Local business intel for AI agents: audits, lead scoring, tech stack, prospecting.
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Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Average 3/5 across 8 of 8 tools scored. Lowest: 2.3/5.
Each tool has a clearly distinct purpose: audit vs bulk audit, finding leads with specific conditions, searching, getting details, tech stack, and lead scoring. No overlap that would cause confusion.
All tool names follow a consistent verb_noun snake_case pattern (e.g., audit_website, find_no_booking, get_business_details). Verbs are descriptive and nouns clearly indicate the target.
With 8 tools, the set is well-scoped for a business intelligence server. It covers core operations without being bloated or insufficient.
The tools cover lead discovery, auditing, and scoring comprehensively. Minor gaps: no detailed audit breakdown beyond score, no export or note-saving functionality, but these are not core to the stated purpose.
audit_websiteBInspectScore a website 0-100 across SSL, mobile-readiness, speed, contact, booking.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes |
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must communicate behavioral traits. It indicates the tool performs scoring (likely a read operation) but does not mention whether it modifies anything, requires authentication, has rate limits, or handles invalid URLs. The lack of detail leaves uncertainty for an AI agent.
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, short sentence that front-loads the main action ('Score a website'). It is concise with no wasted words. However, it could be slightly more structured by separating purpose from output dimensions.
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 simple with one parameter and likely a clear output schema (not shown). The description covers the core purpose and dimensions but omits context like prerequisites (e.g., website must be accessible), expected input format, or interpretation of scores. Given low complexity, it is minimally complete but could benefit from a bit 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 schema has only one parameter (url) with 0% description coverage. The tool description does not explain the URL format, constraints, or what constitutes a valid input. It only mentions the scoring dimensions, which relate to the output, not the parameter. The description adds minimal value beyond the schema for the 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 scores a website 0-100 across specific dimensions (SSL, mobile-readiness, speed, contact, booking). It uses a specific verb 'score' and resource 'website', and the list of dimensions distinguishes it from sibling tools like 'find_no_booking' or 'bulk_audit'.
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 explicit guidance is given on when to use this tool versus its siblings (e.g., bulk_audit for multiple sites, find_no_booking for a specific issue). The description implies it's for a single website audit but does not state this explicitly or provide exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
bulk_auditAInspectAudit up to 20 URLs concurrently. Results sorted worst-first (best leads first).
| Name | Required | Description | Default |
|---|---|---|---|
| urls | Yes |
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses concurrency and sorting, but no annotations are provided. The description does not cover safety (idempotency), auth requirements, or potential side effects. Output schema exists but is not detailed here.
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, every word contributes value, front-loaded with key info. No redundant or vague phrasing.
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 and 0% schema coverage, the description is too sparse. It omits error behavior, pagination, and the meaning of 'worst-first' in the context of lead scoring. Output schema existence reduces burden but still incomplete.
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 only parameter 'urls' has no schema description (0% coverage) and the tool description does not explain URL format, validation, or constraints beyond the 20-count limit. This leaves the agent guessing about input 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?
Clearly states the tool audits up to 20 URLs concurrently, with a specific sort order. The verb 'audit' and resource 'URLs' are explicit, and the bulk nature distinguishes it from siblings like audit_website.
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?
Implies use for multiple URLs, but does not explicitly exclude single URL scenarios or name alternatives. The context is clear but lacks direct when-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
find_no_bookingCInspectBusinesses with a website but no online booking system. Big opportunity for SaaS pitches.
| Name | Required | Description | Default |
|---|---|---|---|
| city | Yes | ||
| limit | No | ||
| niche | Yes | ||
| state | No |
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description lacks behavioral details such as safety, authentication, or output structure. It only states the high-level result.
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 very short (one sentence) but includes unnecessary sales language ('Big opportunity'). It could be more structured.
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?
Despite having an output schema, the description does not mention return values or usage hints for the 4 parameters. Incomplete for a tool with no schema coverage.
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 0%, and the description does not explain any parameters (e.g., niche, city). The agent has no guidance on input semantics.
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: find businesses with a website but no online booking system. It distinguishes from siblings like 'find_no_website' by focusing on the booking system gap.
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 use for SaaS pitches but does not explicitly state when to use or avoid this tool, nor does it compare to siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
find_no_websiteBInspectFind businesses in a niche with NO website at all — hottest cold-outreach leads.
| Name | Required | Description | Default |
|---|---|---|---|
| city | Yes | ||
| limit | No | ||
| niche | Yes | ||
| state | No |
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It does not disclose any behavioral traits such as rate limits, authentication requirements, or what happens with empty results. The phrase 'hottest cold-outreach leads' adds value but insufficiently covers behavioral aspects.
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 concise sentence that front-loads the key function. It is efficient but lacks structural elements like bullet points or sections. It earns its place without waste.
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 (2 required), no schema descriptions, and no annotations, the description is moderately complete. It states the core purpose but omits details about output format or limits, despite an output schema existing. Adequate but not thorough.
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 0%, yet the description does not elaborate on any parameters. While parameter names like 'niche' and 'city' are somewhat self-explanatory, no additional meaning or format guidance is given, leaving the agent to rely solely on the schema.
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 finds businesses in a niche with no website, which is distinct from siblings like 'find_no_booking' and 'audit_website'. The verb 'find' and resource 'businesses without website' are specific, and the value proposition for cold outreach is highlighted.
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 use for cold-outreach leads without websites but provides no explicit guidance on when to use vs. alternatives like 'search_businesses' or 'audit_website'. The context is clear but lacks exclusions or comparative advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_business_detailsCInspectResolve a single business to phone, address, website, hours, rating.
| Name | Required | Description | Default |
|---|---|---|---|
| city | Yes | ||
| business_name | Yes |
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It only lists output fields but does not mention whether the operation is read-only, authentication needs, error behavior (e.g., what if business not found), or rate limits. Minimal transparency beyond the basic resolution action.
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 sentence of 10 words, which is very concise. The structure is simple and front-loaded with the key action. However, it omits important details, so conciseness comes at the cost of completeness, preventing a higher score.
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 low complexity (2 params) and presence of an output schema, the description could be minimal but still complete. However, it lacks usage guidelines, parameter semantics, and behavioral transparency, making it incomplete for an AI to use correctly. The agent would need to guess about error handling and exact input needs.
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 0%, meaning no parameter descriptions exist in the schema. The description should compensate but does not. It does not mention the required parameters (business_name and city) or explain their meaning, format, or constraints. The AI agent must infer from parameter names alone, which is insufficient.
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 'Resolve a single business to phone, address, website, hours, rating' clearly states the action (resolve) and the resource (single business) and lists specific output fields. It implicitly distinguishes from sibling tools like search_businesses (multiple results) and audit_website (specific URL audit), but does not explicitly differentiate.
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 no guidance on when to use this tool versus alternatives. With siblings like search_businesses and audit_website, it would be helpful to mention that this tool is for a single business lookup or contrast with batch operations. No hints on prerequisites or typical use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_tech_stackCInspectCMS, booking platform, email provider, analytics detected on a target URL.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes |
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description fails to disclose any behavioral traits such as whether it is read-only, if it initiates external requests, or if there are rate limits. With no annotations provided, this is a critical gap.
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 very short, which might be seen as concise, but it lacks necessary detail. It is front-loaded with the key capability but too terse to be fully useful.
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 there is an output schema (not shown), the description does not hint at the return structure, pagination, or error handling. For a detection tool, this incompleteness reduces agent confidence.
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 0% description coverage for the 'url' parameter. The description only mentions 'target URL' but does not clarify format, required protocol, or if the URL must be the domain or full path, leaving ambiguity.
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 detects CMS, booking platform, email provider, and analytics on a target URL. This distinguishes it from sibling tools like audit_website or find_no_booking, though it could be more explicit about the 'get' action.
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 sibling tools such as audit_website or bulk_audit. The description does not specify conditions, prerequisites, or alternatives, leaving the agent to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
score_leadCInspectComposite 0-100 lead score combining audit + demand signal.
| Name | Required | Description | Default |
|---|---|---|---|
| city | Yes | ||
| niche | No | ||
| business_name | Yes |
| Name | Required | Description |
|---|---|---|
No output parameters | ||
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 combining two signals but omits details on idempotency, side effects, permissions, or error handling. The description does not confirm if the tool is read-only or if it modifies data.
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 sentence, which is concise but lacks structure. It does not front-load critical information or organize details logically. It could be expanded without losing conciseness.
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 three parameters and an output schema, the description is too minimal. It does not explain how the score is computed or what the output represents (despite having an output schema, it is not referenced). The context of 'audit + demand signal' is vague.
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 0%, yet the description does not explain any of the three parameters (business_name, city, niche). It does not map 'audit' or 'demand signal' to these parameters, leaving their semantics completely unclear.
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 that the tool computes a composite 0-100 lead score from audit and demand signals. It specifies the range and components, making the purpose understandable. However, it does not use a strong verb like 'calculate' or 'generate', and it does not differentiate from sibling 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?
No guidance is provided on when to use this tool versus alternatives, such as when a lead should be scored or what prerequisites exist. Sibling tools are listed but not explained in relation to this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_businessesAInspectFind local businesses by niche + city. Yelp-backed; OSM fallback if Yelp not configured.
| Name | Required | Description | Default |
|---|---|---|---|
| city | Yes | ||
| limit | No | ||
| niche | Yes | ||
| state | No |
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It mentions data source fallback behavior but does not disclose read-only nature, rate limits, auth requirements, or what happens on no results. The output schema exists but isn't referenced. Adequate but could be more transparent.
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?
Extremely concise, single sentence. Front-loaded with purpose, then data source detail. No wasted words. Could be slightly more structured with separate sentences, but very efficient.
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?
Despite having output schema, the description lacks details on limit parameter pagination behavior and state usage. For a search tool with 4 parameters and no schema descriptions, the description insufficiently covers all aspects, though it adds fallback context.
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 0%. Description explains niche and city (used for searching) but does not define state or limit parameters. Without schema descriptions, the tool name alone provides minimal parameter guidance. Insufficient compensation for the 0% coverage.
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 'Find local businesses by niche + city', which is a specific verb+resource. It distinguishes from siblings like audit_website and get_business_details, which have different purposes.
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?
Description provides context on data sources (Yelp-backed with OSM fallback) and implies this tool is for general business search, while siblings are for specific tasks like auditing or details. However, lacks explicit when-not or alternative tool references.
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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