Lead Intelligence

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

With no annotations, the description carries the burden. It discloses a key behavioral trait: exact crawling of submitted URLs without discovery, and mentions cost. However, it omits other behavioral aspects like caching, side effects, or output handling, which leaves some transparency 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 a single, front-loaded sentence stating the purpose, followed by cost. Every word earns its place, and it is concise without unnecessary 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?

Given no output schema and no annotations, the description should provide more context about what results look like, what 'reception-channel gaps' entails, and how the cost scales. The brevity leaves too many important details unaddressed for a tool with 7 parameters and no output schema.

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

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

Schema coverage is 100%, so all seven parameters are documented in the schema. The description adds no parameter-specific meaning, but the baseline of 3 applies because the schema fully explains each 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 a specific action ('Analyze submitted clinic websites') and a specific resource ('clinic websites for reception-channel gaps'), distinguishing it from the sibling tool for restaurants. The addition of 'exact BYOD crawling and no discovery' further clarifies the scope.

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

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

Usage is implied through the name and description (use for clinic websites), but there are no explicit when-to-use or when-not-to-use instructions, nor is a specific alternative tool mentioned. This is adequate but lacks exclusionary guidance.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds useful context: the datasets are fixed, signals are evidence-backed, and the cost is $0.03/call via x402. Nevertheless, it doesn't mention return format, pagination, rate limits, or whether the operation is read-only, leaving notable gaps in transparency.

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

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

The description is two concise sentences, front-loaded with the core purpose and followed by pricing. Every word earns its place 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?

With no output schema, the description fails to explain the structure of 'evidence-backed signals' or list the specific five Socrata datasets. The parameter schema is thorough, but the overall description leaves questions about return values and dataset details, though it is adequate for an initial understanding.

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

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

Schema description coverage is 100%, so the baseline is 3. The description adds no parameter-specific details beyond what the schema already provides; it doesn't elaborate on maxResults, detailLevel, lookbackDays, or freshnessMinutes.

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 'Detect' and identifies the resource: 'commercial permit and license openings from five fixed Socrata datasets,' and states it returns 'evidence-backed signals.' This clearly differentiates it from sibling tools like clinic-reception-gap-lead-finder or restaurant-booking-gap-lead-finder, which target other verticals.

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 clearly indicates this tool is for detecting commercial permits/licenses, which distinguishes it from the unrelated sibling tools. However, it does not explicitly state when not to use it or name alternatives, making it slightly short of a 5.

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

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

With no annotations, the description carries the burden. It discloses the free nature, the read-only 'list' behavior, and the type of data returned (price, payTo address, network). No side effects or prerequisites are hidden, and the 'free' claim is a meaningful behavioral trait.

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 tight sentences: first states the action and output fields, second gives the usage hint. Front-loaded with 'Free' and immediately informative, with no wasted words.

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

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

For a simple, zero-parameter tool with no output schema, the description fully covers what the tool does (list pricing info) and when to use it. It names the output fields and the free nature, making it self-contained.

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 is empty with 100% coverage. Per the rubric, a 0-parameter tool receives a baseline of 4. The description adds no parameter-specific info because none are needed.

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 lists every paid tool in the 'lead-intelligence' bundle with specific fields (price, payTo address, network). It uses a specific verb ('list') and clearly distinguishes itself from sibling lead-finder tools.

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

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

Provides clear context for when to call ('Call this first if you don't have a wallet ready yet'), implying this is an informational first step. However, it does not mention when not to use it or explicitly name alternatives, so it misses full exclusion/alternative guidance.

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

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

With no annotations provided, the description carries the full burden for behavioral disclosure. It does add useful context: 'exact BYOD crawling' indicates precise crawling of provided URLs, 'no discovery' clarifies it won't find new websites, and the '$0.05/call, x402 (USDC on base)' discloses pricing. Yet it lacks details on output format, rate limits, or side effects, leaving significant 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 concise, front-loading the main verb and resource in a single sentence. However, it uses jargon ('BYOD', 'x402') that may not be universally clear, and the dash-separated pricing clause adds necessary but slightly scattered 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?

The tool is moderately complex with seven parameters and no output schema, but the description does not explain what the output looks like, what 'booking-channel gaps' means in practical terms, or how results are structured. It omits return value details, which are essential for agent use without an output schema.

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

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

The input schema has 100% description coverage for all seven parameters, so the baseline is 3. The description does not add any parameter-specific semantics beyond what the schema already provides, such as clarifying the meaning of 'minGapScore' or 'freshnessMinutes'.

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

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

The description clearly states the tool's function: 'Analyze submitted restaurant websites for booking-channel gaps.' The verb 'Analyze' plus the specific resource (restaurant websites) and outcome (booking-channel gaps) makes the purpose explicit. It also distinguishes itself from siblings by focusing on restaurants and submitted URLs, with 'no discovery' setting it apart from discovery-oriented tools.

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

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

The description provides clear context: use this tool when you have 'submitted restaurant websites' to analyze, and explicitly excludes discovery use cases ('no discovery'). However, it does not name alternative tools or provide explicit 'use this instead of' guidance, so it falls short of a 5.

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