Licence audit, page read and endpoint check (AI-operated)

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

States it's free and AI-operated, implying no human involvement and no cost. Does not explicitly mention read-only nature, side effects, or rate limits, though 'checks' suggests a safe operation.

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

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

Very concise, two sentences. No unnecessary words, clearly structured with free vs paid distinction.

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?

Provides sufficient context for expected output (status code, latency, and paid extras). Lacks mention of error handling or non-responsive endpoints, but overall gives a clear functional picture.

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

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

Schema descriptions for 'url' and 'method' are identical to text; no additional meaning provided. Since schema coverage is 100%, the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states the tool's function: checking an HTTPS endpoint and returning status code and latency. Also clarifies free vs paid capabilities.

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?

Mentions free vs paid tiers but does not explicitly differentiate from sibling tools or provide when-to-use guidance. Lacks clear conditions for choosing this over alternatives.

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

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

No annotations are provided, so the description is the only source of behavioral transparency. It discloses multiple payment methods (x402, manual transaction, Stripe), the cost (5.00 USD), and that no gas is needed for the buyer. However, it doesn't mention side effects like returning a transaction hash or that it settles through a facilitator, which is a notable behavior. It doesn't disclose potential rate limits or external dependencies beyond the facilitator. Overall, it adds substantial context but misses some behavioral details.

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

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

The description is a single long paragraph that packs a lot of information. It's front-loaded with the core purpose (returns what paid operations cost and how to pay) and then elaborates on methods. While it's comprehensive, the length is borderline; it could be broken into clearer sentences or bullet points for readability, but it's not overly verbose.

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 no parameters, no output schema, and no annotations, the description covers the essential aspects: costs, chains, payment methods, and additional returns (free examples). It doesn't specify the format of the returned data (e.g., if it's a JSON object with fields), but the description is sufficient for an agent to understand what the tool does and likely interpret the response. Sibling context suggests this is a read-only operation, but no exclusions are stated.

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

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

The tool has no parameters, so the schema is trivial (100% coverage). The description provides all necessary context about what the tool returns without needing to describe parameters. Since there are no parameters, the baseline for parameter semantics is high, and the description fully compensates by explaining the return content.

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 returns payment information for paid operations, including costs, chains, and payment methods. It distinguishes itself from siblings by focusing on payment terms rather than previews or checks. However, it could be more precise about the verb (e.g., 'get' vs 'retrieve') but overall it's specific enough.

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 when to use this tool (when needing payment details for paid operations) but does not explicitly mention alternatives or when not to use it. Siblings like 'licence_audit_preview' might be used for previewing the audit, but no direct comparison is made. The guidance is inferred from the content rather than stated.

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

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

No annotations are provided, so the description carries the full burden. It discloses key behaviors: operates on public manifests only, never clones/builds/executes, and caps at 8 packages. This is thorough behavioral disclosure for a free preview tool.

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

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

The description is dense but efficient, front-loading the key purpose and limitations in the first sentence. Every sentence adds value: cost, scope, and safety constraints are covered without fluff. Well-structured for quick scanning.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (2 params, no output schema), the description fully covers what an agent needs to call it correctly: the input manifest format, the distribution param's role, the 8-package cap, and the safety profile. Nothing critical is missing.

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

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

The schema already fully describes both parameters with 100% coverage, including the enum for distribution and the format for manifest_url. The description adds no new meaning beyond the schema; it only implies that manifest_url is the input for the audit, which is already clear. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool audits the first packages of a public dependency manifest and returns licenses with source documents. It specifies what it does not do (no cloning, building, executing, vulnerability scanning), which uniquely distinguishes it from siblings like endpoint_check_preview and page_read_preview.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says when to use the free preview (for a limited 8-package audit) and when to use the paid full audit via get_payment_terms. It also clarifies limitations (caps at 8 packages, no vulnerability scanning), guiding the agent to the right tool for full audits.

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 key behaviors: it avoids executing JavaScript, returns cleaned text, and includes specific elements (title, headings, first 800 characters). It also notes that each call is limited to public pages. However, it does not mention potential side effects, error conditions, or rate limits, though it covers the primary behavior well.

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, using two sentences to convey the core functionality and the free/paid distinction. It is well-structured, front-loading the primary action and output, and avoids unnecessary detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the absence of an output schema, the description adequately specifies what the tool returns (title, headings, first 800 characters) and the parameter constraints. It could be more complete by mentioning error handling or edge cases, but for the tool's simple purpose, it is sufficiently informative.

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 single parameter 'url' is fully described with constraints: it must be an absolute https URL of a public page. This provides clear semantic guidance for the parameter, leaving no ambiguity about its format or requirements.

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 action (reads one public web page), its scope (no JavaScript execution), and the specific output (title, headings, first 800 characters of cleaned text). It also distinguishes the free version from the paid call, 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 does not explicitly state when to use this tool over alternatives. It mentions the paid call returns more data, but this is not a directive for choosing between tools. It lacks guidance on scenarios where this tool is preferred, such as quick previews or limited content needs.

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