IteraTools MCP

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Most tools have distinct purposes targeting different domains like audio, images, PDFs, web, and utilities, with clear boundaries. However, there is some overlap between image_fast and image_generate (both generate images with different models/speeds) and between scrape and browser_act (both involve web extraction), which could cause minor confusion for agents.
Naming Consistency5/5
Tool names follow a consistent snake_case pattern throughout, with clear verb_noun or noun_verb structures (e.g., audio_transcribe, browser_act, chart_generate). There are no deviations in style or convention, making them predictable and readable.
Tool Count3/5
With 25 tools, the count is borderline high for a general-purpose utility server, as it covers many disparate domains (e.g., audio, images, web, crypto, weather). While each tool seems functional, the scope feels broad, potentially making the set feel heavy or unfocused compared to more specialized servers.
Completeness4/5
The tool set covers a wide range of common utility tasks across multiple domains, with no obvious major gaps for the stated purpose of general automation and processing. Minor gaps exist, such as no tool for editing images beyond resizing/background removal or no tool for summarizing text, but agents can likely work around these.
Average 3.2/5 across 25 of 25 tools scored. Lowest: 2.6/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
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 pricing ($0.003) but fails to specify critical behavioral traits: the return format (URL, file ID, or binary data), file size limits, supported CSS, or error handling for malformed HTML.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The single sentence is front-loaded with the action and includes cost information efficiently. However, given the lack of schema descriptions and output schema, it is inappropriately brief—verging on under-specification rather than effective conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, no annotations, and 0% parameter coverage, the description is incomplete. It omits essential information about what the tool returns (critical for a generation tool) and parameter validation rules, leaving significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, requiring the description to compensate. While it identifies the 'html' parameter's general purpose (HTML content), it lacks constraints, expected format (full document vs fragment), encoding details, or size limits necessary for correct invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb (Generate), resource (PDF), and input format (HTML content). The name and verb distinguish it from sibling pdf_extract, though it doesn't explicitly mention this distinction in the text.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides no guidance on when to use this tool versus alternatives (e.g., when to use pdf_extract), no prerequisites, and no exclusions. The cost hint ($0.003) is useful but does not constitute usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. While cost is disclosed, critical behavioral traits are missing: aspect ratio handling (stretch vs crop), output format/location, file size limits, and whether the operation is idempotent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with no redundant words. Action and cost are front-loaded. However, extreme brevity contributes to information gaps given the lack of schema descriptions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, yet description fails to indicate return format (resized image URL? binary data?). With zero schema coverage and no annotations, the description should elaborate on parameter constraints and output behavior, but remains minimal.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage. Description mentions 'specified dimensions' which vaguely maps to width/height parameters, but fails to specify units (pixels?), valid ranges, or that URL must be publicly accessible. Insufficient compensation for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
States specific verb 'Resize' and resource 'image' with scope 'to specified dimensions'. Cost disclosure ($0.001) adds useful context. Does not explicitly differentiate from sibling 'image_fast', but the core 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.
Usage Guidelines2/5
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 alternatives like 'image_fast', or prerequisites such as URL accessibility requirements. Lacks exclusion criteria or preconditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only provides pricing information ($0.001) but omits critical details like output format (PNG/JPG), return type (URL vs base64 vs binary), and whether the generated image is persisted or transient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with no wasted words, though the parenthetical cost information slightly disrupts the functional clarity and might be better placed in annotations.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Without an output schema, the description should specify what the tool returns (e.g., image URL, base64 data, file path). It also leaves the 'size' parameter undocumented, making the definition incomplete for an image generation tool where output specifications are critical.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 50% description coverage (only 'text' is documented). The description fails to compensate for the undocumented 'size' parameter or add context about valid size ranges, units (pixels), or behavior when size is omitted despite the default value in schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates a QR code image with a specific verb and resource. However, it does not explicitly differentiate from sibling tools like 'image_generate' or 'url_shorten' that could serve similar use cases for encoding data or sharing links.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to prefer this tool over alternatives such as 'image_generate' or 'url_shorten', nor does it mention prerequisites, input constraints (e.g., maximum text length), or error conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only specifies 'current' (implying real-time data) but fails to disclose error handling for invalid coins, the return data structure/format, data source reliability, or rate limiting constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The single-sentence structure is appropriately brief and front-loaded. However, the '($0.001)' fragment creates confusion without clear context—if it indicates return precision or format, it should be explicit; if erroneous, it wastes the limited space.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (one optional parameter, no nested objects, no output schema), the description is minimally adequate. However, it lacks critical completeness for an API tool: the return value format (string, number, JSON object?) and currency denomination are unspecified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (the 'coin' parameter is fully documented with type, default, and examples). The description text does not mention parameters at all, but with high schema coverage, the baseline score of 3 is appropriate as the schema carries the semantic weight.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the core function using a specific verb ('Get') and resource ('cryptocurrency price'). It effectively distinguishes from non-financial siblings like audio_transcribe or image_generate. However, the parenthetical '($0.001)' is ambiguous—it may indicate precision, a price example, or a formatting hint—which slightly obscures the clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, nor does it mention prerequisites (e.g., API keys) or rate limits. While no siblings overlap functionally, the agent lacks explicit context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses pricing ('$0.001') which is valuable behavioral context not found in annotations or schema. However, with no annotations provided, the description fails to mention error handling (e.g., NXDOMAIN responses), caching behavior, rate limits, or return format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely brief single sentence with no redundant words. Every element serves a purpose (action, target, cost). However, the density leaves no room for parameter documentation, which is desperately needed given the empty schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Inadequate for a tool with zero schema coverage and no output schema. The description omits critical details: supported DNS record types, parameter formats, and return value structure. Relies entirely on the tool name being self-explanatory.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fails to compensate adequately. While it implies the 'domain' parameter, it completely omits documentation for the 'types' array parameter (which has a default value of ['A', 'MX', 'TXT']) and provides no guidance on valid record type strings.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb ('Lookup') and resource ('DNS records') with clear scope ('for a domain'). The tool name and description clearly distinguish this from siblings like 'search' or 'browser_act', though it doesn't explicitly address when to prefer this over general web search for DNS info.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides no guidance on when to use this tool versus alternatives like 'search' or 'scrape' for finding DNS information. No prerequisites (e.g., valid domain format) or conditions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description includes cost information ('$0.002') which is valuable behavioral context not present in the schema or annotations. However, with no annotations provided, the description fails to disclose other important behavioral traits such as whether the operation is read-only, rate limits, authentication requirements, or the format/structure of the returned results.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of a single efficient sentence where every element serves a distinct purpose: 'Search' defines the action, 'the web' identifies the resource, 'return results' describes the output, and '($0.002)' provides cost context. There is no redundant or extraneous text, and the information is front-loaded with the core action stated immediately.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complete absence of schema descriptions for both parameters and the lack of an output schema or annotations, the description is insufficiently complete. While it conveys the basic operation and cost, it fails to document critical implementation details such as parameter usage, return value structure, or error handling that an agent would need to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With zero percent schema description coverage, the description bears full responsibility for explaining parameter semantics, yet it completely omits any mention of the 'query' or 'count' parameters. There is no explanation of what constitutes a valid query string, expected format, or that the count parameter controls the number of results returned.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs a web search and returns results, specifying the exact resource ('the web') and action. However, it does not differentiate this tool from siblings like 'scrape' or 'browser_act' which also interact with web content, potentially causing confusion about when to use search versus direct content extraction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 alternative tools such as 'scrape' for URL-specific extraction or 'browser_act' for browser automation. There are no stated prerequisites, constraints, or conditions that would help an agent select this tool appropriately from the available web-interaction siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With zero annotations provided, the description must carry the full behavioral burden. It successfully discloses cost ($0.001), but omits critical details like return format (translated string vs object), error handling for unsupported languages, text length limits, or rate limiting.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely brief single sentence with no filler. While efficient in length, it lacks necessary structural elements like return value description or usage constraints that would make it appropriately informative for an agent without being verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Incomplete for a tool with no output schema and no annotations. Missing explanation of return values, supported language code standards (ISO 639-1?), maximum text length limits, and error conditions. The cost mention is the only operational detail provided.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 33% (only `target_lang` documented). The description fails to compensate by not explaining `source_lang` auto-detection behavior, `text` input constraints (max length, encoding), or semantic relationships between parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb ('Translate') and resource ('text'), and includes pricing context ($0.001). Lacks explicit differentiation from siblings like `tts` or `audio_transcribe`, though the core action is clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides no guidance on when to use this versus alternatives (e.g., `image_ocr` for text extraction followed by translation), no prerequisites mentioned, and fails to explain when to manually specify `source_lang` versus relying on the 'auto' default.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses cost ($0.002) and output format (image), but lacks critical behavioral details since annotations are absent. Missing: return format (URL, base64, file path), synchronous/asynchronous behavior, rate limits, and error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with zero waste. Front-loaded with action verb, includes parenthetical examples and pricing without verbosity. Appropriately compact.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Inadequate for the tool's complexity. With 4 parameters (including nested objects), 0% schema coverage, and no output schema, the description must explain data structure requirements and return values. Currently insufficient to guide successful data visualization implementation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fails to compensate for the undocumented parameters. Mentions chart types (hinting at 'type' enum) but provides no guidance on the complex 'datasets' array structure or 'labels' format, which are critical for correct invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clear verb ('Generate') and resource ('chart image') with specific examples (bar, line, pie). Distinguishes from sibling 'image_generate' by specifying chart types, though could explicitly clarify when to use this versus general image generation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 alternatives like 'image_generate' or 'spreadsheet_generate'. No mention of prerequisites (e.g., data formatting requirements) or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It successfully discloses pricing ($0.003), which is valuable behavioral context. However, it omits critical execution details: output format (PNG/JPG), viewport dimensions, full-page vs. viewport capture, and whether the operation is idempotent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely efficient single phrase with zero filler. The cost parenthetical adds essential information without clutter. Front-loaded with the action verb immediately.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite being a single-parameter tool, the description is incomplete. With no output schema provided, the description should specify what gets returned (image data, file path, base64 string) and basic execution constraints. The current description is insufficient for confident invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, requiring the description to compensate. While 'of a webpage' implies the 'url' parameter targets a webpage, the description fails to explicitly document the parameter, its format requirements (absolute URL, protocol requirements), or validation rules.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Take a screenshot') and target ('webpage'), distinguishing it from text-based siblings like 'scrape' or 'browser_act'. However, it lacks specificity regarding viewport scope (full page vs. visible area) or output format.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance provided on when to use this tool versus alternatives like 'scrape' (for text extraction) or 'browser_act' (for interaction). No prerequisites, error conditions, or workflow positioning is mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the cost ($0.005) but fails to disclose critical operational traits: whether sessions persist across calls, what happens if an action in the sequence fails, timeouts, or the return value format (since no output schema exists).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence where every word serves a purpose. The cost annotation at the end is concise and material. There is no redundant or filler text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex automation tool with no output schema, the description is materially incomplete. It omits what data is returned (HTML, JSON, success boolean?), whether the browser session is shared or isolated, and error handling behavior—all critical for an agent to use this tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
While the schema has 100% description coverage and defines the actions array structure, the description adds crucial semantic meaning by mapping the generic 'type' field to concrete verbs (click, fill, extract, navigate). This helps the agent understand valid action values not explicitly enumerated in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool automates browser interactions and specifically enumerates the four supported action types (click, fill, extract, navigate). This distinguishes it from sibling tools like 'scrape' (passive extraction) and 'screenshot' (capture only). However, it could further clarify whether this operates on a live DOM or headless context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 alternatives like 'scrape' or 'code_execute'. It lists capabilities but does not specify prerequisites (e.g., when navigation is required before extraction) or exclusions (e.g., when simple HTTP fetching suffices).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full disclosure burden. It successfully notes the cost and external provider (Kling AI), but omits critical operational details: output format (MP4? GIF?), resolution limits, async vs. synchronous behavior, and content policy restrictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single, dense sentence front-loaded with the action. Every element earns its place: function (generate), scope (short video), input (prompt), provider (Kling AI), and cost constraint ($0.05). No redundant or filler text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 2-parameter tool with simple types and no output schema, the description is minimally viable. The cost disclosure adds necessary context for a paid API, but the undocumented 'duration' parameter and lack of output format guidance leave gaps that should be addressed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage. The description mentions 'prompt' implicitly but does not explain what it should contain (scene description, style, motion cues?) or the expected format. It completely omits the 'duration' parameter and its units (seconds?).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clear verb ('Generate') and resource ('short video'), specifies input mechanism ('from a prompt') and provider ('Kling AI'). Distinguishes from siblings by medium (video vs. image/audio) and cost model, though lacks explicit differentiation from image_generate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Mentions cost ($0.05) which informs budget-conscious usage, but provides no explicit guidance on when to choose video over image_generate or other visual tools, and no prerequisites or constraints for the prompt content.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 provides valuable cost information ('$0.003') not found elsewhere, but fails to disclose output format, file size limits, whether the operation is read-only, or error handling behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise with zero waste. The action ('Extract text from a PDF file') is front-loaded, and the pricing parenthetical is appropriately placed as metadata without obscuring the primary purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite being a simple single-parameter tool, the lack of output schema means the description should explain what gets returned (plain text? structured JSON? confidence scores?). It also omits file size limits and OCR capabilities, leaving significant gaps for an extraction tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% ('PDF URL'), so the baseline is 3. The description does not add semantic details beyond the schema, such as supported protocols, URL accessibility requirements, or examples of valid inputs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Extract') and resource ('text from a PDF file'), clearly distinguishing it from sibling 'pdf_generate'. However, it does not clarify whether it handles scanned PDFs via OCR (relevant to sibling 'image_ocr') or only text-based PDFs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance provided on when to use this tool versus alternatives. Given siblings like 'image_ocr' (for scanned documents) and 'scrape' (for HTML content), the description should specify preferred use cases but does not.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Provides useful cost information ($0.003) not found elsewhere, but fails to disclose critical behavioral traits given zero annotations: return format (file content vs URL), file persistence, or size limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise single sentence with zero waste. However, given the tool's complexity (nested objects, file generation), it is overly terse rather than appropriately sized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Inadequate for complexity: no annotations, no output schema, low schema coverage (33%), and the description omits file handling behavior, sheets data structure requirements, and error conditions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Mentions 'Excel or CSV' which maps to the format enum, but with only 33% schema description coverage and a complex required 'sheets' parameter, the description fails to explain the expected structure ({name, headers, rows}) or filename conventions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Generate') and clear resource ('Excel or CSV spreadsheet'), explicitly distinguishing it from siblings like chart_generate (visualizations) and pdf_generate (documents).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance provided on when to choose this over chart_generate for tabular data, pdf_generate for reports, or whether to use csv vs xlsx formats for specific use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It adds critical cost information ($0.005) and model context, but fails to disclose return format (URL vs base64), latency expectations, or content policy restrictions typical for image generation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with zero waste. Front-loaded with essential differentiators (model name, cost). Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For an image generation tool with no output schema, description inadequately explains what gets returned (image URL? base64? file path?). Also omits expected resolution defaults and behavioral constraints despite having complex siblings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is only 33% (only 'prompt' described). Description fails to compensate for undocumented width/height parameters—no mention of aspect ratio implications, valid ranges, or defaults despite these being critical for image generation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Excellent specificity: states exact verb (Generate), resource (image), model (Flux 1.1 Pro), and cost ($0.005). The model name distinguishes it from sibling 'image_fast' and other generation tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 siblings like 'image_fast' (likely a cheaper/faster alternative) or 'video_generate'. Missing selection criteria for choosing Flux 1.1 Pro over other models.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Includes pricing transparency ($0.001) but omits critical behavioral details: output format (plain text, markdown, JSON?), JavaScript rendering support, error handling for 404s/redirects, and whether the operation is idempotent/read-only.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with specific verbs, zero redundancy. The cost parenthetical is appropriately placed and succinct.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter tool, it covers the core operation and cost, but is incomplete due to missing output format specification (critical since no output schema exists) and absence of error behavior documentation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description partially compensates by referencing 'a URL' which maps to the `url` parameter. However, it lacks specifics on URL format requirements (absolute vs. relative, protocol restrictions, allowed domains) or examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the action (scrape/extract) and target (text content from URL), including cost. However, it does not explicitly differentiate from sibling `browser_act` which may also retrieve web content, or clarify if this handles non-HTML content differently than `pdf_extract`.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides no guidance on when to use this tool versus alternatives like `browser_act`, `screenshot`, or `search`. Does not mention prerequisites, supported content types (HTML vs. PDF), or limitations like paywall handling.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description discloses key behavioral traits: output format (MP3) and cost per use ($0.002). However, it fails to document available voice options (only 'alloy' is shown as default in schema), rate limits, or whether the operation is idempotent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, information-dense sentence with zero wasted words. It front-loads the action ('Convert'), specifies the format ('MP3'), and appends cost—every element earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a two-parameter generative tool without output schema, the description covers the essential purpose and cost but leaves significant gaps: valid voice options are unexplained, and handling of the MP3 output (returned as bytes, URL, or file ID) is not described.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, requiring the description to compensate. While 'Convert text' implicitly clarifies the 'text' parameter, the description completely omits the 'voice' parameter and its valid values (e.g., 'alloy', other options), leaving critical parameter semantics undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the core function with specific verb ('Convert'), resource ('text to speech'), and output format ('MP3'), plus cost information. However, it does not explicitly distinguish from sibling tool 'audio_transcribe' (speech-to-text), which would be necessary for a top score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes cost information ('$0.002') which guides usage economics, but lacks explicit guidance on when to use this tool versus alternatives like 'audio_transcribe', and omits prerequisites such as text length limits or voice availability.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Adds valuable cost information ($0.005) and the template requirement constraint. However, missing disclosure on return values, error handling (e.g., invalid template names), rate limits, or whether the operation is idempotent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single dense sentence with zero waste. Front-loaded with action verb. Cost information parenthetically included without clutter. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for basic invocation given the tool's moderate complexity, covering the essential constraint (templates) and cost. However, incomplete regarding parameter semantics (especially 'params' array purpose) and lacks description of return values or success/failure indicators, which is notable given no output schema exists.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is only 25% (only 'to' parameter described). Description mentions 'template' but fails to explain the critical 'params' array (likely for template variable substitution), the expected format for 'language' (default en_US suggests locale codes), or provide examples. Insufficient compensation for poor schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the action (Send), resource (WhatsApp message), and critical constraint (pre-approved template). Includes cost transparency ($0.005). Lacks explicit differentiation from sibling communication tools (e.g., how it differs from email or SMS capabilities), though the WhatsApp specificity helps.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies a usage constraint through 'pre-approved template,' hinting that free-form messaging isn't supported. However, lacks explicit guidance on when to use this versus alternatives, prerequisites for template approval, or what happens if templates aren't pre-approved.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It successfully reveals pricing information ($0.001) which is valuable context, but fails to mention mutation characteristics, idempotency, rate limits, or what the tool returns (the shortened URL string).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise at five words. Every element earns its place: the action ('Shorten'), the resource ('a URL'), and critical cost context ('$0.001'). No filler or redundant text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a low-complexity single-parameter tool, the description covers the core operation and cost, but leaves gaps given the lack of output schema. It omits what the tool returns (the short URL), error scenarios (invalid URLs), and whether shortened URLs expire.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, requiring the description to compensate. While the single parameter 'url' is self-evident from the tool name and description context, the text does not explicitly document the parameter's purpose, expected format (absolute vs relative), or validation constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Shorten') with a clear resource ('URL'), making the tool's function immediately obvious. Among the diverse sibling tools (audio_transcribe, image_generate, etc.), this distinctly identifies the URL shortening capability.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, nor does it mention prerequisites (e.g., URL format requirements) or when not to use it. The cost hint ($0.001) implies it's a paid operation but doesn't explain cost implications.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It successfully discloses cost ('$0.001') and validation methodology (MX check), but fails to describe return values, error handling, rate limits, or safety characteristics (e.g., read-only nature).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely efficient: every token earns its place. Front-loaded with the action ('Validate'), followed by scope, technical method in parentheses, and cost. Zero waste despite high information density.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter tool without output schema, the description adequately explains the operation and cost, but should mention the return format (boolean? object?) and potential error states to be fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% for the single 'email' parameter. The description implies the parameter is the target email address ('Validate an email address'), providing baseline semantic context, but does not explicitly document the parameter's purpose, format requirements, or constraints beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Validate') with clear resource ('email address') and methodology ('format + MX check'). No sibling tools handle email validation, so no explicit differentiation is needed; the scope is immediately obvious.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no explicit guidance on when to use this tool versus alternatives, or prerequisites for use. The cost indicator ('$0.001') provides implicit usage context (paid operation), but lacks explicit when/when-not recommendations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description carries full burden. Mentions 'sandbox' (isolation) and cost, but omits critical execution details: timeout limits, available libraries/packages, output format (stdout vs return value), and file system persistence.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with action verb, zero redundancy. Every element (action, languages, environment, cost) conveys essential information efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a high-complexity operation (arbitrary code execution) with no annotations, no output schema, and minimal schema coverage, the description is insufficient. Missing: security boundaries, resource limits, package availability, and execution lifecycle details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage. Description compensates partially by specifying the two supported languages (aligning with the enum), implying 'code' parameter content, but does not explicitly document parameter semantics or required syntax.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clear specific verb ('Execute') and resource ('Python or JavaScript code'). Explicitly distinguishes from all siblings (image processing, PDF, search, etc.) by specifying code execution capability.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides implicit usage context (run code) and cost constraint ($0.01), but lacks explicit guidance on when to choose Python vs JavaScript, timeout limits, or alternatives to using this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, description carries full burden. It successfully discloses cost ('$0.001') and dual output type (current + forecast), but omits safety profile (read-only status), error handling, rate limits, and forecast timeframe.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with action verb, zero redundancy. The cost parenthetical is dense and valuable. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for a single-parameter tool with complete schema coverage. Includes pricing transparency. Minor gap: lacks output description (forecast range, units) though no output schema exists to compensate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (location parameter fully documented as 'City name or coordinates'), establishing baseline 3. Description adds minimal parameter context beyond schema, merely referencing 'a location' without additional format examples or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Specific verb 'Get' with clear resources ('current weather and forecast') and scope ('for a location'). Unambiguously distinguishes from all siblings (e.g., crypto_price, dns_lookup, search) by specifying weather data retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides no guidance on when to use versus alternatives (e.g., when to use this vs. general 'search'), no prerequisites (e.g., location format requirements), and no exclusions (e.g., not for historical weather data).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It successfully discloses cost ('$0.003/min') and technology ('Whisper AI'), but omits critical behavioral details: output format (plain text vs. JSON with timestamps), maximum file duration, supported file size limits, or error handling for invalid URLs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence of 10 words. Every element earns its place: action (Transcribe), resource (audio), constraint (from a URL), implementation (Whisper AI), and cost ($0.003/min). No redundant or filler text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 2-parameter tool with 100% schema coverage and no nested objects, the description is minimally adequate. However, the absence of an output schema creates a gap—the description should ideally specify what the tool returns (e.g., transcribed text string, confidence scores) but does not.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with 'url' and 'language' fully documented in the schema. The description reinforces the URL requirement but does not add syntax details, format constraints, or usage guidance for the parameters beyond what the schema already provides, warranting the baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description provides specific verb (Transcribe), resource (audio), source constraint (from a URL), and distinguishes from siblings (e.g., image_ocr, tts) by specifying audio input. The addition of 'Whisper AI' and pricing '$0.003/min' further clarifies scope and mechanism.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'from a URL' implies the tool requires a hosted audio file, not local/uploaded files, providing implicit usage context. However, there are no explicit when-to-use guidelines, exclusions, or comparisons to alternatives like image_ocr for visual text extraction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It successfully discloses cost ($0.002) and speed characteristics ('quickly', 'faster'), but omits return format (URL vs base64), rate limits, dimension constraints, or idempotency behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with zero waste. Front-loads the action ('Generate'), specifies the model, and packs two key differentiators (speed, cost) into a compact form. Every clause earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for basic tool selection but incomplete for invocation. Missing output schema coverage is expected, but the lack of parameter constraints (min/max dimensions, valid aspect ratios) for the dimension parameters leaves critical gaps given the 0% schema coverage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage (no descriptions for prompt, width, height). Description fails to compensate—it doesn't mention parameters at all, leaving width/height constraints (valid ranges, step values) completely undocumented despite their defaults.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description states specific verb ('Generate') + resource ('image') + model ('Flux Schnell') and distinguishes from sibling 'image_generate' via explicit speed/cost positioning ('faster, cheaper'). The cost annotation ($0.002) further clarifies economic differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage context through 'faster, cheaper' positioning, suggesting use when speed/cost matters over quality. However, it doesn't explicitly name 'image_generate' as the alternative for higher quality, requiring the agent to infer from the 'fast' suffix.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses cost ($0.002) which is valuable behavioral context absent from annotations. However, lacking annotations, the description fails to clarify safety profile (read-only vs destructive), supported image formats, language limitations, or output structure (plain text vs JSON with coordinates).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single efficient sentence fragment with zero waste. Cost information is contextually valuable and earns its place. Immediate front-loading of action ('Extract text') followed by method and cost.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for a single-parameter tool with high schema coverage. Core operation is clear, though output format specifics would strengthen completeness given the absence of an output schema (implied to return text but format unspecified).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema description coverage ('Image URL'), the baseline is 3. The description implies the URL should point to an image via 'Extract text from an image' but adds no specific syntax guidance, format constraints, or examples beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Specific verb 'Extract' + resource 'text from an image' + method 'using OCR' provides exact operational scope. Clearly distinguishes from siblings like image_generate, image_resize, and image_rembg by specifying text extraction rather than image manipulation or generation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied by the OCR designation (use when needing text from image files), but lacks explicit when-to-use guidance versus alternatives like pdf_extract for documents or scrape for web text, and omits prerequisites like URL accessibility requirements.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Includes valuable cost transparency ($0.003) not found elsewhere. However, lacks disclosure about output format (PNG with alpha channel?), mutation characteristics (source preservation), rate limits, or error conditions (e.g., failure on complex backgrounds).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with zero waste. Front-loaded with the core action, followed by essential cost information in parentheses. Every word earns its place; no redundant or filler content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for a single-parameter utility with full schema coverage. Missing only what the return value contains (image data vs URL) since no output schema exists, but the simplicity of the tool makes the purpose sufficiently clear for agent invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with 'Image URL' clearly describing the url parameter. Description reinforces that the input should be an image ('from an image'), meeting baseline expectations when schema documentation is complete. No additional parameter guidance (supported formats, size limits) provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description provides specific verb ('Remove'), clear resource ('background from an image'), and distinguishes effectively from siblings like image_generate, image_ocr, and image_resize which perform entirely different operations. The pricing annotation further clarifies this is a specific paid processing service.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage context (when background removal is needed) but lacks explicit when-to-use guidance, prerequisites (e.g., publicly accessible URLs), or format limitations. No comparison to alternative approaches or sibling tools that might overlap in functionality.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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