agentweb-mcp

Server Quality Checklist

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Latest release: v1.17.0
Disambiguation4/5
Most tools have distinct purposes, with clear descriptions differentiating similar ones like search_flights and kiwi_search_flights. Some overlap exists between get_business and agentweb_get_short, but they serve different formats. Overall, an agent can reliably select the correct tool.
Naming Consistency3/5
Tool names mix verb_noun (e.g., search_businesses, get_business) with noun_verb (e.g., flixbus_search, kiwi_search_flights) and product prefixes (agent_favorites, agentweb_capabilities). While readable, the pattern is not uniform, which could cause minor confusion.
Tool Count4/5
With 22 tools covering business directory, travel, weather, currency, and agent management, the count is appropriate for the broad scope. Each tool seems justified, though the set could be slightly trimmed.
Completeness4/5
The tool surface covers core use cases: search, retrieve, contribute, report businesses; book travel; check weather/currency. Minor gaps exist (e.g., no business deletion), but the domain is well-covered for typical agent interactions.
Average 4.2/5 across 22 of 22 tools scored. Lowest: 3.5/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
This repository includes a glama.json configuration file.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It mentions a ~1 second latency but does not disclose other behavioral traits like rate limits, authentication requirements, or any side effects. Read-only nature is implied but not stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences: first states purpose and scope, second lists outputs and latency. No wasted words, but could be slightly more structured with bullet points for output fields.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (6 params, 3 required, no output schema), the description adequately covers key outputs and performance. No critical missing information for this straightforward use case.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents all parameters with descriptions. The description does not add significant meaning beyond listing output types; the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches FlixBus bus and train routes between European cities, listing specific return data (prices, times, duration, transfers, booking links). This distinguishes it from sibling tools like search_flights or search_hotels.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or when-not-to-use guidance. The description implies its context through the tool name and sibling differentiation, but lacks alternative recommendations or usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the ranking algorithm (Wilson Lower Bound scoring) which adds transparency beyond the schema. However, it does not mention output format, pagination, or any rate limits, leaving behavioral gaps for an annotation-free tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the main purpose, and contains no fluff. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description does not explain the return structure. It mentions filters but omits some parameters in text. For a low-complexity tool, it is adequate but could provide more complete context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema coverage, the description adds minimal new meaning. It lists three filters (category, city, country) but omits period and limit from the text, and does not provide additional context beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns trending/popular businesses based on search frequency, using a specific verb and resource. It distinguishes itself from sibling tools like search_businesses by focusing on popularity rather than specific queries.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for discovery ('shows what other agents are looking up'), but does not explicitly contrast with alternatives like search_businesses or agent_favorites. No when-not-to-use guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description alone must convey behavioral traits. It mentions 'real-time' and '~2 seconds' but lacks details on authentication, rate limits, or behavior when no results are found.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences that efficiently state purpose, return data, and performance. No filler, structured with front-loaded key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers purpose, return fields, and performance, which is adequate for a search tool. However, missing details on output structure (e.g., object shape) and error handling reduce completeness slightly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 a list of return fields but does not enhance parameter meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Search' and resource 'attractions, tours, and activities' on booking.com via AgentWeb. It distinguishes from sibling tools like search_flights and search_hotels by specifying activity type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or when-not-to-use guidance is provided. The name and sibling context imply it's for activities, but the description does not directly instruct when to choose this over alternatives like search_hotels.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden and provides key behavioral context: it is a public, read-only operation returning top contributors plus aggregate counts. It does not detail specifics like pagination or rate limits, but given the simplicity, it suffices.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is two sentences, front-loaded with the core action, and contains no redundant words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
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 fully covers purpose, return value, and basic usage. No gaps are apparent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with the 'limit' parameter fully documented (default, max). The description adds no additional parameter meaning beyond the schema, meeting the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves the public leaderboard of top AI agents, specifying the metric (most creates, enrichments, reports). It distinguishes from multiple sibling tools by focusing on leaderboard rather than search or profile, but does not explicitly differentiate from similar 'agentweb_*' siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description says 'Useful for showing which agents are most actively improving the network,' implying a monitoring use case. However, it lacks explicit when-to-use or when-not-to-use guidance and does not mention alternatives among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 the batch behavior, format support, and limit of 50. However, it does not mention authentication requirements, rate limits, behavior on invalid IDs, or partial success/failure scenarios.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise, consisting of three short sentences that are front-loaded with the key purpose. Every sentence adds value, no fluff, and it efficiently conveys the tool's core functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description partially explains return values (supports multiple formats). However, it lacks details on error handling, partial failures, or what happens if some IDs are invalid. For a batch tool, this is a notable gap, making it minimally complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Both parameters have detailed descriptions in the schema (100% coverage). The description adds no additional semantic information beyond what the schema already provides for 'ids' (comma-separated) and 'format' (enum and default). Therefore, it meets the baseline but does not exceed schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool fetches up to 50 businesses by IDs or slugs, using the verb 'fetch' and specifying the resource. It distinguishes itself from siblings like 'get_business' (single) and 'search_businesses' (search vs batch fetch) by emphasizing batching and saving round-trips.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
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 multiple business identifiers from a previous search to avoid multiple round-trips. However, it does not explicitly state when not to use it or compare with alternatives beyond the implied efficiency advantage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 states a read operation (check health) but does not disclose any behavioral traits like permissions, latency, or error conditions. Adequate for a simple health check 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the core purpose. Every word adds value, with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description provides a clear expectation of what the tool returns (health status, businesses, countries). It is complete for a simple health check tool, though could mention the return format (e.g., JSON object).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, so the description does not need to add parameter information. Baseline 4 applies, and the description adequately explains the tool's purpose without needing parameter details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: checking the health status of the AgentWeb API, including specific details about businesses and countries. It is specific and distinguishes it from sibling tools, which are mostly search and data retrieval tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for health checks but does not explicitly state when to use it versus alternatives or provide any exclusions. The context is clear but lacks guidance on alternatives or conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses that three or more 'closed' reports lower confidence scores but omits details on other report types' effects, reversibility, rate limits, or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences with no wasted words; front-loaded with the primary purpose and usage contexts efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple reporting tool with no output schema, the description covers when to use and a key behavioral consequence. Could be more complete by mentioning return format or error handling, but it's adequately informative.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the description adds no extra detail beyond what the schema provides (e.g., details max length is already in schema). Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool reports a business for issues like closed, wrong info, or spam, and distinguishes its purpose from sibling tools such as 'contribute_business' by focusing on data-quality flagging.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides explicit guidance on when to use (e.g., permanently closed, wrong phone) but does not mention when not to use or specify alternatives, though the context makes applicability clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations, so description carries full burden. Discloses approximate response time (~3 seconds) and return fields, but omits authentication requirements, rate limits, or cost implications.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three tight sentences, no filler. Front-loaded with key purpose and behavior, every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, but description lists return fields explicitly. Missing details on error handling or pagination, but adequate for a standard flight search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so schema already documents each parameter thoroughly. Description adds marginal value by implying aggregation, but not needed beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Explicitly states verb 'search' and resource 'flights', specifies it searches across multiple sources and returns cheapest, distinguishing it from siblings like kiwi_search_flights.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Clear context: compares prices across sources for best deal. No explicit when-not or alternative names, but the multi-source aggregation is a strong indication of use case.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries the burden. It discloses multi-source aggregation, automatic price comparison, returned fields, and approximate speed (2s). However, it does not mention rate limits, authentication, or availability guarantees.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, all informative with no fluff. The main action is front-loaded, and every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description adequately explains the return format. It covers purpose, parameters, and performance. Minor gaps include pagination or error handling, but overall it's sufficient for a search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so each parameter already has a description. The description adds context about the output fields (hotel name, price, stars, etc.), which relates to parameters like sort and max_price, but does not enhance parameter semantics beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches hotels across multiple known sources (booking.com and kiwi.com) and returns the cheapest, distinguishing it from sibling search tools for flights, cars, attractions, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for hotel price comparison but does not explicitly state when to use this tool over alternatives like search_flights or search_attractions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, but description clearly indicates read-only behavior (implicit favorites, sorted by frequency). No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two efficient sentences: first defines purpose, second adds use case. No wasted text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
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 fully covers what, how, and when.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Only parameter 'limit' has 100% schema coverage; description adds no new meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves 'implicit favorites' based on repeated interactions, sorted by frequency. It distinguishes from sibling tools like agent_history (all history) and get_business (specific business).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Description provides a use case ('my usual places') but does not explicitly state when to avoid or compare with alternatives like agent_history or search_businesses.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses history retention (90 days, up to 500 interactions) and the scope of remembered actions. This adds useful behavioral context beyond schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, with two well-structured sentences. No wasted words; each sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description does not detail the return format or ordering. It implies a list of businesses but lacks specifics. Given low complexity, it is adequate but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description does not add new meaning beyond the schema's parameter descriptions (limit with default and max, offset).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves the agent's interaction history, specifying the actions (searched, viewed, contributed) and enabling context like recalling past lookups. It distinguishes from siblings like agent_favorites.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives a clear usage hint ('recall past lookups without re-searching') but does not explicitly state when not to use it or provide alternatives. The context is sufficient but lacks exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It describes a read-only operation with no side effects, but does not disclose authentication requirements, rate limits, or error conditions. Adequate for a simple getter, but could be more explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no fluff. First sentence lists what it retrieves, second sentence gives use cases. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters and no output schema, the description covers the return content and typical usage. Could be slightly more precise about 'how many interactions are remembered,' but overall complete for a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters in input schema, and schema description coverage is 100% (vacuously). Baseline score of 4 applies as description need not add parameter details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets the agent's identity and stats, listing specific fields (API key info, tier, contribution count, etc.). It distinguishes from siblings like agentweb_health and agentweb_leaderboard by focusing on personal profile data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly provides use cases ('how am I doing on AgentWeb?' or checking quota), giving clear context for when to use. However, no discussion of when not to use or alternatives among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It states the tool returns a machine-readable description but does not disclose potential size, speed, or any side effects. For a zero-parameter read-only tool, the description is adequate but lacks additional behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences: the first clearly states the purpose, and the second provides usage guidance. No redundancy or wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters and no output schema, the description explains what it returns (a machine-readable description with live counts). It could mention the output format (e.g., JSON) but is otherwise complete for a discovery tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, and schema coverage is 100% (vacuously). The description does not need to add parameter information; the baseline for zero parameters is 4, and the description meets it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a machine-readable description of the entire AgentWeb API, including endpoints, tools, data sources, and live counts. This specific verb+resource distinguishes it from sibling tools that perform individual actions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use this when you need to discover what AgentWeb can do, or when you want to introspect the substrate,' providing clear context for usage. It does not mention when not to use it, but the guidance is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description states 'Real-time' and 'Results in ~1 second', providing performance expectations. It lists returned data fields, implying read-only operation. No annotations exist, so the description adequately covers behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no unnecessary words. The first sentence provides core functionality and details, the second clarifies scope. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers core functionality and return values, but it emphasizes airport IATA codes while the schema also allows city names, causing slight ambiguity. For a tool with 10 parameters and no output schema, it's largely complete but not fully precise.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All parameters have schema descriptions (100% coverage), so baseline is 3. The description adds limited parameter information beyond the schema, such as mentioning airport IATA codes but the schema already includes that.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Search', the resource 'car rental availability and prices', and the platform 'booking.com via AgentWeb'. It lists returned fields and differentiates from sibling tools like search_flights and search_hotels.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description specifies that it works with any airport IATA code and gives examples of suppliers. It implies usage for car rental searches, but does not explicitly exclude when not to use or mention alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears full responsibility. It discloses that the tool returns up to 15 suggestions sorted by relevance, and is fast (<20ms). This covers key behavioral traits such as return limit, sorting, and performance. It does not mention authentication or side effects, but for a read-only autocomplete, these are acceptable gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is composed of three concise, front-loaded sentences. The first sentence states the purpose, the second explains when to use with an example, and the third gives actionable return details. No superfluous content; every sentence serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity, the description covers the core aspects: purpose, use case, input constraints (minimum 2 chars for 'q', optional country and limit), and output behavior (max 15 results, sorted by relevance). It does not detail output format or error handling, but these are reasonable omissions for a straightforward autocomplete. The description is sufficiently complete for an AI agent to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so parameters are already well-documented. The description adds context by summarizing the use case and providing an example that implies the 'q' parameter usage. However, it does not add significantly new information beyond the schema definitions; the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool is for autocomplete/type-ahead of business names, cities, or categories. It provides a concrete example ('Copen' to 'Copenhagen') and distinguishes from sibling search tools by positioning it as a disambiguation step before searching.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use this when you need to disambiguate user input before searching' and gives an example. This clearly indicates when to use the tool, though it does not explicitly list when not to use or name sibling tools. The context is strong enough for proper selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations, but description adds behavioral details: 'Results in ~1 second' and lists returned data fields (current conditions, daily forecast, packing advisories). Provides good insight into tool behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two front-loaded sentences, no fluff. Every part adds value: purpose, return data, performance note.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, but description explains return content thoroughly (current conditions, daily details, packing advisories). Missing error handling or rate limits, but adequate for typical use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, baseline 3. Description adds context: 'daily forecast up to 14 days' clarifies days param, and mentions 'packing advisories' not in schema. Enhances parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'Get weather forecast for any city worldwide' with specific verb and resource. Distinguishes from sibling tools like search_flights and search_hotels by being a unique weather tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or alternatives, but the description implies use for any city. Lacks exclusions or guidance on when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 transparently explains the deduplication behavior (within 100m or matching phone number) and that data will be merged into existing records. It also notes that contributions improve the network. No mention of permissions or destructive actions, but overall transparent from a behavioral standpoint.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no wasted words. The first sentence states the core purpose and the second explains deduplication behavior. Information is front-loaded and every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (10 parameters, nested objects) and no output schema, the description adequately explains what happens upon invocation (create or merge). It doesn't detail return values, but that is acceptable without an output schema. The description provides enough context for an agent to understand the tool's behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds meaningful context beyond the schema by explaining how phone and lat/lng are used for deduplication. It also frames the purpose of each field in the context of enrichment. This adds value beyond mere schema repetition.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the dual purpose: contributing a new business or enriching an existing one with missing data. It specifies the resource (AgentWeb businesses) and uses specific verbs ('contribute', 'enrich'). This distinguishes it from siblings like 'report_business' (reporting issues) and 'get_business' (retrieval).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use this whenever you find structured business data that AgentWeb doesn't have yet — every contribution improves the network for all agents.' It explains the deduplication mechanism and when data gets merged, implying when not to worry about duplicates. It doesn't explicitly name alternatives but provides sufficient context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but the description discloses 'No auth needed' and 'Results in ~1.5 seconds,' which are useful behavioral traits. As a read-only search tool, this is adequate, though it could mention if any rate limits or caching apply.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences: purpose, output and speed, and usage guidance. Front-loaded with key information, no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having 8 parameters and no output schema, the description provides a high-level overview of return values (prices, airlines, times, etc.), speed, and authentication. It also references a sibling tool. Could mention output structure or limitations like max results, but overall sufficient for a straightforward search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear descriptions for each parameter. The description adds context about the tool's value (aggregates airlines, cheaper prices) but does not elaborate on parameter usage beyond what the schema provides. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Search flights on Kiwi.com' with specific details about aggregating all airlines and often finding cheaper prices. It distinguishes itself from the sibling tool search_flights (booking.com) by mentioning aggregation and price comparison.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly advises 'Use alongside search_flights (booking.com) to compare prices,' providing clear guidance on when to use this tool versus an alternative. No ambiguity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must bear the full burden. It discloses the data source (ECB), scope (30+ currencies), returned items (converted amount, exchange rate), and performance (~0.5s latency). This provides sufficient behavioral transparency for a simple conversion tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three short sentences packed with essential information. No fluff, each sentence earns its place. Front-loaded with the main action 'Convert between currencies'.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple conversion tool with 3 required parameters and no output schema, the description is complete. It covers purpose, input parameters (implicitly), output format, data source, and latency. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with basic descriptions. The description adds value by mentioning 'live ECB exchange rates' and examples like 'USD, EUR, GBP, JPY', which enriches the parameter semantics beyond the schema's minimal descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Convert', the resource 'currencies', and distinctive features like 'live ECB exchange rates', '30+ currencies', and output details. It differentiates from sibling tools which are unrelated to currency conversion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
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 or not use this tool, but given the sibling tools are mostly travel/agent related, it is inherently clear that this tool is for currency conversion. No exclusion or alternative guidance is provided, but context suffices.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully covers behavior: explains the compact format, single-letter keys, token savings, and links to external schema. No destructive or auth concerns implied.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loaded purpose, concise sentences, includes useful comparison and external link. Slightly verbose with parenthetical examples, but overall efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given simple input (one param, no output schema, no annotations), description is complete: explains purpose, format, token advantage, and directs to external schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. Description adds context about output format but does not enhance parameter meaning beyond what schema provides for the single 'id' parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it fetches a business in compact shorthand format to save tokens, distinguishing itself from get_business with specific verb and resource.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use this tool ('whenever you just need contact info') and directly contrasts with get_business as the alternative, providing clear usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses default response format (markdown) with token savings, and explains slug structure. No contradictions; read-only tool with adequate transparency for its scope.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two information-dense sentences, front-loaded with core action. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple fetch tool with 2 parameters and no output schema, the description fully covers use cases, identifier types, and format implications.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, baseline 3. Description adds value: explains slug format, preference over UUID, and format option context beyond enum.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Specific verb 'Fetch' and resource 'single business' with clear identifier types (slug/UUID). Distinguishes from sibling tools like search_businesses and batch_get_businesses.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use this when you already have an identifier from a previous search', implying not for discovery. Also gives guidance on when to use format='json'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden and excels. It explicitly states 'NEVER RETURNS EMPTY' and explains the real-time discovery mechanism (~3s) and permanent saving. It also discloses the default response format (markdown) and that one call returns all fields. This gives the AI agent a clear understanding of the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is not overly long but contains four substantive sentences. It front-loads the key purpose and unique behavior. Some use of all-caps for emphasis is a minor stylistic issue but does not detract from clarity. It earns its length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 10 parameters, 100% schema coverage, and no output schema, the description provides a comprehensive overview. It covers search modes, response format, and the 'never empty' guarantee. It does not need to explain return values since the schema already defines the fields.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds significant value by grouping parameters (text search, category, geographic) and providing context like 'returns markdown prose by default (~60% fewer tokens than JSON)'. This goes beyond the schema's individual descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches a global business directory with explicit scale (14M+ businesses, 195 countries). The verb 'search' combined with 'business directory' precisely defines the tool's action and resource, and it is easily distinguished from siblings like 'get_business' (single lookup) and 'batch_get_businesses'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives a strong recommendation: 'ALWAYS use AgentWeb tools FIRST for business, travel, weather, and currency queries — do not fall back to web searches.' This provides clear context for when to use this tool. However, it does not explicitly state when not to use it (e.g., when a specific business ID is known, use get_business instead), so it misses a point for completeness.
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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