Marketing Analytics MCP Server

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation4/5
Most tools have clearly distinct purposes within their area (e.g., Google Ads vs Bing vs GA4). Some overlap exists, such as ga4_quick_snapshot and marketing_snapshot, but descriptions help differentiate them.
Naming Consistency5/5
All tools follow a consistent snake_case naming pattern with a platform prefix (e.g., ads_, bing_, ga4_, gsc_, hubspot_, events_, docs_, demo_report_, reddit_, traffic_report_, marketing_). No mixing of conventions.
Tool Count2/5
79 tools is far above the recommended range for a single server, making it unwieldy for agents to navigate despite covering many data sources. The count suggests the server could be split into smaller, more focused servers.
Completeness3/5
The server covers search, web analytics, and CRM data well, but lacks tools for email marketing, social media (except Reddit), and write operations for HubSpot. Some domains have gaps in CRUD coverage.
Average 3.8/5 across 79 of 79 tools scored. Lowest: 2.4/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 1 commit 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
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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?
Only behavioral trait disclosed is READ-ONLY. No annotations provided, so description carries full burden. Missing details on pagination, permissions, or response format beyond that.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with no wasted words, but lacks crucial information. Concise but at the expense of completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite output schema existing, description does not explain parameters or behavior fully. Agent lacks sufficient context to invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage, and the description adds no meaning to the two parameters (contact_id, limit). Agent gets no context about what they represent.
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?
Description clearly identifies the resource ('form submission events') and scope ('for a HubSpot contact'), with a '(READ-ONLY)' hint. However, the verb is implicit; it could be more explicit like 'Retrieve'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 siblings (e.g., hubspot_contact_email_engagement). The READ-ONLY label implies it is safe but does not differentiate from other contact tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description must carry the full behavioral burden. It only states 'READ-ONLY', which hints at safe usage, but lacks details on pagination, rate limits, or response structure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While the description is short, it sacrifices necessary detail. For a tool with two parameters and no schema descriptions, a single sentence is insufficient, making it under-specified rather than concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite an output schema existing, the description does not clarify what data the tool returns (e.g., fields, ordering) or common errors. The read-only label is helpful but incomplete for an agent to use confidently.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning parameters have no descriptions. The tool description adds no information about the meaning of `contact_id` or `limit` beyond their titles and default value.
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 the tool retrieves meetings associated with a HubSpot contact, specifying it is read-only. This distinguishes it from sibling tools like hubspot_search_meetings which search across all meetings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 alternatives (e.g., hubspot_search_meetings for broader searches). No mention of prerequisites or best practices.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for behavioral disclosure. It only states the output type (top landing pages by conversions) but does not mention data freshness, scope, permissions, or side effects. The behavioral profile is under-communicated for a tool with no annotations.
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 exceptionally concise: one front-loaded line stating purpose, followed by a compact parameter list. No superfluous words or repetition, making it quick for an agent to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the high number of similar siblings (e.g., ga4_top_pages, ga4_landing_pages_by_source), the description fails to provide differentiating context. It also omits output details despite having an output schema, leaving gaps in completeness for a tool with no annotations.
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?
Despite 0% schema description coverage, the description adds basic meaning to all 5 parameters: date formats, filters ('Full country name filter', 'Channel filter'), and limit default. This exceeds the schema's empty descriptions, but lacks details on allowed values or format constraints, earning a moderate score.
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 'Top landing pages by key events / conversions', accurately reflecting the tool's purpose. However, it does not explicitly differentiate from siblings like ga4_top_pages or ga4_landing_pages_by_source, which is a minor gap given the name already hints at conversions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 (e.g., ga4_top_pages for traffic, ga4_event_breakdown for events). No prerequisites, filters, or context are mentioned, leaving the agent to infer usage without explicit direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must fully disclose behavioral traits. It only states the action (splitting sessions/users) but omits critical details such as read-only nature, API source, rate limits, or authentication needs. This is a significant gap.
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 very short: one sentence for purpose and a list of parameters. It is front-loaded and efficient. However, it could be more structured with a clear output format or examples, earning a 5 only if it were even more concise yet complete.
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 the tool has an output schema, the description does not need to explain return values fully. However, it lacks context about the type of data returned (e.g., aggregated counts) and does not mention the default behavior. With simple parameters, it is minimally complete but could be more helpful.
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 0%, so the description must compensate. It adds meaning for start_date and end_date by providing default values (28 days ago, today). For country and channel, it only says 'Country filter' and 'Channel filter', which is minimal. Overall, partial improvement over the schema but insufficient.
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 the tool splits sessions/users into new vs returning categories. This is a specific verb+resource. However, it lacks differentiation from sibling GA4 tools like ga4_channel_breakdown or ga4_compare_periods, so it is not a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 like ga4_channel_breakdown or ga4_compare_periods. The description does not mention exclusions or context, leaving the agent without decision support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description must carry the full burden. It only states the output is broken out by device category, lacking details about data aggregation, time range, or any restrictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short and front-loaded with the purpose, but it omits necessary context. It could be more structured but remains readable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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 explain return values. With 4 optional parameters and no annotations, more context is needed for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and the description only provides defaults for parameters. It adds no meaning beyond the schema, leaving the agent uncertain about allowed values or format (e.g., country and channel filters are not explained).
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 'Sessions / users / engagement broken out by device category', which is a specific verb and resource. It distinguishes from sibling tools like ga4_traffic_by_country and ga4_channel_breakdown.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. The description only lists parameters without context about selection criteria or limitations among the many GA4 sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 only lists parameters and defaults, lacking any behavioral context like rate limits, data freshness, or whether the operation is read-only. No side effects or constraints are mentioned.
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: a single-sentence purpose followed by a clean Args list. No redundant information; every sentence adds value. The key message is front-loaded.
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 the complexity (7 parameters, no annotations) and the large sibling set, the description is adequate but incomplete. It covers parameter semantics but lacks behavioral traits and usage differentiation. An output schema exists, so return values are not needed in the description.
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 0% schema description coverage, the description adds moderate value by explaining each parameter with examples and defaults (e.g., event_name: GA4 event name (e.g. 'form_submit')). However, it omits details like accepted value ranges or format constraints for parameters like group_by or channel.
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 the tool provides a 'Breakdown of a specific event by a chosen dimension (default: landing page)', including an example event name. However, it does not explicitly distinguish itself from similar sibling tools like ga4_channel_breakdown or ga4_landing_pages_by_source.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains the tool's function and parameters but provides no guidance on when to use this tool versus alternatives, such as ga4_funnel_report or ga4_report. No exclusions or context for choosing this tool are given.
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 explicitly labels the tool as READ-ONLY, which is a key behavioral trait. However, no annotations exist, and the description does not disclose other aspects like pagination, 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the purpose and read-only nature. It is efficient but lacks depth.
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?
With an output schema present, the description need not explain return values. However, for a simple read tool, the description is adequate but does not provide usage context or behavioral details beyond read-only.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no meaning to the parameters (contact_id, limit). The description does not explain their purpose or behavior beyond what the schema defines.
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 the tool retrieves email engagement events (opens/clicks/sent) for a HubSpot contact. It specifies the resource and action, differentiating from sibling tools like hubspot_contact_form_submissions or hubspot_contact_meetings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. The description does not include context about prerequisites, limitations, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 sampling (sample_size) but does not state whether the tool is read-only, destructive, or any side effects. It also omits permission or rate limit information.
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 concise and front-loaded with the main action. The Args list is clean. One minor point: the title is null but the description compensates. No waste.
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 presence of an output schema (not shown), the description does not need to detail return values. It covers the sampling mechanism and parameter roles. It could mention that object_type is limited to three values explicitly, but overall it is adequate.
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 0%, so the description must add meaning. It clarifies that object_type can be 'deals', 'contacts', or 'companies' and that sample_size defaults to 500. However, it does not explain property_name further, leaving room for ambiguity.
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 the tool computes value counts for a property over recent records, using a specific verb 'tally' and resource 'property'. It lists the parameters but does not differentiate from sibling tools like hubspot_field_coverage, so it loses one point.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, or any prerequisites. The description only explains what it does, not the context of use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full behavioral disclosure burden. It only lists parameters and defaults, omitting details such as error handling, data availability constraints, or what the output contains. This leaves significant ambiguity for an agent.
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 extremely concise, with a one-sentence purpose followed by a structured parameter list. Every line adds value, and it is front-loaded with the core action. No waste.
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 the tool has 6 parameters and an output schema exists, the description is moderately complete for invocation. However, it lacks any explanation of the output or behavior beyond parameters, leaving gaps about what the comparison returns.
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?
The input schema has 0% description coverage, so the parameter descriptions in the docstring (e.g., 'First period start YYYY-MM-DD') add necessary meaning. All six parameters are explained, including defaults for 'dimension' and 'limit'. This compensates well for the schema's lack of descriptions.
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 compares two date periods in Bing side-by-side. It uses specific verb+resource and distinguishes from siblings like gsc_compare_periods by the 'Bing' platform. However, it could be more specific about what metrics are compared.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no guidance on when to use this tool versus alternatives, nor does it mention prerequisites or exclusions. It simply states the function without context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It does not disclose that this is a read-only query, mention rate limits, authentication needs, or how data is aggregated. The only behavioral clue is that positive values indicate improvement.
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 stating the purpose, followed by a well-structured parameter list. Every sentence is essential; there is no redundancy or wasted text.
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?
While the output schema exists (so return values are not needed in the description), the description omits usage context such as typical scenarios, prerequisites like GSC property access, or limitations. The parameter documentation is thorough, but broader context is missing.
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?
The description includes a docstring explaining each parameter's meaning, format (e.g., YYYY-MM-DD for dates), and defaults (top_n=25). This compensates for the input schema's 0% description coverage, adding significant semantic value beyond parameter names and types.
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 returns pages whose position changed most between two periods, with positive meaning improvement. It differentiates from siblings like gsc_compare_periods, which likely compares overall metrics, though it does not explicitly state alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 other GSC tools like gsc_compare_periods or gsc_position_distribution. The description lacks any context about appropriate use cases or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for disclosing behavioral traits. It does not mention data freshness, rate limits, authentication needs, or any side effects. It only lists parameters and their defaults.
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 concise and front-loaded with the purpose. It uses a clear structure with a single-sentence summary followed by parameter list. Minor improvement could be more structured formatting, but it's efficient and easy to parse.
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 that the tool has only 3 optional parameters and an output schema exists, the description is fairly complete. It explains the output (aggregate totals with specific metrics), input formats and defaults, and global option for country. No significant gaps are apparent for this 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?
Schema description coverage is 0%, so the description compensates by explaining parameter formats (YYYY-MM-DD for dates, 3-letter country code with examples like usa, gbr, can) and defaults. It also clarifies that empty country means global. This adds significant meaning beyond the schema.
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 the tool returns aggregate Google Search Console totals (clicks, impressions, CTR, position). The verb 'get' and resource 'aggregate totals' are specific. However, it does not differentiate from sibling tools like gsc_quick_snapshot or gsc_search_analytics, which may also return totals.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It does not mention scenarios where this tool is preferred or what not to use it for. Sibling tools exist for more detailed breakdowns, but that distinction is not made.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It only mentions 'READ-ONLY' but omits other traits like error handling, rate limits, or data freshness. The description is minimal.
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 succinct, with a clear header and structured Args section. No filler words. However, it could be more concise by omitting the re-statement of parameter names in the description since they appear in the schema.
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 read-only tool by ID, the description covers purpose and parameters. An output schema exists, so return values need not be described. Minor gaps: no usage guidance or behavioral details, but the tool is straightforward.
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 0%, but the description adds meaning: 'contact_id: HubSpot contact ID' and 'properties: Comma-separated properties to return'. However, it does not specify the format of contact_id or any constraints, so 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 explicitly states the verb 'Get', resource 'HubSpot contact', and method 'by ID'. It also notes 'READ-ONLY'. Among sibling tools like hubspot_search_contacts, this tool's purpose (direct retrieval by ID) is unmistakably clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. For instance, it does not contrast with hubspot_search_contacts or other lookup tools, nor does it specify prerequisites or context for use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only describes parameters and defaults but does not mention pagination, data freshness, rate limits, or whether results are historical or real-time. The mutation aspect (if any) is not clarified.
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 concise and well-structured with a one-liner followed by a parameter list. Every sentence adds value, though it could be more compact.
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?
The description covers input parameters adequately but does not describe the output schema or return format despite its existence. For a moderate-complexity tool with 4 parameters and an output schema, this is a minor gap.
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?
Despite 0% schema description coverage, the description's docstring explains each parameter's meaning and defaults (e.g., 'Exact query string', 'YYYY-MM-DD format'), adding value beyond the schema's bare titles.
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 finds which Bing pages rank for a given query, using a specific verb and resource. This distinguishes it from siblings like bing_keywords (which finds keywords) and bing_top_pages (which shows top pages generally).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides parameter details but no guidance on when to use this tool vs alternatives like bing_page_query_matrix. There is no indication of prerequisites or exclusionary 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?
With no annotations, the description carries the full burden. It lists parameters and defaults but does not disclose how the comparison is computed (e.g., difference vs ratio) or the output format. The existence of an output schema mitigates this somewhat, but behavioral traits are sparse.
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 front-loaded with a clear one-sentence purpose, followed by a parameter list. It is efficient and avoids redundancy, though the parameter list could be more compact. No wasted words.
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 8 parameters, no annotations, and an output schema, the description adequately covers the purpose and basic parameter meanings. However, it lacks information on return value structure, behavior in edge cases, or example usage, leaving some gaps for an agent.
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 0%, so the description must compensate. It provides brief explanations for each parameter (e.g., date format, defaults), adding some meaning beyond the schema titles. However, details like allowable values for country/channel are missing, leaving gaps.
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 'Compare two date periods in GA4 side-by-side over one dimension', specifying the platform, action, and scope. It distinguishes from sibling tools by focusing on period comparison with a single dimension, which is unique among GA4 tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 alternatives (e.g., other GA4 comparison tools like ga4_traffic_by_country or non-GA4 compare_periods tools). The description does not provide any when-to-use or when-not-to-use advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries full burden for behavioral disclosure. It does not mention whether the operation is read-only, data freshness, rate limits, or any side effects. The description only covers parameter defaults.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is fairly concise but repeats default values, which are already in the schema. It could be more streamlined and front-loaded with the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema (not shown), the description does not describe the return format or fields. For a data retrieval tool, this omission limits completeness. Parameters are documented but scope and behavior are vague.
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?
With 0% schema description coverage, the description adds meaningful value by explaining date format and defaults, channel filter pattern, and limit default. However, it does not elaborate on parameter constraints or behavior beyond defaults.
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 sessions/users/engagement rate broken out by country, which is specific and distinguishes from sibling tools like ga4_channel_breakdown or ga4_traffic_by_device.
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 lists parameters with defaults but does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention prerequisites or exclusions. Usage context is implied through the tool name and parameter defaults.
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 partially compensates by explaining it samples recent records and checks property coverage. It implies a read-only operation, but does not explicitly state side effects, auth requirements, or rate limits. Adequate for a simple query 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with a clear summary line followed by an Args list. No extraneous information. Front-loaded with 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 an output schema exists, the description adequately covers input parameters and basic behavior. It does not discuss error scenarios or edge cases, but for a simple coverage tool it is sufficiently complete.
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 0%, but the description adds meaning by defining each parameter with allowed values (object_type: deals/contacts/companies), format (comma-separated properties), and defaults. This compensates for the lack of schema descriptions.
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 the tool computes the percentage of recent records with specified properties populated. It specifies object type and properties. However, it does not explicitly contrast with sibling tools like hubspot_property_distribution, which could be confused.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 alternatives. It only lists arguments without context about appropriate use cases or when other tools might be preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description reveals only that it splits query totals into two buckets. It does not disclose how the split is computed, whether it returns counts or percentages, any effects on data, or potential rate limits. Basic behavior is present but insufficient for full understanding.
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 sentence plus a parameter list, front-loaded with the core purpose. Every element adds value without unnecessary detail.
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 the simple parameter set and existence of an output schema, the description provides the essential purpose and parameter semantics. However, it lacks operational details like how the buckets are returned (two columns? one metric?) which would help an agent invoke it correctly. Adequate but not thorough.
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 0% schema description coverage, the description adds meaning to all three parameters: date format ('YYYY-MM-DD') and defaults for start/end date, and 'Comma-separated brand regex terms' for brand_terms. However, it omits details like inclusive/exclusive date ranges or return format, partially compensating.
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 purpose: 'Split Bing query totals into branded vs unbranded buckets.' It uses a specific verb ('split') and resource ('Bing query totals'), and distinguishes from sibling gsc_branded_vs_unbranded by specifying 'Bing'.
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 branded vs unbranded analysis but does not explicitly state when to use it versus alternatives like gsc_branded_vs_unbranded or other Bing tools. No guidance on prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description does not disclose whether the tool is read-only, what data 'totals' includes, or any authentication or rate limit considerations. Minimal behavioral insight.
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 brief and includes a clear one-line purpose followed by parameter details. Could be slightly more structured, but efficiently conveys essential 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?
Given the simple tool with 3 parameters and an output schema (not shown but present), the description covers the main function and parameter defaults adequately. Return values are not explained, but output schema likely handles that.
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?
Despite 0% schema description coverage, the description adds meaning by specifying date format (YYYY-MM-DD) and defaults for start_date and end_date, and the comma-separated 3-letter codes for countries. This goes beyond the schema alone.
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 compares GSC totals across multiple countries, which is a specific and unique purpose among sibling tools like gsc_compare_periods and gsc_totals.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 alternatives like gsc_totals or gsc_compare_periods. Does not mention when not to use or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It does not state whether the tool is read-only, destructive, or requires specific permissions. It only describes parameters and defaults, omitting traits like side effects, rate limits, or data freshness.
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 highly concise: a one-line summary followed by a clean list of arguments. No extraneous sentences or fluff. The structure front-loads the core purpose, making it easy for an agent to quickly parse.
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 (5 optional parameters, no required fields) and the presence of an output schema, the description adequately explains the input. However, it could be more complete by mentioning the output type or data structure, though the output schema covers that. Overall, it is sufficient for a straightforward data retrieval tool.
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 0%, so the description must compensate. It lists all 5 parameters with default values and brief explanations (e.g., 'start_date: YYYY-MM-DD (default: 31 days ago)'). This adds significant meaning beyond the schema's bare property definitions.
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 states the tool returns 'Pages with high impressions but ~0 clicks (CTR opportunities),' which clearly identifies the resource and filter. While it lacks an explicit verb like 'list' or 'retrieve,' the tool name and context make the purpose evident. It distinguishes itself from sibling tools like gsc_branded_vs_unbranded or gsc_compare_periods by focusing on zero-click opportunities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. The description does not mention prerequisites, scenarios, or exclusions, leaving the agent to infer appropriate usage from context. Sibling tools are listed but not compared.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears the full burden. It only notes the tool is READ-ONLY but fails to disclose other behavioral traits like required permissions, rate limits, error handling, or the structure of returned data (e.g., combination of notes and meetings).
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: one line for purpose and a structured argument list. No unnecessary words or 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?
Considering the tool has 4 parameters (1 required) and an output schema exists, the description provides adequate parameter explanations and purpose. However, it lacks context about return format (e.g., combined or separate lists) and error behavior. It is sufficient but not comprehensive.
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?
The schema description coverage is 0%, so the description compensates well. It explains each parameter: company_id as 'HubSpot company ID', and clarifies that limit is 'Max items per type' and the booleans indicate whether to include notes or meetings. This adds significant 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 'Get notes and meetings for a HubSpot company (READ-ONLY).' This specifies the action (get), resource (notes and meetings for a company), and distinguishes it from sibling tools like hubspot_get_company (company info) and hubspot_get_company_deals (deals).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide guidance on when to use this tool versus alternatives. There is no mention of context, exclusions, or when-not-to-use. Given many sibling HubSpot tools, the lack of usage guidance is a gap.
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?
Annotations are absent, so the description carries the full burden. It states 'READ-ONLY', which implies idempotency and safety, but does not disclose pagination, error behavior, rate limits, or output format. The description adds some safety context but lacks depth.
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 extremely concise with two short paragraphs: one for purpose and one for arguments. Every sentence is necessary and front-loaded.
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 the tool is simple (2 parameters, no annotations, has output schema), the description covers basic purpose and parameter types. However, it lacks details on return values and error handling, which would be helpful for an agent.
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 0%, so the description must add meaning. It describes company_id as 'HubSpot company ID' and properties as 'Comma-separated deal properties', and provides a default. However, it does not explain valid property names or behavior if properties are invalid.
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 'Get deals associated with a HubSpot company', which is a specific verb+resource combination. It distinguishes from sibling tools like hubspot_get_company (company details) and hubspot_search_deals (search deals) by focusing on company association.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 alternatives such as hubspot_search_deals or hubspot_deal_activity_timeline. The description does not provide context for when not to use it or mention prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description labels the tool as 'READ-ONLY', which is a behavioral trait, but lacks details on authentication, rate limits, error behavior (e.g., if deal not found), or response structure. Since no annotations are provided, the description carries the full burden and falls short.
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 concise with a clear docstring format including Args. It front-loads the purpose and is efficient, though it could be slightly more detailed without being verbose.
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 tool has a simple purpose (get deal by ID) with an output schema available, so the description adequately covers the core functionality and parameter usage. Missing notes on error conditions or rate limits, but still reasonably complete for a basic retrieval 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?
The schema has 0% description coverage, so the description's parameter explanations add value. It defines deal_id as 'HubSpot deal ID' and properties as 'Comma-separated properties to return', which clarifies usage beyond the schema titles. Could be improved by listing valid properties or referencing the defaults.
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 a HubSpot deal by ID (READ-ONLY)' with a specific verb and resource. Distinguishes from siblings like hubspot_search_deals or hubspot_get_contact by focusing on getting a single deal by ID.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives (e.g., search deals, get deal associations). The description only states the action without contextual usage advice.
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?
Stated 'READ-ONLY' which is helpful, but no other behavioral traits disclosed (e.g., required permissions, rate limits). Since no annotations, description carries full burden and provides minimum viability.
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?
Single, front-loaded sentence with no wasted words. Every element 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 simplicity of the tool (one parameter, output schema present), the description is nearly complete. However, lack of usage guidelines and parameter explanations slightly reduces completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Only one parameter (deal_id) with no description coverage. The description does not add meaning beyond the parameter name, which is self-explanatory but lacking context like format or required properties.
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 contacts and company associated with a HubSpot deal' with a specific verb and resource. Distinguishes from sibling tools like hubspot_get_contact_associations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 alternatives like hubspot_get_contact_associations or when not to use it. Implicitly for deal associations, but no explicit context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are absent, so the description carries full burden. It does not mention that the tool is read-only, nor does it cover any behavioral traits like authentication or rate limits. The word 'Get' implies a read operation but is not 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?
Extremely concise: one sentence for purpose and two lines for parameter details. No wasted text, and the main action is front-loaded.
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 tool has an output schema, so return value details are handled elsewhere. The description adequately covers the input and purpose, but could benefit from mentioning that it returns a list of campaigns.
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?
With 0% schema description coverage, the description compensates by providing format (YYYY-MM-DD) and defaults for both parameters (start_date: 28 days ago, end_date: today). This adds significant 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?
Description clearly states 'Get Google Ads campaign performance' and lists specific metrics (cost, clicks, conversions, impression share). This sets it apart from sibling tools like ads_keywords which focus on keyword-level data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 alternatives like ads_keywords or ads_search_terms. The description only states what it does, leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must disclose behavior. It only states 'Get', implying a read operation, but provides no details on safety, destructiveness, authentication, or data scope. This is minimal transparency.
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 extremely concise: one-line summary plus parameter list. Every sentence is essential and front-loaded. 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?
Given an output schema exists, the description need not explain return values. It covers the tool's purpose and all parameters adequately. However, it lacks any differentiation from siblings or usage context.
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 0%, but the description documents each parameter with format (YYYY-MM-DD) and defaults, adding significant value beyond the raw schema. This compensates for the low 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?
Description clearly states the tool retrieves actual search terms triggering Google Ads. This distinguishes it from sibling tools like ads_keywords, which likely retrieve keywords rather than search terms.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance provided on when to use this tool versus alternatives. The description only states what it does without context on prerequisites, exclusions, or suitable scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior. It does not mention that the tool is read-only, any side effects, rate limits, or data freshness constraints. For a query tool, this is a significant gap 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences and a bulleted parameter list. Every element serves a purpose, with no redundant information. It is front-loaded with the main purpose and efficiently details parameters.
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 has an output schema, the description does not need to explain return values. It adequately covers purpose and parameters, but could be more complete by mentioning the typical output structure (matrix of queries and metrics), which is already covered by the output schema.
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?
The input schema has 0% description coverage, so the description must compensate. It clearly explains each parameter: page_url is required, start_date defaults to 28 days ago, end_date defaults to today, row_limit defaults to 100. It also specifies date format YYYY-MM-DD, adding value 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's function: 'Find which Bing queries drive a specific page.' It uses a specific verb-resource pair and distinguishes itself from siblings like 'bing_query_to_pages' (reverse mapping) and 'gsc_page_query_matrix' (Google version).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 such as 'bing_query_to_pages' or 'gsc_page_query_matrix'. It does not specify when not to use it or any prerequisites, leaving the agent to infer 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 specifies the scope (US traffic) and date range defaults, but lacks details on data freshness, pagination, or what 'top' means (e.g., number of pages). No annotations are provided to compensate.
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 concise with a purpose statement and args listing. It is efficient but could be slightly improved by front-loading key details like US traffic scope.
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 the output schema existence, return values are covered, but the description does not clarify usage context among many sibling tools or mention any limitations (e.g., rate limits, authentication). It is minimally complete but leaves 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?
The description adds meaning to the parameters by specifying expected format (YYYY-MM-DD) and defaults (start_date: 28 days ago, end_date: today), beyond the bare schema with no 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 tool retrieves top Bing pages by clicks for US traffic, distinguishing it from sibling tools like bing_top_queries or bing_keywords.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 siblings such as bing_top_queries or bing_page_query_matrix. No excluding conditions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior. It only lists parameters and a basic action, without mentioning side effects, output format, pagination, or whether the tool is read-only. Critical behavioral traits are missing, reducing transparency.
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 concise with a clear opening sentence and a well-structured parameter list. It avoids unnecessary details, though the parameter list could be slightly more compact without losing clarity.
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 the tool's complexity (5 parameters, no required fields) and the existence of an output schema, the description covers filter options adequately. However, it omits details on return format, pagination, or ordering, leaving gaps for a comprehensive understanding.
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?
The schema description coverage is 0%, so the description compensates by explaining each parameter with examples and case-insensitivity notes. This adds meaningful context beyond the schema's basic titles and defaults, though examples could be more comprehensive.
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 purpose: 'Search Acme events by name, type, location, or attendee.' It specifies the verb (search), resource (Acme events), and the searchable attributes. This distinguishes it from sibling tools like events_detail or events_upcoming, which have different scopes.
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 does not explicitly state when to use this tool versus alternatives like events_attendee_schedule or events_detail. It implies usage for flexible searching, but lacks direct guidance on exclusions or specific contexts, leaving the agent to infer based on parameter names.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must disclose behavioral traits. It only states the tool returns top landing pages, without mentioning read-only nature, potential rate limits, or any side effects. This leaves the agent without important 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?
Extremely concise: one-line purpose followed by a parameter list with defaults. Every part is necessary and front-loaded with the key action. 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?
Given low complexity and presence of output schema, the description adequately covers purpose and parameters. It could mention the output metric (e.g., sessions) but the schema likely supplies that. Missing any ordering info, but still complete enough.
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?
Despite 0% schema description coverage, the description adds meaning by specifying date format (YYYY-MM-DD), default values, and example filters (e.g., 'United States', 'Organic Search'). This exceeds baseline 3 for low 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 verb (list top landing pages) and dimension (broken out by sessionSource), distinguishing it from siblings like ga4_top_pages which likely don't include the source breakdown.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 alternatives like ga4_channel_breakdown or ga4_top_pages. The description implies a use case but does not provide explicit when-to-use or when-not-to-use information.
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 provided, the description carries full burden. It states 'READ-ONLY' (a behavioral trait) and mentions the default limit. However, it does not disclose other behavioral aspects such as data freshness, pagination behavior, or error handling for invalid contact IDs.
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 extremely concise: one sentence of purpose plus a compact Args list. Every word adds value, and the most critical information is front-loaded. No unnecessary fluff.
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 presence of an output schema, the description does not need to explain return values. It covers the core function and parameter meanings. However, it could mention sorting order (e.g., chronological) or prerequisites (e.g., contact must exist) to fully guide the agent in a complex sibling 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?
Schema coverage is 0%, so the description must compensate. It describes 'contact_id' as 'HubSpot contact ID' and 'limit' as 'Max page visits to return (default: 50),' which adds meaning beyond the schema titles and types. However, the explanations are minimal and do not provide further constraints or format 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 'Get page visit history for a HubSpot contact (READ-ONLY).' It uses a specific verb ('Get') and resource ('page visit history'), distinguishing it from sibling tools like hubspot_contact_email_engagement or hubspot_contact_form_submissions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no explicit guidance on when to use this tool versus alternatives. The description only notes it is READ-ONLY but does not mention context, prerequisites, or exclusions. The agent must rely on the tool name alone to differentiate among many HubSpot contact tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so description must fully convey behavior. It mentions 'first/last analytics URL' but doesn't explain what that means or how matching works. Missing details on pagination, case sensitivity, or error conditions.
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?
Short and includes structured Args list. First sentence slightly redundant with name, but overall efficient. No wasted sentences.
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?
Output schema exists, so return values are covered. Parameters are documented. However, behavioral details (pagination, error handling) are missing, leaving gaps for complex use cases.
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?
With 0% schema coverage, description adds value by explaining each parameter: url_pattern as substring, start/end_date as ISO dates relative to createdate, limit with default. Example provided. However, 'first/last' semantics are unclear.
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 finds contacts based on URL pattern and retrieves their deals. This distinguishes it from sibling tools like hubspot_search_contacts or hubspot_get_contact_deals by adding the URL pattern matching specificity.
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 guidance on when to use this vs. alternatives. The purpose implies usage for URL-based contact discovery, but no exclusions or comparisons are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full responsibility. It does not disclose read-only nature, side effects, or output structure beyond mentioning 'performance with quality scores'. Given the lack of annotations, more behavioral detail is needed.
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 concise: a one-line purpose followed by a clear list of parameters. It is front-loaded with the main action. Minor redundancy in repeating defaults but overall efficient.
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 has only 3 optional parameters and an output schema (indicated by context), the description adequately covers purpose and parameter semantics. Return values are not explained, but the output schema likely handles this. Some what-if scenarios are missing but acceptable for this complexity.
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 0%, so the description compensates by explaining each parameter's purpose, format (YYYY-MM-DD), defaults (start_date: 28 days ago, end_date: today, limit: 30), and the role of 'limit' as a max. This adds significant meaning beyond the schema's titles and defaults.
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 'Get' and the resource 'Google Ads keyword performance with quality scores', making the tool's purpose specific and distinct from sibling tools like 'ads_campaigns' and 'ads_search_terms'.
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 retrieving keyword performance but lacks explicit guidance on when to use this tool versus alternatives (e.g., 'ads_campaigns' for campaigns). Defaults for date range and limit are provided but no 'when not to use' information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must cover behavioral traits. Only mentions 'US traffic' but lacks details on data freshness, pagination, rate limits, or what defines 'top'. Minimal transparency beyond basic function.
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?
Extremely concise: two-line summary plus two parameter lines. Front-loaded with essential info; every sentence adds value without 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?
Explains returned metrics (clicks, impressions, CTR, position) and parameter usage. Output schema exists, so return format details aren't needed. However, lacks context on timezone, data source, or definition of 'top' queries.
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 coverage is 0%, but description adds format (YYYY-MM-DD) and actual defaults (28 days ago, today) that are missing from schema. Provides clear, actionable parameter guidance beyond schema fields.
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 it retrieves 'top Bing search queries' with specific metrics (clicks, impressions, CTR, position) and scope (US traffic). Distinguishes from siblings like 'bing_keywords' by specifying 'top' and geographic scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool vs alternatives. Does not mention prerequisites, limitations, or appropriate contexts. The description only states what it does, not when to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must disclose behavioral traits. It fails to mention that the tool is read-only, what happens if the person is not found, or any limitations (e.g., maximum events). The description only lists parameter formats.
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 tightly written: one sentence for purpose followed by concise parameter descriptions. Every sentence adds value, and it is structured for quick scanning.
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 the tool has an output schema (not shown), return values are presumably covered. However, the description lacks behavioral details (e.g., read-only, pagination, authentication) and does not address edge cases. It provides adequate parameter info but lacks completeness in usage context.
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 0%, meaning the description must compensate. It provides meaningful guidance: person parameter with example names, date parameters with YYYY-MM-DD format hints, and default values for year and start_date. This adds significant value beyond the schema titles.
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 'Show all events a specific person is attending,' which is a specific verb-resource pair. It distinguishes from sibling event tools like events_search (general search) and events_upcoming (upcoming events) by focusing on a specific person's schedule.
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 provides parameter details and defaults but does not explicitly state when to use this tool versus other event tools. It implies usage for per-person queries but lacks alternatives or when-not conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It tells the action is read-only implicitly but does not disclose any behavioral traits like side effects, authentication requirements, or rate limits. 'Full details' is vague without referencing the output 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?
Concise, well-structured with Args section and inline formatting. Every sentence adds value. No fluff.
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 an output schema exists, the description doesn't need to detail return values. It mentions partial match which is important context. However, it does not explain what 'full details' encompasses or how it relates to sibling tools, but overall adequate for a detail look-up tool.
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 has 0% description coverage, but the description adds significant meaning: 'Full or partial event name to look up (case-insensitive)' for event_name, and 'Calendar year — "2025" or "2026" (default: "2026")' for year, including allowed values and default.
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?
Clear verb+resource: 'Get full details for a specific event by name.' Distinguishes from siblings like events_search (list) and events_upcoming (upcoming events) by specifying 'full details' for a single event.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives like events_search or events_upcoming. It states 'by name' but does not specify prerequisites or when to choose this over list-type tools.
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 must carry the behavioral burden. It discloses that direct traffic is excluded, which is a key behavioral trait. However, it does not mention authentication requirements, rate limits, data freshness, or any side effects. The behavior is minimally transparent but lacks depth.
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 exceptionally concise: one line for purpose followed by a clean bullet list of parameters. Every sentence serves a purpose, and the structure front-loads the answer. No fluff or redundancy.
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 the presence of an output schema and a moderate number of parameters (4 optional), the description is minimal but covers the basics. It does not explain what sessionSource means or how the exclusion of direct traffic is calculated. For a data retrieval tool, this is adequate but not thorough, considering the many siblings.
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?
With 0% schema description coverage, the description adds significant value by explaining all four parameters: date format (YYYY-MM-DD), default values (28 days ago for start_date, today for end_date, 30 for limit), and the purpose of country and limit. This compensates well for the empty schema, though it could clarify that country defaults to no filter.
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 that the tool returns 'Top referrers (sessionSource) excluding direct.' This is a specific verb-resource combination that distinguishes it from sibling tools like ga4_channel_breakdown or ga4_top_pages. The phrase 'excluding direct' adds precision.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when to use this tool versus alternatives. Among many GA4 sibling tools (e.g., ga4_channel_breakdown, ga4_top_pages), there is no mention of context, prerequisites, or when not to use it. The user must infer usage from the name and summary.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully cover behavior. It mentions default date ranges and a row limit, but it does not disclose that the tool is read-only, nor does it describe any side effects, authentication requirements, or rate limits. The output format is not described, though an output schema exists.
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 a single paragraph with an Args section that lists parameters clearly. It is front-loaded with the purpose and then details. A bit more structure (e.g., bullet points) could improve readability, but it remains concise without extraneous information.
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 the tool has 7 parameters (1 required) and an output schema, the description covers parameter semantics well but lacks guidance on when to use it among siblings and does not explain the output structure. The absence of annotations increases the burden, which is partially met.
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 0%, yet the description explains each parameter's meaning, format, and defaults (e.g., metrics: 'sessions,totalUsers,keyEvents', start_date: 'default 28 days ago'). This adds essential value beyond the schema, which only provides titles and defaults.
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 states 'Run a custom GA4 report with any metrics and dimensions', clearly identifying the verb (run), resource (GA4 report), and scope (custom, any metrics/dimensions). This distinguishes it from sibling GA4 tools that are more specific, like ga4_funnel_report or ga4_channel_breakdown.
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 explains parameters and defaults but does not explicitly state when to use this tool versus alternatives. There is no guidance on when not to use it or which sibling tool to prefer for specific report types. The flexibility is implied but not contrasted with other GA4 tools.
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 must convey behavioral traits. It explains that page_url uses GSC 'contains' if no protocol is provided, and gives default values for dates and row_limit. However, it does not state whether the tool is read-only, if it requires specific permissions, or any rate limits. The behavior is partially transparent but leaves gaps.
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 concise, consisting of a single-sentence summary followed by a bulleted list of parameters with their details. It is well-structured and front-loaded with the core purpose. Every sentence contributes information, though the format could be slightly more compact.
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 that an output schema exists, the description does not need to explain return values. It covers the tool's purpose, all parameters with behavioral details (e.g., partial URL matching), and default values. For a tool with 5 parameters and an output schema, this provides sufficient completeness.
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?
The schema has 0% description coverage for properties, meaning the input schema provides no explanatory text. The tool description compensates well by listing each parameter with its meaning and defaults (e.g., country: 3-letter code, empty for global; start_date: YYYY-MM-DD, default 31 days ago). This adds significant value 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's purpose: to find which queries drive impressions/clicks to a specific page. This is a specific verb ('find queries') and resource ('specific page'), and it naturally distinguishes from sibling tools like gsc_query_to_pages (reverse mapping) and gsc_search_analytics (broader analytics).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide guidance on when to use this tool versus alternatives. It does not mention when not to use it or suggest other tools for different scenarios (e.g., when to use gsc_query_to_pages instead). The context signals list many sibling tools, but the description itself lacks any explicit usage guidelines.
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 defaults and parameter formats but does not mention authentication, rate limits, data freshness, or side effects. The output schema exists but is not referenced.
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 extremely concise with a one-sentence summary followed by a structured parameter list. Every sentence is informative 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?
The tool has 5 parameters and an output schema. The description covers parameters and defaults but lacks usage guidance and behavioral context. Given the tool's simplicity, it is largely complete.
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 0%, but the description fully explains each parameter: query as exact string, date formats with defaults, country with example, and row_limit with default. This adds significant meaning beyond the schema titles.
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 the tool finds pages ranking for a given query in GSC. However, it does not differentiate this tool from sibling tools like gsc_page_query_matrix, which may serve a similar purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives such as gsc_search_analytics or gsc_page_query_matrix. The use case is implied but not explicitly stated.
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 bears full burden. Mentions GSC data lag (end_date default 3 days ago), but omits other behavioral traits like rate limits, authentication needs, or output pagination.
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 a single paragraph with clear bullet-like args. Front-loaded with purpose, every sentence adds value, no fluff.
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 output schema exists, description doesn't need to explain returns. Covers parameters and data lag well. Could add more context about sibling tool specialization, but overall adequate.
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 0%, but description fully explains all 5 parameters: dimensions format, date formats, row_limit, country codes. Adds significant meaning beyond schema titles and defaults.
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 'Get Google Search Console search analytics data', which is a specific verb+resource. It distinguishes from siblings by implying it's the general data retrieval tool, though it doesn't explicitly differentiate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. Provides default values and data lag context but no comparison with sibling tools like gsc_totals or gsc_quick_snapshot.
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?
Explicitly marks the tool as READ-ONLY, a key behavioral trait, but with no other behavioral details (e.g., rate limits, required permissions) despite no annotations to fall back on.
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?
A single, concise sentence that places the key verb and resource at the start, with no wasted words. Ideal for quick scanning.
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 tool is simple (one required parameter) and has an output schema (not shown but assumed), so the description adequately covers purpose and key entities, though some may wish for more context on output structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter contact_id has no description in the schema (0% coverage), and the description adds no extra meaning beyond stating what entities are returned, failing to explain ID format or constraints.
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 it gets companies and deals associated with a HubSpot contact, distinguishing it from sibling tools like hubspot_get_contact or hubspot_get_company.
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?
Indicates read-only nature, which is a usage guideline, but does not explicitly state when to use this tool versus alternatives or provide any exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations, so description must disclose behavior. Only states what it does, not side effects, idempotency, or data freshness. Lacks important 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?
One-line purpose followed by clean Args block. Every sentence is valuable, no redundancy.
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?
Covers purpose and parameters adequately, and output schema exists. However, lacks usage guidelines and behavioral context, leaving gaps.
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 coverage is 0%, but description explains each parameter with examples and purpose (year, quarter, event_type). Adds significant meaning 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?
Clearly states 'Get Acme events budget summary — total spend, breakdown by type and quarter.' Uses specific verb and resource, distinct from sibling events 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?
Provides parameter examples but no explicit guidance on when to use vs alternatives. Implied usage but no exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description bears full burden. Only states it 'lists' events, implying read-only, but does not disclose if it is non-destructive, what fields are returned, or any limitations like pagination. Lacks 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?
Extremely concise: one sentence for purpose, then bullet-style argument descriptions. No fluff, front-loaded with main action. Every word 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 output schema exists (but not visible), description does not need return values. However, for a list tool, it omits common context like ordering, maximum results, or whether it supports pagination. Adequate for basic use but not fully complete.
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 has 0% description coverage, but description fully compensates by explaining each parameter's format (YYYY-MM-DD) and defaults (today, 30 days from today) for start/end dates, and allowed values ('2025' or '2026') for year. Adds meaningful usage information 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?
Description clearly states 'List upcoming Acme events in a date range' with a specific verb and resource. It distinguishes from sibling tools like events_search (which likely searches by criteria) and events_detail (which gets details of one event).
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?
Provides defaults for date range (today to 30 days), implying typical use case. However, no explicit guidance on when not to use or alternatives among sibling events tools (e.g., events_search, events_attendee_schedule).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It mentions date range and country filter but does not disclose read-only nature, data freshness, aggregation, or limitations. The behavioral context is minimal beyond the stated parameters.
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 extremely concise: one sentence for purpose followed by a clear bullet-style Args block. No redundant words, front-loaded with the core function.
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 and the presence of an output schema, the description covers purpose and parameter details well. It does not describe the output structure, but the output schema fills that gap. Slightly more context on what data is returned (e.g., metrics) would improve completeness.
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?
Because schema description coverage is 0%, the description compensates effectively. It explains each parameter's format (YYYY-MM-DD), defaults (e.g., '28 days ago' for start_date), and offers an example for country. This adds significant value beyond the bare 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 verb 'Get', the resource 'GA4 traffic breakdown by channel', and enumerates example channels (Organic Search, Paid Search, Direct). This distinguishes it from sibling tools like ga4_traffic_by_country or ga4_traffic_by_device.
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 channel-level traffic breakdown but does not provide explicit when-to-use or alternatives. It lacks guidance on when not to use (e.g., for country or device breakdowns) compared to sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It does not disclose behavioral traits such as read-only nature, authentication needs, rate limits, or side effects. Only describes parameters and action, lacking transparency on tool behavior beyond the obvious.
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?
Structured as a clear docstring with a one-line purpose followed by parameter list. Efficient and front-loaded, though the parameter descriptions could be slightly more concise. Every sentence provides necessary 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?
All 7 parameters are explained, including required ones. Purpose is clear. Output schema exists (not shown), so return details are not required. However, no mention of data boundaries or specific behavior beyond parameter descriptions. Still fairly complete for the tool's complexity.
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 0%, so description provides all parameter semantics. It specifies date format (YYYY-MM-DD), defaults (query, 50), country format with examples (usa, gbr), and purpose. This adds significant value beyond the bare 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?
Description clearly states 'Compare two date periods in Google Search Console side-by-side', specifying verb, resource, and platform. This distinguishes it from sibling compare_periods tools for other platforms (ga4, bing).
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. Implied usage from name and description, but no references to alternatives or contra-indications. Lacks clear differentiation from sibling tools like gsc_search_analytics or gsc_movers_and_losers.
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 explicitly marks the tool as READ-ONLY, which is a key behavioral trait. However, no other behavioral details are provided (e.g., error handling, rate limits, auth requirements). Without annotations, the description carries the burden but provides minimal additional transparency beyond read-only.
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?
Extremely concise with one sentence for purpose and a clear args list. Every line adds value with no redundancy. Front-loads the core functionality.
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 simple read-only nature and the presence of an output schema, the description covers the essentials. It could mention that the result is a list of contacts, but the output schema likely defines the return structure.
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 0%, so the description compensates well. It explains company_id as 'HubSpot company ID' and limit as 'Max contacts to return (default: 5)', adding meaning beyond the schema's titles and default value.
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 the tool gets contacts associated with a HubSpot company, with a specific verb and resource. It distinguishes from siblings like hubspot_get_company (gets company info) and hubspot_search_contacts (searches contacts).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives such as hubspot_search_contacts or hubspot_get_contact. The description lacks context on prerequisites or conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It mentions 'approximate' but lacks details on data freshness, limitations, or any destructive actions.
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 a clear first sentence defining the tool and a structured bullet list for parameters. Every sentence adds value without repetition.
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 output schema exists, returning values are covered. The description covers purpose, parameters, and approximation. Minor gaps: no mention of error handling or rate limits, but adequate for a non-destructive reporting tool.
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?
With 0% schema coverage, the description explains all 5 parameters, including format (comma-separated steps), defaults (start_date 28 days ago), and filter semantics, adding substantial 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 counts users who fired each event in order, returning per-step counts and conversion rates. This distinguishes it from sibling GA4 tools like ga4_channel_breakdown or ga4_traffic_by_country.
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 funnel analysis but does not explicitly state when to use this tool versus other GA4 tools. No guidance on prerequisites or alternatives 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 provided, so the description carries full burden. It implies a read-only operation but does not explicitly state safety, permissions, rate limits, or data freshness. It is adequate but minimal.
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: a one-line purpose followed by a clear parameter list. Every sentence 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?
With an output schema present, description need not explain return values. It covers basic usage and parameters but lacks discussion of limitations or edge cases, which is acceptable given the tool's simplicity.
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 0%, and the description compensates well by explaining each parameter with format, default values, and examples (e.g., 'Start date YYYY-MM-DD'). This adds significant 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 it retrieves top landing pages by sessions from GA4, with a specific verb and resource. It distinguishes from siblings like ga4_landing_pages_by_source which adds a source filter.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description lists parameters but provides no guidance on when to use this tool versus alternatives such as ga4_landing_pages_by_source or ga4_channel_breakdown. No explicit when-not-to-use conditions are given.
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 must convey behavioral traits. It correctly declares 'READ-ONLY' and hints at a limit per activity type, but does not disclose behavior on invalid deal IDs, pagination strategy, data freshness, or authorization requirements. This is adequate but incomplete.
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 lines: a single purpose statement followed by two parameter definitions. It is front-loaded with the key action and resource, with no wasted words. Every sentence contributes 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 the output schema exists (not shown) and there are only two parameters, the description covers the necessary context: what the tool does and its arguments. Minor missing details like ordering of results (chronological?) do not detract significantly, but the description assumes agent knowledge of HubSpot deal activity types.
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?
With 0% schema description coverage, the description fully compensates by explaining both parameters: 'deal_id: HubSpot deal ID' and 'limit: Max items per activity type (default: 25)'. This adds meaning beyond the schema titles, which are generic ('Deal Id', 'Limit'), making parameter intent immediately clear.
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 'Notes, meetings, and calls associated with a HubSpot deal' with a 'READ-ONLY' qualifier, specifying the verb (retrieve) and resource (activity timeline for a deal). The name and description make it distinct from sibling tools like hubspot_get_deal or hubspot_get_deal_associations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when to use this tool versus alternatives, such as hubspot_get_deal for deal properties or hubspot_get_deal_associations for linked objects. There is no mention of context, exclusions, or prerequisites, leaving the agent to infer usage from the name alone.
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 explicitly labels the tool as 'READ-ONLY', which is a key behavioral trait. No annotations are provided, so the description carries the full burden; it does not mention rate limits, authorization, or error handling, but for a simple get operation, the read-only disclosure is sufficient.
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 extremely concise, with two sentences and a simple list. Every part is necessary and functional; there is no wasted text.
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 the tool's simplicity, an output schema exists (not shown), but the description does not mention error cases (e.g., missing company ID) or default property list behavior. It is adequate but could be more complete for a production environment.
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?
The description adds a brief 'Args:' section that repeats the parameter names but adds that 'properties' are 'Comma-separated properties to return', which is not in the schema format. However, with 0% schema description coverage, the description provides only minimal additional 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 states 'Get a HubSpot company by ID (READ-ONLY)', which clearly identifies the verb (Get), resource (HubSpot company), and scope (by ID). This distinguishes it from sibling tools like hubspot_search_companies or hubspot_get_contact.
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 when you have a HubSpot company ID, but it does not explicitly state when to use this tool versus alternatives like search_companies or get_contact. No exclusions or alternatives are mentioned, though context from sibling tool names provides some inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only states it gets keywords (read operation), but lacks details on rate limits, data freshness, or any side effects. This is insufficient for full transparency.
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 extremely concise: a one-sentence purpose, a brief use-case note, and a clear argument list. Every sentence is purposeful 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 5 parameters and no annotations, the description covers the purpose and parameters well. It could be more complete by describing the output format or any constraints, but the presence of an output schema partly alleviates this.
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 0%, but the description explains each parameter (keyword, start_date, end_date, country, language) with format and defaults, adding significant value beyond the schema's property names and types.
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 related keywords from Bing, with a specific verb 'Get' and resource 'keywords'. It distinguishes from sibling tools like 'bing_keywords' and 'bing_top_queries' by focusing on related keyword expansion.
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 mentions 'useful for content gap analysis and discovering adjacent topics', providing clear use cases. However, it does not explicitly state when not to use or mention alternatives, which would improve guidance.
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 reveals the tool creates a doc, writes content, and returns a URL. It does not mention ownership implications, rate limits, or any destructive behavior, but for a creation tool the behavioral profile is adequately outlined.
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 with no wasted words. It covers purpose, parameters, and return value efficiently. 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 schema descriptions and no annotations, the description is fairly complete for a creation tool. It explains the action, key parameters, and return. Could mention permissions or limitations, but overall sufficient.
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 0%, so the description must compensate. It explains 'title' is the document title and 'blocks' is a JSON array of content blocks referencing docs_add_tab format. This adds meaning, though the exact format of blocks is not fully specified.
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 creates a new Google Doc and writes formatted content into its default tab. It also references the sibling tool docs_add_tab for the blocks format, distinguishing its role as a creation 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?
The description implies creation vs. adding to an existing doc, but does not explicitly state when to use this tool over alternatives like docs_add_tab or other creation methods. No when-not or exclusion criteria are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It does not disclose behavioral traits such as read-only nature, potential rate limits, performance implications of combining calls, or whether it aggregates data differently. Only describes what it does, not how it behaves.
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 compact paragraphs and an Args section. First paragraph succinctly states purpose and replaced tools. Second paragraph gives usage guidance. No unnecessary language; every sentence contributes 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 the tool has 2 optional parameters, 0% schema coverage, and an output schema, the description covers the combined nature and parameter details. Could add context on performance benefits or limitations of the composite call, but overall adequate for a straightforward snapshot 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?
The description includes an Args block explaining start_date (default 28 days ago, format YYYY-MM-DD) and end_date (default today, format YYYY-MM-DD). This adds meaning beyond the schema, which only has type and default. Provides format and usage context.
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 it combines GA4 site engagement, channel breakdown, and top 10 pages into one call. Distinguishes from sibling tools like ga4_site_engagement, ga4_channel_breakdown, and ga4_top_pages by positioning as a composite alternative.
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 recommends use as 'starting point for any 'how is our website traffic doing?' question.' Mentions it replaces separate calls, implying when to use over alternatives. However, lacks explicit exclusions or when not to use it.
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 burden. It explains that the tool 'splits' GSC totals, indicating an analysis operation. However, it does not disclose whether it modifies data, authentication needs, rate limits, or the nature of the output. The description adds some context but lacks depth for a tool with no annotations.
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: one sentence summarizing the purpose followed by a clean parameter list. No unnecessary words or repetition. It earns its place with every sentence.
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 that an output schema exists (so return values are documented elsewhere) and parameters are well explained, the description is fairly complete. A minor gap is that 'brand_terms' could be clearer about whether it accepts patterns or exact terms, but overall it is sufficient.
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 0%, so the description must add meaning. It does so by listing each parameter with format hints (e.g., 'YYYY-MM-DD' for dates), defaults, and an explanation for brand_terms ('Comma-separated brand regex terms'). This adds significant value beyond the bare 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 purpose: 'Split GSC totals into branded vs unbranded query buckets.' It uses a specific verb (split) and resource (GSC totals), making the tool's function immediately clear. The purpose distinguishes it from siblings like gsc_totals which aggregates without splitting.
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 when a branded vs unbranded breakdown is needed but lacks explicit guidance on when not to use it or alternatives. For instance, it could mention that for raw totals, use gsc_totals, or for other segmentations, use other tools. The description is adequate but not fully instructive.
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. The description discloses the bucketing logic and parameter defaults, but does not mention whether the tool is read-only, rate limits, or data freshness. It assumes the agent understands GSC context but lacks explicit behavioral caveats.
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 extremely concise: one sentence for purpose followed by a clean list of arguments with defaults. No unnecessary words, 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 that an output schema exists (context flag true), the description does not need to detail return values. It covers input parameters thoroughly. Minor omission: no mention of what the output looks like (e.g., counts per bucket), but the output schema likely fills this gap.
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?
The input schema has no parameter descriptions (0% coverage), but the description fully documents each parameter with format (YYYY-MM-DD) and defaults, and clarifies the country code format and meaning of empty. This compensates well for the schema gap.
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: 'Bucket indexed pages by average position' with specific ranges (1-3/4-10/11-20/21+). This distinguishes it from siblings like gsc_search_analytics or gsc_totals, which serve different analytical purposes.
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 explains parameters and defaults but provides no guidance on when to use this tool versus alternatives (e.g., gsc_search_analytics for query-level data). No explicit usage context or selection criteria is given.
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 flags the tool as 'READ-ONLY' and explains pagination via the 'after' cursor parameter. However, since no annotations are provided, the description carries the full burden, and it does not disclose rate limits, authentication needs, 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 extremely concise, using a bullet-like list for parameters under 'Args:' with no wasted words. The main purpose is front-loaded in the first line. Every sentence is necessary.
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 output schema exists, return values do not need explanation. The description covers input parameters and pagination well, but it could explicitly state that the tool returns a list of contacts matching the filters and specified properties. It is mostly complete.
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?
With 0% schema description coverage, the description adds significant meaning: it explains filters as 'JSON string of HubSpot filter groups array', properties as comma-separated, dates as ISO filters, and pagination via 'after'. This compensates well, though the exact filter format could be more detailed.
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 HubSpot contacts with filters (READ-ONLY)', specifying the verb 'Search' and resource 'HubSpot contacts'. It distinguishes itself from sibling tools that search other entities (e.g., companies, deals).
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 searching contacts with filters but provides no explicit guidance on when to use this tool versus alternatives (e.g., hubspot_get_contact for a single contact). No exclusions or when-not-to-use are mentioned.
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 adds value by noting that each entry includes decoded issue labels, which goes beyond a generic 'get list' phrasing. However, with no annotations provided, it does not disclose any potential behavioral traits like rate limits, data freshness, or authorization requirements. For a simple read tool, this is adequate.
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 consists of two efficient sentences: the first states the core purpose, and the second provides concrete examples of returned data. No unnecessary words or repetition.
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 the presence of an output schema (not shown but indicated), the description appropriately focuses on the tool's primary function and output structure. With no parameters and no annotations, the description fully covers the necessary context for a simple list retrieval 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, so the description naturally requires no parameter explanations. The schema coverage is 100% (trivially). The description does not need to add parameter semantics, and it does not hinder usability.
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 list of URLs with crawl issues from Bing, specifying the nature of the data. This distinguishes it from sibling tools like bing_crawl_stats, which likely provides aggregate statistics rather than individual issue details.
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 technical SEO fixes, but lacks explicit guidance on when to use this tool versus alternatives, such as bing_crawl_stats for high-level overviews. No exclusions or prerequisites are mentioned.
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 provides some behavioral info (returns time-series data, includes error counts) but does not disclose other aspects like permissions, side effects, or data freshness.
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, front-loaded with purpose, and every word adds value. 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?
Given zero parameters and an output schema (not shown), the description adequately explains the return value: a time-series of crawl metrics. It feels complete for this 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 exist, so the baseline is 4. The description adds no parameter info, but none is needed.
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 weekly crawl statistics from Bing for a site, listing specific metrics (pages crawled, index count, error counts). This distinguishes it from siblings like bing_crawl_issues or other Bing 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?
No explicit guidance on when to use this tool versus alternatives. The description implies it's for general crawl health monitoring but doesn't compare with related tools like bing_crawl_issues.
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 discloses idempotency, upsert behavior, lead row replacement, and non-fatal warnings for reconciliation issues. It does not cover auth or rate limits but adequately conveys core 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 front-loaded with purpose and efficiently explains key behaviors in ~10 sentences. The args section is detailed but necessary for clarity. No redundancy.
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 the tool's complexity (2 params, output schema exists), the description covers the input structure, idempotent behavior, and result (warnings output). It is complete enough for an agent to use correctly.
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 0%, but the description adds extensive meaning: it details the required structure of week_summary_json (with required key week_ending and list of optional keys) and leads_json (array with per-lead fields). This fully compensates for the lack of schema descriptions.
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 the tool persists a week's demo report to Supabase with idempotent upsert behavior. It uses a specific verb ('persist') and resource (one week's classified demo report). However, it does not explicitly differentiate from sibling tools like demo_report_datapack or demo_report_month_rollup.
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 saving a week's data but provides no guidance on when to use this tool versus alternatives or when not to use it. Context is clear but lacks exclusions or alternative suggestions.
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 fallback to empty rows if the prerequisite is not met and mentions default dates. However, it does not describe whether the operation is read-only, any authentication requirements, or rate limits. The presence of an output schema partially mitigates the lack of output description.
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 extremely concise (≈60 words) and well-structured: a single sentence summary followed by a bulleted Args list. Every sentence adds value, with no redundant or unnecessary 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?
Given the output schema exists (per context signals), the description does not need to explain return values. It covers the prerequisite, fallback, and parameter details. It could be slightly improved by clarifying the timeline ordering (e.g., chronological), but overall it is sufficiently complete for a tool with a dependent output schema.
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?
With 0% schema description coverage, the description fully compensates by listing each parameter (client_id, start_date, end_date, limit) with clear explanations: 'GA4 clientId value to filter on', date formats (YYYY-MM-DD) with explicit defaults (28 days ago, today, 100). This adds substantial meaning beyond the bare 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 creates a 'best-effort event timeline for a single user.' The verb 'timeline' and the resource 'events for a single user' are specific. It also distinguishes itself from other GA4 tools by focusing on individual user-level tracking with a required clientId, making its purpose distinct.
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 provides context about the prerequisite (user-scoped clientId custom dimension) and fallback behavior, but it does not explicitly state when to use this tool versus similar GA4 tools like ga4_report or ga4_event_breakdown. No alternatives or when-not scenarios are mentioned.
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?
Since no annotations are provided, the description must disclose behavioral traits. It correctly identifies the tool as READ-ONLY and explains automatic stage filtering. However, it lacks details on pagination, rate limits, or required permissions.
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 front-loaded with the core purpose and ordering. It efficiently conveys usage and parameter info without redundancy, though the warning paragraph could be slightly tighter.
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 the key aspects: purpose, ordering, usage guidelines, parameter meanings. The presence of an output schema reduces the need to describe return values. It could explicitly state sorting direction, but it's implied.
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?
With 0% schema coverage, the description compensates well by explaining both parameters with types, defaults, and usage notes. The only gap is not specifying allowed values for properties beyond the default.
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 'most recently CLOSED-WON deals' with explicit ordering by close date. It distinguishes from sibling tools like hubspot_search_deals by specifying the filtered subset and automatic stage resolution.
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?
Provides explicit use cases ('recent/last/latest closed-won deals') and warns against misusing lifecyclestage. It explains the automation of filtering but does not explicitly contrast with similar deal search tools, leaving some 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 provided, but the description explains the limit behavior (totals reflect only rows returned) and that the output includes total and per-source breakdown. This adds valuable behavioral context beyond the basic function.
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 (about 5 lines) with a clear front-loaded purpose, followed by an organized Args section. No unnecessary words or 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 the output schema exists, the description explains return values and the limit behavior. It covers the key aspects for an aggregation tool. Could mention country filter behavior (exact match?), but overall complete.
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?
With 0% schema coverage, the description compensates by adding an Args section explaining each parameter's meaning, format (date), and defaults. This adds significant value beyond the schema types.
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 aggregates GA4 traffic from LLM platforms, listing specific platforms (Perplexity, ChatGPT, etc.). This distinguishes it from sibling GA4 tools that handle other traffic breakdowns.
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 LLM referral data but does not explicitly state when to use this tool over alternatives. No guidance on when not to use or references to similar sibling tools.
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 must carry the burden. It describes the output (totals, top10 queries, top10 pages) and default date ranges, implying a read-only snapshot. However, it does not explicitly state safety (e.g., no side effects) or discuss authentication or rate limits. The behavioral transparency is adequate but not comprehensive.
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 highly concise with no wasted words. It is structured into three logical paragraphs: purpose, usage, and parameters. The most important information (what it does and when to use it) is front-loaded, and 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 that an output schema exists (as indicated by context signals), the description adequately covers the tool's behavior: returning totals and top 10s for queries and pages. The description does not need to detail return values. For a snapshot tool, it is sufficiently complete for its intended 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?
The schema has 0% description coverage, but the description provides clear parameter explanations in the Args section: start_date and end_date with format and defaults, and country with an example. This adds significant value beyond the bare schema, compensating for the lack of schema 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 provides 'GSC totals + top 10 queries + top 10 pages in one call,' specifying that it replaces three separate calls, and positions it as the starting point for organic search queries. This distinguishes it from sibling tools like gsc_totals and gsc_search_analytics.
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 as the starting point for any 'how is organic search doing?' question,' indicating when to use it. It also mentions it avoids calling multiple tools separately. However, it does not provide explicit when-not-to-use scenarios or alternative tools beyond stating it replaces them.
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 full burden. It discloses that the tool 'probes' the ID, implying a safe read operation, but does not explicitly state whether it is read-only or if there are any side effects. It lacks details about permissions, rate limits, or any observable effects.
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 extremely concise: two sentences for purpose and usage, then a clear one-line parameter description. Every sentence serves a purpose, and the most critical information (what the tool does) is front-loaded.
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 has an output schema (not shown but indicated by 'Has output schema: true'), the description need not detail return values. However, it could mention what the response includes (e.g., object type string). Overall, it is fairly complete for a simple resolver tool with clear input and purpose.
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?
The schema has 0% description coverage, so the description must compensate. It adds meaning by explaining that 'unknown_id' is 'The HubSpot numeric ID to probe', clarifying it is numeric despite being a string in the schema, and linking it to the use case. This is helpful but could specify format constraints.
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 identifies the type of HubSpot object (deal, company, contact) that an ID belongs to, using specific verb 'identify' and distinct resource 'HubSpot object type'. This distinguishes it from sibling tools like hubspot_search_* or hubspot_get_* which retrieve or search existing 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?
The description explicitly states 'Use this when a lookup returns 404 and you're unsure whether the ID is a deal ID, company ID, or contact ID.' This provides clear context for when to use the tool. No exclusions or alternatives are mentioned, but the guidance is sufficient for decision-making.
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 must carry full burden. It explains parameters and defaults but does not disclose any behavioral traits like read-only nature, rate limits, or data freshness. The description is neutral but lacks depth.
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 and well-structured: a single-sentence summary followed by a bulleted list of arguments with clear explanations. Every sentence adds value, and it is front-loaded with the core 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 complexity (6 parameters, no annotations, many siblings), the description covers key aspects: date range, filters, defaults, and pagination. Output schema exists, so return values are not needed. Minor omission: nature of owner ID format, but overall adequate.
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 0%, so the description compensates well by adding defaults (start_date, end_date, limit), example values for outcome, and explanation of after for pagination. This goes beyond the schema's titles and defaults.
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 purpose: 'Search HubSpot meetings within a date range, optionally by owner/outcome.' It identifies the specific resource (meetings) and allows filtering, distinguishing it from sibling search tools for companies, contacts, deals, etc.
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 implies usage for searching meetings with optional filters and pagination. It provides defaults and examples, but does not explicitly state when not to use it or contrast with alternatives. Still, it gives sufficient context for correct invocation.
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 the full burden. It discloses that the tool scans up to a limit of deals, groups by a property, and filters by date range and pipeline. While it doesn't explicitly state read-only/isn't destructive, the aggregation nature strongly implies it.
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 concise with a clear purpose statement followed by a bullet-like list of parameter explanations. Every sentence provides value, and the structure is easy to parse.
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 that an output schema exists and there are 5 parameters with no schema descriptions, the description covers the core behavior and all parameters. Minor gaps exist (e.g., not mentioning valid group_by property values), but overall it is complete enough for an agent to use the tool correctly.
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 0%, so the description must compensate. It provides defaults and brief but useful descriptions for each of the 5 parameters (e.g., 'ISO date >= createdate' for start_date, 'Max deals to scan' for limit), adding 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?
Description clearly states the tool aggregates deals by a property over a date range, providing count and amount sum. This distinguishes it from sibling tools like hubspot_search_deals or hubspot_get_deal.
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 when aggregation and grouping is needed, but it does not explicitly state when to use this tool versus alternatives or provide 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; description explains the data is impressions-ranked and from Bing's topical index, but lacks details on rate limits, data freshness, or error states.
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?
Brief, front-loaded purpose, followed by clear bullet-pointed parameters. No extraneous text.
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?
Covers parameter usage and data source adequately; output schema exists so return format is handled. Could add example usage or edge cases, but sufficient for a keyword tool.
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 0%, but the description fully documents all 5 parameters with defaults and formats (e.g., YYYY-MM-DD for dates), adding essential meaning.
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 states it gets keywords Bing topically associates with example.com, impressions-ranked. Distinguishes itself from query stats, making purpose clear and distinct.
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?
Provides use case (authority and content gaps) and contrasts with query stats, but does not explicitly compare to sibling bing tools like bing_related_keywords or bing_top_queries.
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 must carry full behavioral transparency burden. It states it 'Fetches the URL linked in the event name cell' and returns details, but it does not disclose whether it follows redirects, handles timeouts, or requires authentication. This is adequate but not comprehensive.
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 three sentences: purpose, usage context, and parameter details. No redundancy, well-structured, and front-loaded with the most important 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, usage guidelines, and parameter semantics sufficiently. Given that an output schema likely defines return values, this is not a gap. However, it lacks mention of prerequisites (e.g., the event must exist in the sheet) or potential errors, making it slightly incomplete.
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?
With 0% schema description coverage, the description fully compensates by explaining event_name as 'Full or partial event name (case-insensitive)' and year as 'Calendar year — '2025' or '2026' (default: '2026')', adding crucial semantics missing from 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 'Fetch and read the linked event website for a specific event', specifying the verb ('Fetch and read') and resource ('linked event website'). It distinguishes itself from sibling tools like events_detail or events_search by focusing on external website content beyond the sheet.
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 details not in the sheet — venue, agenda, speakers, registration info, pricing', providing clear usage context. However, it does not mention when not to use it or explicitly name alternative tools, missing some depth.
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 clearly declares the tool as READ-ONLY, explains pagination with the 'after' cursor, and describes filter format, providing good insight into tool behavior beyond the 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 and well-structured: one-line purpose followed by a labeled Args block. Every sentence is informative, 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?
With 6 parameters and no annotations, the description covers all parameters, pagination, and read-only nature. Output schema exists to handle return values. Could briefly mention error handling, but overall adequate.
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 0%, but the description's 'Args' block provides clear semantics for all 6 parameters: filters (JSON string), properties (comma-separated), date filters (ISO), limit (default 50), and after (pagination cursor). This adds essential meaning beyond the schema's bare titles.
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 'HubSpot companies', and includes 'with filters (READ-ONLY)' to specify scope and safety. It is distinct from sibling tools like hubspot_search_contacts or hubspot_search_deals.
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 does not explicitly state when to use this tool over alternatives or provide exclusions. The 'READ-ONLY' hint implies safe usage, but no comparison to siblings is given.
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?
Without annotations, the description explains that it pulls queries, filters by min_words, sorts by impressions, and returns results. It is transparent about the filtering and sorting logic, though it does not detail rate limits or error states.
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 concise, front-loading the purpose and then listing parameters. A few words could be trimmed, but overall it is efficient and well-structured.
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 the 5 parameters and no annotations, the description covers purpose, filtering, sorting, and parameter formats. The output schema exists, so return values are documented elsewhere. No gaps are evident.
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 0%, so the description adds value by specifying date formats (YYYY-MM-DD), country code format (3-letter), and default values. It compensates well for the missing schema 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 tool extracts long-tail, conversational GSC queries and positions them as a proxy for LLM inputs. It distinguishes from siblings by focusing on multi-word, natural-language queries rather than keyword searches.
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 implies use for GEO content strategy by linking queries to natural-language problem statements. It does not explicitly exclude other GSC tools or state when not to use, but the specific focus on long-tail queries provides clear 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?
No annotations provided, so the description carries full burden. It explains the write operation, required access, and that it returns tab_id and a link. It does not disclose potential failure modes or idempotency, but the block format details are extensive. Overall, it provides good transparency for a mutation tool.
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 lengthy but well-structured: a clear opening sentence, a prerequisite line, then parameter explanations with blocks detailed in a bullet-like list. It is front-loaded with the main action. While comprehensive, some redundancy in the blocks examples could be trimmed without loss.
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 the complexity (string parameter for JSON blocks) and no output schema needed (tool returns tab_id and link), the description covers all necessary aspects: purpose, parameters, required access, and block format. It is complete for an agent to invoke correctly.
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 coverage is 0%, so the description must explain all three parameters. It does so thoroughly: doc_id with URL pattern, tab_title with float, and blocks with a complete specification of the JSON array format, including all supported types, flags, and examples. This adds significant value 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 'Adds a new named tab to an existing Google Doc and writes formatted content.' It specifies the action (add), resource (existing Google Doc), and output (tab and formatted content). This distinguishes it from the sibling 'docs_create_doc' which creates a new document.
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 includes a prerequisite: 'The service account must have Editor access to the target document.' It implicitly differentiates from 'docs_create_doc' by focusing on an existing doc. However, it does not explicitly state when not to use this tool or provide alternatives beyond the sibling 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?
With no annotations provided, the description carries the full burden. It describes the tool as a read operation for retrieving metrics and lists the output fields (sessions, users, engagement rate, bounce rate). This is adequate, though it could mention data aggregation or any limitations.
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 extremely concise, with a single-sentence purpose followed by a bullet-list of arguments. Every piece of information is relevant and front-loaded. There is no wasted text.
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 (4 optional parameters, output schema exists), the description covers the main usage. It explains input parameters well and hints at the output metrics. However, it does not detail the output format or row structure, but the output schema likely fills that gap.
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 0%, so the description must compensate. It documents all four parameters: start_date and end_date with format and defaults, and country and channel with examples. This adds significant meaning beyond the schema titles, making the tool easy to use.
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 that the tool retrieves GA4 site engagement metrics, listing specific metrics (sessions, users, engagement rate, bounce rate). It uses the verb 'Get' and identifies the resource, distinguishing it from sibling GA4 tools like ga4_channel_breakdown or ga4_compare_periods.
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 implies usage for obtaining site engagement metrics and provides parameter details, but does not explicitly state when to use this tool over alternatives. It gives clear context and parameter defaults, which helps the agent select it when those metrics are needed.
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 must disclose all behavioral traits. It states what it returns (GSC totals, top queries, etc.) but does not mention side effects, authentication needs, rate limits, or any cautions. Adequate for a read-only overview but lacks explicit safety or behavior notes.
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?
Concise, front-loaded opener, followed by usage guidance and parameter details. Every sentence adds value; 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?
Output schema exists, so description doesn't need to detail return structure. It lists key data points (GSC totals, top queries, top pages, GA4 engagement, channel breakdown) sufficiently for an overview tool. No missing context for its intended purpose.
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?
Input schema has two parameters (start_date, end_date) with 0% schema description coverage. Description adds format and defaults: 'Start date YYYY-MM-DD (default: 28 days ago)' and 'End date YYYY-MM-DD (default: today)', providing 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?
Clearly states 'Full marketing overview: GSC organic + GA4 traffic in one call,' specifying the verb (provide overview) and resource (marketing performance combining GSC and GA4). Distinguishes from many sibling tools that focus on individual metrics.
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 as the first tool for any weekly or ad-hoc "give me an overview of marketing performance" question,' providing clear when-to-use context. Lists what it returns, implicitly guiding users to other tools for deeper analysis.
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 declares the tool is READ-ONLY and deterministic, describes the paginated sweep and enrichment process, and explicitly mentions that returned fields like 'complete' and 'warnings' make partial pulls explicit. It does not describe rate limits or auth, but the behavioral context is sufficiently disclosed.
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 a clear introductory sentence explaining the purpose and process, followed by bullet-point parameter descriptions. It is well-structured and front-loaded, with 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?
Given the tool's complexity (multiple data sources, enrichment, pagination), an output schema exists (context signal), so the description doesn't need to detail return values fully. However, it still summarizes the returned JSON structure. The three parameters are thoroughly explained, making the definition complete for correct invocation.
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 0%, requiring the description to fully explain parameters. It does so: week_ending is 'Anchor date YYYY-MM-DD; the target week is the most recent completed Mon–Sun on/before it (default: today)', weeks_back is 'Completed weeks back to target (default: 1 = last week)', max_contacts_per_deal is 'Cap on contacts enriched per deal (default: 3)'. This adds 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 is a 'Complete, deterministic data pack for the weekly inbound demo report (READ-ONLY)' and details exactly what it does: computing target week, running sweep, fetching deals, enriching them, and returning a JSON object. It distinguishes itself from siblings like demo_report_month_rollup and demo_report_save_week by being the comprehensive data pack.
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 says 'The LLM's only remaining job is classification judgment + narrative,' implying it should be used before classification. It also mentions it replaces the hand-orchestrated demo skill. However, it does not explicitly state when not to use it or provide alternatives, though the context of siblings gives some 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?
Since no annotations are provided, the description carries the full burden. It declares READ-ONLY and explains pagination, sorting, and filtering behavior, but does not mention rate limits or authentication.
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?
Concise and well-structured. Starts with a clear purpose sentence, then lists parameters with explanations. No redundant information.
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 the tool's complexity and the presence of an output schema, the description covers filtering, sorting, pagination, and property selection. It is complete for a search tool.
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?
With 0% schema description coverage, the description fully compensates by explaining each parameter, providing defaults, and giving an example for filters. This adds significant value 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?
Clearly states it searches HubSpot deals with filters, and the title 'hubspot_search_deals' aligns. Among siblings like hubspot_search_companies, it distinguishes by resource.
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?
Provides detailed parameter explanations and an example for filters, but lacks explicit guidance on when to use this tool vs. alternatives like hubspot_get_deal or hubspot_search_contacts.
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 full burden. It discloses idempotent upsert behavior and the effect of stopping re-surfacing. It doesn't detail requirements or rate limits, but for a simple record-keeping tool, this is sufficient.
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 a clear purpose statement and well-structured argument explanations. Every sentence adds value without unnecessary verbosity.
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?
The tool is simple, and the description covers purpose, idempotency, all parameters, and provides usage context. With an output schema existing, the description is complete for correct invocation.
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 coverage is 0%, but the description thoroughly explains all three parameters: post_id (required, with format example), comment_url (optional, for audit trail), and note (optional, with examples). This adds high value 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 records that a Reddit candidate was engaged to stop re-surfacing. It uses specific verbs and resource, and distinguishes from the sibling `reddit_engagement_candidates` by being the complementary action after a comment is posted.
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 'call it once a comment is actually posted' and provides example notes for skipped or posted actions, giving clear context. It does not explicitly list when not to use or compare directly with alternatives, but the usage is well implied.
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 carries full burden. It discloses the tool's behavior as a pure read with no side effects, mentions return behavior for empty months ('explicit note'), and specifies no external integrations. This provides comprehensive behavioral transparency.
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, front-loaded with the main action, and uses bullet points for the parameter. Every sentence adds value without redundancy, and the structure is clear and easy to parse.
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 (one parameter, existence of output schema), the description is nearly complete. It explains input format, behavior, and return values. Minor gap: no explicit mention of error handling for invalid month format, but the parameter description is sufficiently detailed.
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?
The Args section fully explains the 'month' parameter: format (YYYY-MM), example, and semantics (returns weeks with week_ending in that month, leads, summed totals, note if empty). Schema coverage is 0%, so the description compensates completely for the single 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?
The description clearly states 'Read all stored demo weeks for a month and return pre-aggregated totals,' which specifies the action (Read), resource (stored demo weeks), and outcome. It distinguishes itself from siblings like demo_report_datapack and demo_report_save_week by focusing on aggregation without external pulls.
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 by stating 'Pure Supabase read — no datapack pull, no HubSpot, no re-classification,' implying it is a read-only rollup. However, it lacks explicit guidance on when to use this tool versus alternatives or when not to use it.
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 full burden. It discloses data sources (reddit_hits, reddit_classifications), ranking logic (bucket priority and recency), output split (posts vs comments), and listed fields. It lacks explicit mention of read-only behavior or rate limits, but the description adequately conveys non-destructive intent.
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 well-structured with purpose, details, usage guidelines, and parameter definitions. It is front-loaded with the key purpose. Though slightly long, every sentence adds value, and the structure aids readability.
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 the tool has an output schema (context signal) and no annotations, the description is thorough: it explains data sources, ranking, output fields, and intended workflow. All parameters are described, and the usage guidance is complete for a candidate retrieval tool.
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 0%, yet the description includes a detailed 'Args' section explaining each parameter (lookback_hours, include_posts, include_comments, limit, exclude_engaged) with defaults and semantics. This adds meaning well beyond the bare 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 it returns 'recent, classified, non-noise Reddit candidates to comment on.' It specifies reading from pipeline tables (no live fetch) and distinguishes itself from sibling tools like reddit_mark_engaged by outlining the intended workflow.
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?
The 'Intended use' paragraph explicitly tells when to use the tool (draft comments) and what to do next (call reddit_mark_engaged after posting). It also advises to open permalink first to avoid repeating replies, providing clear context on alternatives and proper usage.
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?
No annotations are provided, so the description carries the full burden. It explicitly states READ-ONLY, deterministic behavior, failure handling with warnings, and details about the computation (Monday-Sunday target, GSC lag, pre-computed cross-references). This provides rich 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a front-loaded summary, but it is somewhat lengthy. While every sentence adds value, it could be slightly more concise without losing information.
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 the tool's complexity (aggregating multiple sources), the description covers what it does, how it handles failures, and what it computes. It also mentions outputs (pre-computed cross-references, warnings). No output schema is provided, but the description sufficiently explains the return value context.
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 coverage is 0%, meaning the input schema properties lack descriptions. The description fully compensates by explaining both parameters: week_ending (anchor date in YYYY-MM-DD format) and weeks_back (number of completed weeks), along with their defaults.
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 is a 'Complete, deterministic data pack for the weekly traffic report (READ-ONLY)'. It specifies the verb 'data pack' and the resource 'weekly traffic report'. This distinguishes it from sibling tools that are individual platform queries (e.g., ads_campaigns, gsc_search_analytics).
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 implies usage for aggregating data for a weekly traffic report, but it does not explicitly state when not to use or provide alternatives. However, the context of sibling tools makes it clear that this is an aggregate alternative to individual platform calls.
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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