AIWebSignals

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

With no annotations, the description carries the burden and it does meaningful work: it discloses that the data is public, current, and served from a specific endpoint, and it names the included sections. The word 'Return' implies a read-only operation, though it does not explicitly address side effects, rate limits, or failure behavior.

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

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

A single front-loaded sentence that names the action, resource, endpoint, and contents without wasted words. Every phrase adds information.

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

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

For a zero-parameter, no-output-schema read tool, the description is nearly complete: endpoint, scope, and content categories are all present. It does not specify the exact response format or error cases, but the low complexity makes those omissions minor.

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?

There are zero parameters, so parameter documentation is not needed; the schema already covers everything (100% coverage). The description adds no parameter semantics, but none are required.

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

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

The description uses a specific verb ('Return') and identifies a precise resource: the public capability contract served at /api/capabilities. It also enumerates the main content areas (active protocol, evidence, security boundaries), which clearly separates it from pricing and readiness-scan siblings.

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

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

Usage is implied: call this when you need the current public capability contract. The description does not explicitly state when not to use it or compare it to get_machine_pricing or scan_ai_web_readiness, but the endpoint and content scope make the intended context reasonably clear.

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

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

With no annotations, the description carries the full behavioral burden. It discloses that the response mirrors the public endpoint and explicitly excludes provider configuration identifiers and payment credentials, which is valuable context about what the tool will and will not return.

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, front-loaded sentence followed by a precise exclusion note. Every word earns its place; there is no redundant phrasing or unnecessary detail.

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

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

For a zero-parameter, public-catalog lookup, the description covers the purpose and the key exclusion. It does not spell out output format or authentication, but the simplicity of the tool and the 'public' qualifier make those omissions acceptable.

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

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

The tool has zero parameters, and the schema confirms this with an empty object. The description adds no parameter-specific detail, but none is needed; the baseline for a zero-parameter tool is appropriately high.

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

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

The description uses a specific verb ('Return') plus a clear resource ('public plan catalog') and even ties it to an endpoint. It is distinct from the sibling tools, which target capabilities and AI web readiness, so an agent can immediately tell this is the pricing tool.

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 that this tool is for retrieving public pricing data but does not explicitly state when to use it over the siblings. There is no direct mention of alternatives or exclusions, though the tool name and endpoint reference make the intent reasonably clear.

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

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

With no annotations provided, the description carries the full behavioral disclosure burden. It clearly states the target website is not modified (non-destructive) and that AIWebSignals may persist its normalized observation in scan history, which is an important side-effect disclosure. It does not mention authentication or rate limits, but the key safety and persistence traits are covered.

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 zero filler. The first sentence front-loads the action and target; the second covers constraints and side effects. Every clause earns its place and nothing repeats the schema.

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 one-parameter tool with no output schema, the description should explain what the call returns. It explains what the scanner does and its side effects, but never states the form of the readiness result (score, report, boolean, etc.), leaving an agent to infer the output. This is a real gap, but otherwise the low-complexity tool is well covered, so a 3 is appropriate.

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

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

Schema description coverage is 100% for the single 'domain' parameter, so the baseline is 3. The description adds the explicit 'Private/local network targets are rejected' constraint, but this essentially restates the schema's 'Public hostname or HTTP(S) URL' wording in negative form. It does not add new parameter-level semantics beyond what the schema already conveys.

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

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

The description uses a specific verb ('Run'), names the exact tool ('AIWebSignals' existing bounded public readiness scanner'), and states the target ('public hostname or HTTP(S) URL'). It explicitly contrasts with rejected private/local targets, making the tool's scope unmistakable. Sibling tools about machine capabilities/pricing are unrelated, so there is no confusion with them.

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

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

The description gives clear use context: scanning a public hostname or URL, with an explicit 'when-not' condition ('Private/local network targets are rejected'). It does not discuss alternatives, but the sibling tools are on entirely different subjects (machine capabilities and pricing), so no alternative is needed. This is clear context with one concrete exclusion, not full alternative routing.

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