavioral disclosure. It adds two meaningful behaviors: 'Handles React/Vue/Angular events' and 'waits for navigation.' However, it omits other significant behaviors like waitForSelector, autoAnalyzeAfter, and waitForRouteChange, which are explained only in the schema. This is adequate but not comprehensive.

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 two concise sentences: the first states the action and identification methods; the second covers two key behaviors. Both sentences earn their place, and the content is front-loaded with the core action. There is no fluff or 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?

The tool has 9 parameters and no annotations or output schema, so the description must compensate for complexity. While the schema is 100% covered, the main description does not summarize advanced features like waitForSelector or autoAnalyzeAfter, which are essential for dropdowns/popups. The description is sufficient for basic clicks but incomplete for the tool's full capability.

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 the baseline is 3. The description adds value by specifying 'APOM ID (preferred)' over CSS selector, which is not explicit in the schema. It also implies the id/selector trade-off through framework event handling, adding semantic meaning beyond the raw parameter list.

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 clearly states the tool's purpose: 'Click element by APOM ID (preferred) or CSS selector.' It identifies the verb ('Click'), the resource ('element'), and the identification methods. It also distinguishes from sibling tools like type, hover, and pressKey by focusing on clicking and framework event handling.

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 context: clicking elements with APOM ID preferred over CSS selector, and it handles framework events and waits for navigation. It does not explicitly mention alternatives or exclusions, but the tool's name and sibling list make the use case obvious (e.g., use click for mouse clicks, not for typing). This earns a 4 rather than 5.

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 full burden of disclosing behavior. It only says 'Pixel-perfect validation' without explaining whether the tool performs a read-only comparison, requires a live page, makes network calls to Figma API, or what happens on mismatch. No side effects, auth prerequisites, or failure behavior are disclosed.

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 two concise sentences with no filler. The main verb and object are front-loaded in the first sentence, and the second sentence adds context ('Pixel-perfect validation'). It is appropriately sized for a tool with clear purpose, though slightly vague tone costs a point.

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 tool has 6 parameters, no output schema, and no annotations, yet the description is minimal. It fails to explain what the tool returns (e.g., a diff percentage or pass/fail), preconditions (e.g., element must exist and be visible), or how threshold and figmaScale affect the comparison. This is a substantial gap for a tool with this complexity.

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 the schema already documents all 6 parameters (fileKey, nodeId, selector, threshold, figmaScale, figmaToken) with meaningful descriptions. The tool description adds no semantic value beyond the schema, but the baseline of 3 applies because the schema does the heavy lifting.

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 clearly states the tool's function: 'Compare Figma design with browser element' — a specific verb and both resources. 'Pixel-perfect validation' adds scope. This clearly distinguishes it from sibling tools like getFigmaFrame (retrieves frame) or screenshot (captures browser), as none perform comparison.

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 implies a validation use case but provides no explicit guidance on when to use this tool vs alternatives like getFigmaFrame, screenshot, or getComputedCss. There are no exclusions or prerequisites stated, leaving the agent to infer context from the schema alone.

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 full burden. It discloses that the tool fetches node structure and rendered image and returns simplified design data with AI instructions, which is transparent about its internal process. However, it lacks explicit statements about side effects, error conditions, or prerequisites like authentication.

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?

Three concise sentences lead with the core purpose, followed by the process and focus area. Each sentence adds distinct value with no filler or 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?

The description outlines the high-level workflow but does not detail the exact structure of the returned 'simplified design data' or possible limitations. With no output schema, this leaves some ambiguity about the response format, though it covers the tool's main function adequately.

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 provides 100% coverage for all five parameters, so the schema fully documents them. The description adds no parameter-specific details beyond what the schema already states, so it merits the baseline 3.

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?

Clearly states it converts Figma designs to React/Tailwind code, with a specific verb, resource, and outcome. The process description (fetches node structure and rendered image, returns design data with AI instructions) distinguishes it from sibling tools like getFigmaFrame or getFigmaSpecs.

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 implies use for converting Figma designs to React/Tailwind code and mentions its focus on React/Tailwind styling, offering some context. However, it does not explicitly state when to use this tool over related Figma tools, nor does it provide exclusions or mention alternatives.

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?

No annotations are provided, so the description carries the full burden. It fails to disclose whether deletion is permanent, requires permissions, or what side effects occur (e.g., deleting secrets). The mention of 'secrets' is vague and adds ambiguity.

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 single, concise sentence with no filler. It communicates the core purpose efficiently, though it lacks additional useful context.

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 mutation tool with no annotations or output schema, the description is too thin. It does not explain permanence, confirmation, or the nature of 'secrets', leaving the agent uncertain about the operation's effects and safety.

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 fully describes the sole parameter 'name' with 'Scenario name', achieving 100% coverage. The description does not add extra meaning beyond the schema, so a baseline score of 3 is appropriate.

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 clearly states the action ('Delete') and the resource ('scenario and secrets'), which distinguishes it from other scenario-related tools like listScenarios or exportScenarioAsCode. It lacks explicit distinction from potential delete-like siblings, but no such siblings exist.

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?

No usage context, prerequisites, or alternatives are mentioned. The tool is simple enough that usage is implied (when you want to delete a scenario), but no explicit guidance is provided.

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 full burden for behavioral disclosure. It does not explain how the drag is performed (e.g., mousedown/mousemove/mouseup sequence), what happens on failure, or effects of distance/duration. The only behavioral hint is the mode selection, which is already in the schema.

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 four short, front-loaded sentences. No filler words; each sentence adds actionable information (purpose, use cases, mode guidance, alternative tool). Excellent structure for quick comprehension.

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 drag tool with no output schema and no annotations, the description provides essential usage context but lacks depth on behavioral nuances (e.g., coordinate origins, supported element types, error cases). It is adequate but leaves gaps that a more detailed description could fill.

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 the baseline is 3. The description adds value by explaining when to use 'synthetic' mode (JS libraries) and mentions scrollHorizontal as an alternative for scrollbars, enriching the understanding of parameters like mode and direction.

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 clearly states 'Drag element in any direction' with specific use cases (maps, charts, SVG, canvas, sliders), distinguishing it from sibling tools like scrollHorizontal and click. The verb and resource are specific and unambiguous.

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?

Provides concrete usage guidance: use mode='synthetic' for JS libraries and use scrollHorizontal for scrollbars. This clarifies when to use this tool versus alternatives, though it doesn't explicitly list all exclusion cases.

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?

No annotations are provided, so the description carries the full burden of disclosing behavior. It says 'Check connection' but does not mention whether the tool has side effects, what it returns, or what happens if the connection is missing. The name 'enableRecorder' also hints at a state change that the description does not confirm or deny.

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 two sentences long and front-loads the core purpose. The second sentence adds a practical usage note. It is appropriately sized, though some wording could be more precise; it does not over-explain.

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 lacks essential behavioral context for a simple diagnostic tool: no expected return value, no failure behavior, and no mention of prerequisites. The ambiguity between 'enable' and 'check' further reduces completeness, and with no output schema or annotations, the description should provide more detail.

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 zero parameters, so the baseline score is 4. No additional parameter details are needed, and the description does not introduce any parameter-related confusion.

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 clearly states a specific action ('Check ChromeTools Extension connection') and context ('for scenario recording'), which differentiates it from tools like startRecording or stopRecording. However, the name 'enableRecorder' suggests an enabling action, while the description only says 'check', creating slight ambiguity about the tool's actual effect.

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 implies the tool should be used to verify the extension connection before recording, and provides an alternative ('Use Chrome Extension popup (CT icon) for recording'). It does not explicitly state when to avoid using this tool or compare it to sibling tools, so the guidance is mostly implicit.

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?

No annotations are provided, so the description carries the full burden. It explains the Strategy Pattern mechanism and the prerequisite of calling analyzePage(), which is useful context. However, it does not disclose return format, error behavior, or potential side effects, despite examples showing mutating actions like type and check.

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 well-organized with a clear intro, prerequisite callout, model list, and examples. Each section adds useful information without wasting words. It is slightly longer than necessary but remains focused and readable.

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 model-driven complexity and the absence of an output schema, the description should explain return values and error behavior. It adequately covers the discovery workflow (analyzePage) and usage patterns, but leaves out critical execution outcomes (e.g., success/failure, return data), making it incomplete for an agent to use confidently.

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 covers all four parameters, but the description adds valuable concrete examples mapping actions to params (e.g., type→text, SetDate→date, selectOption→value, check→no params). This goes beyond the schema's descriptions and clarifies usage.

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 clearly states the tool's purpose: 'Universal tool to execute any model-specific action on element.' It distinguishes itself from specific sibling tools like click/type by being a generic action executor tied to element models. Examples further clarify the resource and action scope.

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?

Provides explicit guidance to use analyzePage() first to discover available actions in the 'models' map. It also illustrates usage with multiple examples across different model types. However, it doesn't explicitly state when not to use this tool versus the specialized sibling tools, though that is implied by its universal nature.

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?

No annotations are present, so the description must disclose behavior. It mentions dependency resolution as a behavioral trait, but it does not disclose potential side effects of executing a scenario, whether it modifies browser state, or error/failure behaviors. This is a significant gap for a tool that causes actions.

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 consists of two concise sentences with no redundant content. The first sentence delivers the core purpose, and the second adds a valuable usage tip. It is front-loaded and every word earns its place.

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 complex execution tool with no output schema and no annotations, the description omits critical operational context: return values, side effects, error handling, and how execution fits into broader workflows. The schema covers parameters, but the behavioral and outcome context is severely under-specified.

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%, and the schema already thoroughly describes all four parameters, including projectId's disambiguation role. The description only restates the projectId tip without adding new parameter-level meaning, so it stays at the baseline for high 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 clearly states the tool executes a scenario by name and includes dependency resolution, using a specific verb and identifying the resource. This distinguishes it from sibling tools like deleteScenario or saveScenario. The disambiguation tip adds precision.

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 a parameter-specific guideline for projectId but does not explicitly state when to choose this tool over alternatives like executeScript or deleteScenario. Usage context is implied by the name and core action, but no exclusions or alternative comparisons are given.

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 full burden. It discloses the key risk: may break React/Vue/Angular synthetic events. It also sets expectations as a destructive/advanced tool by labeling it LAST RESORT. However, it does not mention other possible side effects (e.g., page navigation, state mutation beyond the script's scope) or return value behavior, which would be useful for a raw script execution tool.

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 compact, front-loaded with the critical warning, and every sentence provides actionable guidance. It uses bullets-like structure with 'NEVER use for' list, making it easy to parse. No wasted words; it earns its 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?

The tool has no output schema, and the description does not explain what the script execution returns (e.g., the script's result value, whether the result is serialized, or how errors are surfaced). Given the tool's power and fallback nature, this omission is a gap. The usage context is well-covered, but the execution result and post-conditions are left ambiguous, so completeness is below the ideal for a high-risk tool.

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 the baseline is 3. The description does not add additional parameter-level semantics beyond what the schema already provides (script code, timeout, waitAfter, screenshot). It does not compensate with extra detail, but the schema is sufficient, so a 3 is appropriate.

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 name 'executeScript' and description clearly indicate this tool executes JavaScript. It explicitly positions itself as a LAST RESORT fallback and distinguishes itself from specialized sibling tools by listing what it should NOT be used for (clicking, typing, etc.). The verb+resource+scope is clear and differentiates from alternatives.

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 guidance: use ONLY when ALL specialized tools failed, and lists specific alternatives for common actions (click, type, scrollTo, analyzePage, etc.). It also advises against using it with React/Vue/Angular due to synthetic event breakage. This is a model of clear when-to-use and when-not-to-use 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 provided, the description carries the full burden. It discloses that the tool targets new files and describes POM integration behaviors, which adds context. However, it doesn't state whether the tool writes a file, returns code, or what happens if the file already exists, leaving side effects unclear.

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 two sentences, front-loaded with the core purpose, and includes necessary differentiation and mode explanations without excess. It could be slightly better organized, but it is appropriately concise.

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 tool with 8 parameters and no output schema, the description covers core purpose and main mode options but omits important behavior like return value, file creation details, or handling of optional parameters. It is adequate for a basic understanding but not fully complete for an agent deciding to invoke it.

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 the baseline is 3. The description repeats some enum semantics already present in the schema (e.g., pageObjectMode explanations) and adds the 'NEW file' context, but it doesn't significantly enhance understanding of parameters like cleanSelectors or includeComments beyond what the schema provides.

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 clearly states the tool exports a scenario as test code for a NEW file, which is a specific action on a specific resource. It explicitly distinguishes from appendScenarioToFile, making the purpose unambiguous and differentiating it from sibling 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?

It directly says 'Use appendScenarioToFile for existing files,' providing a clear alternative for the append case. It also explains the different pageObjectMode options, giving context on when to choose each mode. However, it doesn't explicitly mention when not to use this tool for other scenarios, but the key alternative is named.

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?

No annotations are provided, so the description must disclose all behavioral traits. It only says 'Returns matching requests with full details,' which suggests a read operation. However, it omits the destructive 'clear' behavior (from the schema), the default types (Fetch, XHR), and any side effects. The tool could clear the network log if clear=true, which is a significant undisclosed 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?

The description is a single concise sentence that conveys the core purpose and return value without any fluff or redundant information. It is front-loaded and every word adds value.

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 simple filter tool with 3 parameters and full schema coverage, the description is adequate but lacks key context. It does not mention that the tool can also filter by request types, nor does it disclose the clear side effect or default types. Without an output schema, the return format is vague ('full details'), but the tool's simplicity keeps completeness at a moderate level.

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 describes all parameters with 100% coverage, so the baseline is 3. The description does not add any parameter-specific meaning beyond the schema. It mentions URL pattern but doesn't elaborate on the 'types' or 'clear' parameters, which are already explained in 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?

The description clearly states the verb 'Filter' and the resource 'network requests' with the specific criterion 'by URL pattern.' This distinguishes it from sibling tools like 'listNetworkRequests' (which lists all) and 'getNetworkRequest' (which retrieves one). The purpose is unambiguous.

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 implies the tool is for filtering network requests, but it does not explicitly state when to use it over alternatives like 'listNetworkRequests' or provide any exclusions. The usage context is only implied via the tool name and description, with no mention of the 'types' parameter or clear flag that would affect usage.

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?

No annotations are present, so the description carries the burden. It discloses that the tool can 'optionally perform actions directly', implying non-read-only behavior, but does not elaborate on side effects (e.g., clicking may navigate) or state that the default is read-only. This is a partial disclosure.

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 four sentences, front-loads the core purpose, and provides useful guidance. Minor redundancy exists between 'get their selectors' and 'Returns working selectors', but no fluff is present and the structure is logical.

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 tool has a nested action object and no output schema. The description covers the main use case and the alternative to executeScript, but it does not explain the return format (e.g., array of selectors) or that actions apply to the first match (only mentioned in the schema). Some operational details 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%, so the baseline is 3. The description adds semantic value by specifying 'visible text content' for the text parameter, but it does not clarify exact, caseSensitive, or action semantics beyond the schema's brief descriptions.

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 a specific verb ('Find') and resource ('elements by visible text content'), and states the output ('get their selectors'). It explicitly distinguishes from executeScript by saying 'Use this INSTEAD of executeScript', which clarifies its unique role.

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: 'when you need to find elements', and names an alternative: 'INSTEAD of executeScript'. It also states that returned selectors work with click/type tools, giving downstream usage context.

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 full burden. It goes beyond a generic statement by enumerating technical behaviors: $ref resolution, enums, allOf/oneOf, and nested objects. It also discloses the side effect of generating model files, but stops short of mentioning overwrite behavior or output location.

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 three sentences, each earning its place. It front-loads the core purpose, then adds capabilities and usage timing. No redundancy or fluff.

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 tool has 8 parameters and no output schema or annotations. The description covers the core functionality and dependency on loadSwagger, but leaves out output specifics (e.g., where files are written, return value, error behavior). It is adequate but not fully complete for a tool of this complexity.

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?

All 8 parameters have schema descriptions (100% coverage), so the baseline is 3. The description does not add additional context for any specific parameter beyond what the schema provides; it only references languages and styles in a general way, which the schema already caps.

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 a specific verb+resource: 'Generate typed data models from OpenAPI/Swagger spec.' It names target output types (TypeScript interfaces/types, Python dataclasses/pydantic/TypedDict) and source schemas, clearly distinguishing it from sibling tools like loadSwagger.

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 final sentence 'Use after loadSwagger to generate model files' provides clear context for when to invoke this tool, directly referencing a sibling as a prerequisite. It does not explicitly state exclusions or alternatives, but the relationship to loadSwagger is unambiguous.

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 full burden. It discloses analysis, element extraction, grouping, and helper generation, but leaves ambiguous whether the tool writes files, returns code to the UI, or requires a prior analyzePage call. The lack of side-effect or prerequisite disclosure is a significant gap.

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?

Three sentences, front-loaded with the primary purpose. Each sentence adds distinct value: generation of POM, the analysis/extraction/grouping behavior, and supported frameworks. No redundancy 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?

The tool is moderately complex with four parameters and no output schema. The description explains what the generated code does at a high level but omits how the code is returned/stored and whether a prior analysis step is mandatory. This incomplete output/usage contract lowers completeness.

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?

All four parameters have schema descriptions (100% coverage), so baseline is 3. The description adds minor context (grouping to sections, framework support) but doesn't clarify parameter values or interactions beyond what the schema already provides.

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?

Description opens with a specific verb-resource pair: 'Generate Page Object Model (POM) class from current page analysis.' It goes on to detail the analysis and generation behaviors (extracting elements, grouping by sections, framework-specific code), which clearly distinguishes it from sibling tools like generateApiModels or convertFigmaToCode.

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 phrase 'from current page analysis' implies a workflow dependency but does not explicitly state when to use this tool versus alternatives like analyzePage or other generators. It lists supported frameworks but gives no exclusions, alternatives, or prerequisites, so usage context is only implied.

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?

No annotations are provided, so the description must carry the burden. The verb 'Get' implies a read-only operation, and the description lists the categories of data returned. However, it does not disclose error behavior, return format, or any side-effect potential, which is a gap but not a contradiction.

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 single, concise sentence that is front-loaded with the primary action and resource, followed by a colon-separated list of the included properties. There is no redundant wording, 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?

For a simple single-parameter tool with no output schema, the description adequately conveys the return categories (dimensions, positioning, margins, padding, borders). It could be more explicit about the return structure (e.g., units or coordinate system), but overall it is sufficiently complete for an agent to understand the tool's basic function.

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% coverage (selector described as 'CSS selector'), so the baseline is 3. The description adds no additional meaning beyond the schema, but it does imply that the selector refers to an element from which the box model is obtained.

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 clearly states the tool's purpose with a specific verb ('Get') and resource ('element box model'), and enumerates the contained data (dimensions, positioning, margins, padding, borders). This is more specific than a generic 'get element info' and differentiates from siblings like getComputedCss, though it does not explicitly mention alternatives.

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 no guidance on when to use this tool versus alternatives like getComputedCss or getElementDetails. There are no stated scenarios, exclusions, or prerequisites, leaving the agent to infer usage from the name and description alone.

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?

No annotations are provided, so the description should carry the full burden. While 'Get' implies a read operation, the description does not explicitly confirm it is non-mutating, nor does it disclose any potential side effects, performance considerations, or return format. It restates the tool's function without adding behavioral insights.

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 two concise sentences, front-loaded with the core purpose and followed by the primary use case. No extraneous words.

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?

With no output schema and no annotations, the description should explain return values and edge cases. It does not describe the response structure or any limitations. Given the tool's simplicity and full parameter documentation, this is an acceptable but not complete description.

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 schema documents all four parameters clearly. The description adds no additional parameter guidance beyond the schema, so it meets the baseline for full 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 clearly states 'Get computed CSS styles for element', using a specific verb and resource. It distinguishes itself from sibling tools like getBoxModel and getFigmaStyles by specifying 'computed CSS styles'.

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 adds 'For layout debugging and responsive design', providing clear usage context. However, it does not explicitly mention when not to use it or point to alternative tools.

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?

No annotations are provided, so the description carries full burden for behavioral disclosure. It only states 'Get browser console messages' and gives a purpose, but does not mention that the 'clear' parameter can delete messages after reading, nor does it describe any return format or side effects. The description is insufficient for an unannotated tool.

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 two short, front-loaded sentences with no filler: 'Get browser console messages. For debugging JS errors and tracking behavior.' Every word serves a purpose.

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?

With no output schema, the description should clarify return values, but it does not. It also omits behavioral nuances such as the clearing side effect. For a simple tool with two optional parameters, the description is too sparse to be 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?

Schema coverage is 100%, with both parameters ('clear' and 'types') having descriptions. The tool description itself adds no parameter-level meaning, so the baseline score 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 a specific verb 'Get' and a clear resource 'browser console messages', followed by a stated purpose 'For debugging JS errors and tracking behavior.' This unambiguously distinguishes it from sibling tools like listNetworkRequests or listTabs.

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 a clear usage context: 'For debugging JS errors and tracking behavior.' This tells the agent when to use the tool, though it doesn't explicitly mention alternatives or exclusions relative to other debugging tools.

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?

No annotations are provided, so the description carries the burden. It discloses what the tool returns (bounds, CSS selector, position, attributes, computed styles) and mentions the optional children tree analysis. However, it doesn't explicitly state that the operation is read-only or non-destructive, nor does it mention caching behavior (relevant to the 'refresh' parameter) or any side effects. The 'Get' verb implies read-only, but without annotations, more explicit disclosure would be ideal.

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 concise, consisting of three sentences that front-load the core purpose, then describe the output, and finally state when to use it. Every sentence adds value, with no redundancy or fluff. It is well-structured and easy to scan.

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 no annotations, no output schema, and four parameters, the description does a solid job of covering the essential context: what it does, what it returns, and when to use it. The schema handles parameter details fully. It could be more complete by noting error behavior or preconditions, but for a read-only retrieval tool, it adequately covers invocation and purpose.

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 provides 100% coverage with descriptions for all four parameters, so the baseline is 3. The description adds some context by explaining the APOM ID usage and the children analysis feature, which aligns with the 'id' and 'analyzeChildren' parameters, but it doesn't add significant new semantic information beyond the schema. The description's mention of analyzePage output simplified context helps clarify the 'id' source, earning a 3 rather than a lower score.

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 clearly states the tool's purpose: 'Get detailed information about element by its APOM ID.' It specifies the resource (element) and the action (get details), and differentiates itself from siblings by mentioning it returns full details including bounds, CSS, position, attributes, and computed styles, plus optional children tree analysis. This distinguishes it from more specialized tools like getBoxModel or getComputedCss.

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 explicitly tells when to use the tool: 'Use this when analyzePage output was simplified and you need complete information about specific element or analyze specific sections in detail.' This provides clear context and references a sibling tool (analyzePage). However, it doesn't explicitly mention when not to use it or name alternative tools for specific scenarios, so it misses the full 'when-not/alternatives' rubric.

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 provided, the description carries the full burden. It fails to explicitly state that this is a read-only operation without side effects, nor does it mention authentication requirements or error behavior. It only describes the output, leaving safety and side-effect assumptions to the agent.

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 two concise sentences, front-loaded with the primary purpose, and every word adds value. It is appropriately sized for a simple tool with no unnecessary 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 simple extraction tool with a sparse schema and no output schema, the description adequately covers what the tool does and what it returns. It could clarify whether the palette is for the whole file or a selection, but it is sufficient for basic usage.

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 covers 100% of the parameters (fileKey and figmaToken) with clear descriptions, so the description does not need to add extra parameter semantics. It adds no new parameter-level information, but the schema is sufficient.

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 clearly states the action ('Extract color palette') and describes the output (unique colors with hex, rgba, usage count). This distinguishes it from sibling tools like getFigmaStyles or getFigmaFrame, which have different purposes.

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 context is implied by the name and description—use this when needing color palette data from a Figma file—but no explicit guidance is given about when to prefer this over alternatives, nor are any exclusions or preconditions mentioned.

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?

No annotations are provided, so the description bears full responsibility for behavioral disclosure. It mentions the action but does not describe the return format, authentication behavior beyond the optional token, potential large payloads, or any side effects. Minimal behavioral context beyond the verb.

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 short and front-loaded with the main action. The second clause ('For extracting design system') is slightly redundant with the parenthetical '(Design System)' but still adds intent clarification. Overall, it is concise with minor redundancy.

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?

There is no output schema and no annotations, so the description should explain what the tool returns and any important operational context. It does not; the output format is ambiguous, and the tool is not contextualized within the Figma sibling family. The description is adequate only for a simple read operation.

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 covers 100% of parameters with useful descriptions ('File key or URL' and 'API token (optional)'). The description adds no additional parameter guidance, so it meets the baseline of 3 for high 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 clearly identifies the action ('Get all components') and the target ('from file'), with a parenthetical hint about design systems and a purpose clause. It distinguishes itself from sibling tools like getFigmaStyles by focusing specifically on components.

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 a general purpose ('For extracting design system') but does not explicitly state when to use this tool versus alternatives such as getFigmaStyles or getFigmaColorPalette, nor does it mention exclusions. The guidance is implied rather than explicit.

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 must disclose behavior, but it only mentions requirements. It does not explain the return format (e.g., base64 PNG data, URL), failure modes, or side effects. The statement about token requirement is also ambiguous given the schema marks it optional.

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?

Single, brief sentence states purpose and requirements without waste. Very economical and easy to parse.

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 tool without output schema and annotations, the description omits essential return value information and usage context. It is not complete enough for an agent to understand what the tool returns or when to prefer it over other Figma tools.

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 baseline 3 applies. The description adds little beyond the schema, except noting the requirement for token and IDs, which may conflict with the optional figmaToken parameter. It does not provide additional semantic detail for scale or format.

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 clearly states the tool exports a Figma frame as PNG, using a specific verb and resource. However, it mentions PNG only while the schema supports jpg and svg, slightly narrowing the actual functionality. It distinguishes from sibling tools like getFigmaSpecs.

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?

No guidance on when to use this tool versus alternative Figma tools like getFigmaSpecs or listFrames. The only context is the requirement for an API token and file/node IDs, which is more of a prerequisite than a usage guideline.

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?

No annotations are provided, so the description carries the full burden for behavioral disclosure. It only lists the data types extracted and does not mention authentication requirements (the figmaToken parameter is optional but not explained in context), network calls, return format, or potential side effects. This is minimal and leaves the agent guessing about the tool's operation.

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 single sentence, tightly worded, and front-loads the purpose. Every word contributes, and the list of spec types adds useful detail without bloat. It is a model of conciseness.

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 simple extraction tool with fully documented schema, the description is minimally adequate. However, without an output schema, the agent is left to infer the return structure, and the absence of usage guidance or behavioral details (e.g., whether this replaces or complements sibling tools) leaves gaps. It is enough to understand the basic purpose but not fully complete for robust selection.

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 already provides 100% coverage with descriptions for each parameter (nodeId, fileKey, figmaToken). The description adds no additional parameter-level meaning beyond the schema, so the baseline of 3 is appropriate.

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 a specific verb 'Extract' and clearly identifies the resource ('design specs from Figma') while enumerating the categories (colors, fonts, dimensions, spacing). This provides a clear sense of the tool's function, though it does not explicitly differentiate itself from overlapping siblings like getFigmaStyles or getFigmaColorPalette, which might also extract similar data.

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?

There is no guidance on when to use this tool versus the many Figma-related siblings (e.g., getFigmaStyles, getFigmaFrame, getFigmaColorPalette). The description simply states the action without indicating whether this is the comprehensive extractor or if specialized tools should be preferred for specific spec types.

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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does not mention authentication requirements, rate limits, pagination, or any side effects. Although 'get' implies a read-only action, the description lacks explicit safety context and does not go beyond the basic action.

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 extremely concise: two short sentences that immediately state the action and the purpose. Every word earns its place, making it easy to parse quickly.

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 tool has a simple interface with two parameters and no output schema, so the description should ideally convey what the return value looks like or any caveats. It explains the scope (color, text, effect, grid) and purpose, but does not mention return format or file-level limitations. This is adequate but not 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 already provides 100% coverage for both parameters (fileKey and figmaToken). The description adds no additional parameter-level meaning beyond what the schema states, so it appropriately relies on the schema. Baseline 3 is warranted.

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 clearly states the tool gets all styles (color, text, effect, grid) and explicitly ties it to extracting design tokens. The verb 'get' plus the resource 'styles' is specific and distinguishes it from sibling tools like getFigmaColorPalette or getFigmaComponents.

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 phrase 'For extracting design tokens' provides a clear context for when to use this tool. It does not explicitly exclude alternatives or name when-not-to-use, but the stated purpose is enough to guide an agent toward selecting it for design token extraction.

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?

No annotations are provided, so the description carries the full burden. It discloses the return fields (headers, payload, response) and the dependency on requestId from listNetworkRequests. However, it does not mention error behavior, whether network recording must be active, or that the operation is read-only (though implied by 'Get'). This is adequate but not rich.

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 two short sentences, front-loaded with the main action and details. Every word earns its place, with no redundancy or unnecessary 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 a single-parameter tool with no output schema, the description sufficiently covers purpose, parameter source, and partial return shape. It lacks explicit error handling or edge-case behavior, but the low complexity and simple getter nature make this an acceptable level of completeness.

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 fully documents requestId with 'Request ID' (100% coverage), so the baseline is 3. The description adds contextual value by specifying 'Use requestId from listNetworkRequests,' telling the agent where to obtain a valid ID, which enriches parameter understanding beyond 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?

The description clearly states the tool's function: 'Get network request details (headers, payload, response).' It specifies a concrete verb and resource and distinguishes itself from sibling tools like listNetworkRequests by focusing on single-request details and referencing the list tool for obtaining IDs.

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 a clear workflow hint: 'Use requestId from listNetworkRequests.' This tells the agent when to use this tool (after listing) and where to get the required parameter. It doesn't explicitly mention alternatives, but the context is sufficiently clear for a read operation.

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 full burden for behavioral disclosure. It states the tool returns state fields, and 'Get' implies a read-only operation, but it doesn't clarify preconditions like whether the recorder must be enabled/started, or what happens if it isn't.

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 single, well-structured sentence that front-loads the purpose and lists the return fields. Every word contributes meaning, with no redundancy or unnecessary detail.

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 zero-parameter, no-output-schema tool, the description is nearly complete: it enumerates all expected return fields. However, terms like 'action count' and 'current tab' are slightly ambiguous without further type or format details, though this is a minor gap.

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 tool has zero parameters, so the schema is trivially complete (100% coverage). The description doesn't need to explain parameters, earning the baseline score of 4 for zero-parameter tools.

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 a specific verb ('Get') and resource ('current recorder state'), then enumerates the exact returned fields: isRecording, isPaused, action count, current tab. This clearly distinguishes it from sibling recording-control tools like startRecording and stopRecording.

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 phrase 'Get current recorder state' clearly communicates the tool's purpose and implies when to use it, but it doesn't explicitly mention exclusions or alternative tools. No direct sibling tool competes for this functionality, so this is adequate.

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?

No annotations exist, so the description alone must disclose behavioral traits. It only states that it retrieves details, implying read-only, but does not mention error behavior, secret handling defaults, or whether it requires any permissions. This is a significant gap for a tool without annotations.

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?

Single sentence front-loads the purpose and lists the data returned. No filler or 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 simple read-only getter with two well-documented parameters, the description covers the main purpose and return content (actions, parameters, dependencies). However, lack of output schema and annotations means the description should also clarify error handling and secret inclusion behavior, which it partially inherits from the schema but doesn't explicitly state. Still, it's adequately complete for basic use.

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 already documents both parameters fully: 'name' as scenario name and 'includeSecrets' with default. The description adds no additional meaning to either parameter, merely using the word 'parameters' generically, which could confuse with scenario parameters vs tool parameters.

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?

Clear verb+resource: 'Get scenario details' specifies the action. The additional list 'actions, parameters, dependencies' clarifies the scope of details, distinguishing from siblings like listScenarios or searchScenarios which focus on listing/searching rather than fetching full details of a specific scenario.

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 implies use when you need full scenario details by name, but it doesn't explicitly state alternatives or exclusions. There are siblings like listScenarios and searchScenarios, but the description's mention of 'details' suggests the use case. Still, no explicit guidance on when to use this vs alternatives.

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 provided, the description carries the full burden of behavioral disclosure. The verb 'Get' implies a read-only operation, and the description specifies the two outputs (size and pixel ratio). However, it does not explicitly state that there are no side effects, nor does it describe the exact return format, which would be valuable for transparency.

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 exceptionally concise: two short sentences that front-load the action and purpose. Every word earns its place, with no filler or redundant content.

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 low complexity (no parameters, no output schema), the description adequately covers the essentials: what it does and a key use case. It lacks details about return formatting or edge cases, but for a simple getter tool, this is largely sufficient. The absence of an output schema slightly raises the bar, but the description's explicit mention of the returned values helps bridge that gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.