agents

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

With no annotations, the description must disclose behavioral traits. It mentions the output (score, competitors, GEO fix-list) and the payment requirement, but does not describe idempotency, side effects, rate limits, or authentication needs. The payment flow is 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 concise: two sentences, first stating purpose and output, second stating cost. No unnecessary words, front-loaded with key 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?

Given no annotations, no output schema, and 3 undocumented parameters, the description is insufficient. It does not explain how to interpret the score, what 'GEO fix-list' means, or how payment works. The tool's complexity requires 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 3 parameters (url, brand, category) with 0% schema description coverage. The description only explains the 'brand' parameter (the brand to check). It does not clarify the purpose of 'url' or 'category', leaving agents guessing.

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: checking AI answer engines for brand recommendations, outputting a 0-100 score, competitors, and GEO fix-list. It distinguishes itself from sibling tools like extract_web_data or read_web_page by focusing on AI visibility scores.

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 minimal usage guidance: it mentions the tool is paid ($4 USDC via x402) but does not explain when to use this tool over alternatives, what prerequisites exist, 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.

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

The description discloses the cost and payment method (x402), but since no annotations are present, it fails to mention other behavioral traits such as idempotency, rate limits, or authentication requirements. The statement 'exact structured JSON you ask for' hints at flexibility but lacks specifics.

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 with two sentences, front-loading the purpose and then adding cost. It wastes no words, though it could be better structured to separate purpose from cost.

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 lack of annotations, output schema, and low parameter coverage, the description is incomplete. It explains the core function and cost but omits parameter details, error handling, and usage context despite having only 2 parameters.

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?

With 0% schema description coverage, the description does not individually clarify the 'url' and 'instruction' parameters. Only implied meaning from context ('public URL' and 'exact structured JSON you ask for') is given, leaving format and valid values unspecified.

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 'Scrape' and the resource 'public URL', specifying the output as 'exact structured JSON' for data like prices, contacts, etc. It distinguishes from sibling 'read_web_page' which likely provides raw page content.

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 mentions a payment requirement ($0.05 USDC) but does not explicitly state when to use this tool over siblings like 'read_web_page' for simpler reading tasks. No when-not 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 provided, the description carries full burden for behavioral disclosure. It does not mention read-only nature, absence of side effects, data freshness, or error conditions. For a simple list operation, minimal transparency is provided.

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?

A single sentence of 14 words, front-loaded with the action and resource. Every word is informative with 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?

For a zero-parameter tool lacking an output schema, the description covers the essential purpose and output content (what agents do, prices, endpoints). It could mention that no arguments are required, but the empty schema already implies that. Slightly incomplete regarding return format.

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?

No parameters exist, and schema coverage is vacuous (100% covered). Baseline for high schema coverage is 3. The description adds no parameter-level insight since there are none, so it meets the minimum viable level.

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 'list', the specific resource 'Vevang's live autonomous AI agents', and the content 'what they do, prices, and endpoints'. It distinguishes itself from sibling tools like extract_web_data or make_marketing_video by focusing on a unique agent listing.

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 alternatives. It lacks context about prerequisites, expected scenarios, or explicit when-not-to-use conditions. Sibling tools suggest different capabilities but no direct comparison.

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 fully disclose behavioral traits. It mentions the paid nature ($12 USDC) and that the video is produced from a prompt, but fails to explain how other parameters (url, brand, aspect) affect output, whether the action is destructive, or what the return value is. This leaves significant behavioral 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?

The description is extremely concise, providing the core purpose and payment detail in two sentences. No unnecessary words or repetition. It is front-loaded with the primary action and efficiently communicates the key 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?

Given the tool has 4 parameters, no output schema, and no annotations, the description is insufficiently complete. It omits how to use the optional parameters, the expected output format (e.g., video URL or file), and any rate limits or authentication needs. A paid tool requires fuller context for safe invocation.

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 has 0% description coverage for parameters, and the description adds little beyond naming 'prompt' as the input. The meanings of 'url', 'brand', and 'aspect' are not clarified, nor are any constraints or defaults explained. The description does not compensate for the missing schema documentation.

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 produces a finished, on-brand short marketing video from a single prompt. It includes the verb 'produce' and the resource 'short marketing video', and notes the payment requirement. This is distinct from sibling tools which focus on data extraction or visibility checks, making the purpose 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 usage for generating a marketing video from a prompt, and the payment detail signals a cost. While it does not explicitly state when not to use or provide alternatives, the sibling tools are unrelated, so the context is clear. More guidance on prerequisites or limitations would improve the score.

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?

Without annotations, the description must convey behavioral traits. It discloses the non-destructive nature (read-only public URLs), output format (markdown), and cost ($0.01 USDC via x402). However, it does not mention error handling, rate limits, or URL format requirements, which are minor 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?

The description is two sentences with no fluff. The main action is front-loaded, and the payment info is appended separately. 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 tool with one parameter and no output schema, the description covers the core functionality, output format, and cost. It does not differentiate from the sibling 'extract_web_data', but overall it is sufficient for an agent to use correctly.

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

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 0% description coverage, so the description must compensate. It explains that the 'url' parameter is the public page to read, but adds no constraints (e.g., protocol, length). This is adequate but minimal for a single parameter.

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 reads a public URL and converts it to clean markdown, specifying the output includes main content, title, and links. This distinguishes it from sibling tools like 'extract_web_data' which likely performs structured extraction.

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 usage for reading any public URL but does not explicitly state when to use this tool versus alternatives like 'extract_web_data'. It lacks exclusion criteria or conditions.

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?

The description discloses the cost ($1 USDC via x402) but lacks details on verification process, success/failure outcomes, authentication requirements, or rate limits. Given no annotations, this is somewhat informative but insufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no extraneous words. Every part adds value: purpose, action, and cost.

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?

No output schema, no annotations, and sparse parameter details. The description omits what the tool returns, how verification is performed, and what constitutes failure. Not sufficiently complete for a tool involving payment.

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?

With 0% schema description coverage, the description adds context that 'deliverable' is the item to verify and 'spec' is the criteria, but does not explain format, defaults, or how spec is used. Partially compensates but not fully.

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 verifies a deliverable from another agent, checking it's real and meets specifications, before payment. It distinguishes from sibling tools that handle data extraction, web reading, video making, and agent listing.

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 usage before paying for a deliverable, but does not explicitly state when to use versus alternatives, nor does it provide exclusions or prerequisites.

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