Multilead Open API MCP Server

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v1.0.0
Disambiguation2/5
Many tools have overlapping purposes that could cause confusion. For example, there are multiple tools for retrieving leads (get_leads_from_campaign, get_leads_from_seat, list_leads, get_lead), multiple tools for managing tags (create_tag, assign_tag_to_lead, remove_tag_from_lead, get_tags_for_leads, get_tags_for_seat, get_tags_of_a_specific_seat), and multiple tools for webhooks (create_webhook, create_global_webhook, delete_webhook, delete_global_webhook, list_webhooks, list_global_webhooks). While descriptions help, the boundaries between these tools are often unclear, leading to potential misselection.
Naming Consistency4/5
Most tools follow a consistent verb_noun pattern (e.g., create_campaign_from_template, get_campaign_info, update_lead). There are minor deviations, such as 'change_a_password' (includes 'a'), 'get_user_information' (uses 'information' instead of 'info'), and 'list_all_seats_of_a_specific_user' (verbose with articles). However, the overall pattern is readable and predictable, with snake_case used consistently throughout.
Tool Count2/5
With 77 tools, the count is excessive for the apparent scope of a LinkedIn outreach and lead management platform. Many tools appear redundant or overly granular (e.g., separate tools for seat suspension and reactivation, multiple export tools with slight variations). This volume will overwhelm agents and increase the risk of misselection, indicating poor scoping and a need for consolidation.
Completeness5/5
The tool set provides comprehensive coverage for the domain of LinkedIn outreach, lead management, and team administration. It includes full CRUD operations for leads, campaigns, tags, webhooks, seats, teams, and users, along with advanced features like message syncing, blacklisting, statistics, and exports. There are no obvious gaps; agents can perform end-to-end workflows without dead ends.
Average 3.4/5 across 77 of 77 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is failing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

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

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

How is the quality score calculated?

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

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

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

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

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. While 'Add a new tag' implies a write operation, it doesn't specify whether this is idempotent, what happens if the tag is already assigned, what permissions are required, or any rate limits. The return value is mentioned but not described in detail.
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 clear purpose statement followed by Args and Returns sections. It's appropriately concise with no wasted words, though the parameter explanations could be more informative while maintaining brevity.
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?
For a 4-parameter write operation with no annotations, the description provides basic purpose and parameter listing but lacks important context about behavior, error conditions, and relationships with sibling tools. The existence of an output schema helps, but the description's 'Confirmation of tag assignment' is vague and doesn't leverage the schema's potential detail.
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 lists all 4 parameters with brief explanations, but the schema description coverage is 0%, so the schema provides no additional documentation. The parameter explanations are minimal ('The ID of the...') and don't clarify format, source, or validation rules, leaving significant gaps in understanding.
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 action ('Add a new tag') and target resource ('to a specific lead'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'remove_tag_from_lead' or 'create_tag', which would be needed for a perfect score.
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 like 'remove_tag_from_lead' or 'create_tag'. It also doesn't mention prerequisites such as whether the tag must already exist or if the user needs specific permissions.
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 of behavioral disclosure. It states the action is a cancellation but doesn't clarify if this is permanent, reversible, requires specific permissions, or has side effects (e.g., data deletion, billing implications). This leaves significant gaps 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 well-structured with clear sections (action, Args, Returns) and uses minimal sentences. However, the title 'Cancel Seat' is repeated in the first line, which is slightly redundant, and the 'Returns' section could be more informative given the output schema exists.
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?
For a mutation tool with 3 parameters, 0% schema coverage, and no annotations, the description provides basic purpose and parameter labels but lacks critical behavioral details (e.g., permanence, permissions). The presence of an output schema reduces the need to explain return values, but overall completeness is only adequate with clear gaps.
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 lists the three parameters with brief labels (e.g., 'User ID who owns the seat'), which adds basic meaning beyond the schema's type definitions. However, it doesn't explain format constraints, examples, or relationships between parameters (e.g., if user_id and account_id must correspond).
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 action ('cancel') and resource ('a specific seat within a specific team'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'suspend_or_unsuspend_seat' or 'reactivate_seat', which prevents a perfect score.
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 'suspend_or_unsuspend_seat' or 'reactivate_seat'. The description lacks context about prerequisites, such as whether the seat must be active or suspended before cancellation, or any conditions that must be met.
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 behavioral disclosure. It states this is an 'action' that 'disconnects', implying a mutation operation, but doesn't disclose whether this requires specific permissions, whether the disconnection is reversible, what happens to existing data, or any rate limits. The description is minimal beyond stating the basic operation.
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 clear sections (title, action description, Args, Returns) and uses minimal words. Every sentence serves a purpose, though the 'Returns' section could be more informative. The structure is front-loaded with the core action first.
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 this is a mutation tool with no annotations, 2 parameters, and an output schema exists (though not shown), the description provides the basic operation and parameter meanings. However, it lacks important context about behavioral implications, permissions needed, or what 'disconnection' entails. The existence of an output schema helps, but the description should do more for a destructive-seeming operation.
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 includes an 'Args' section that documents both parameters ('user_id' and 'account_id') with brief explanations. This adds meaningful context beyond the bare schema, though it doesn't provide format examples or constraints. With 2 parameters fully documented in the description, this meets the baseline for adequate parameter semantics.
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 action ('disconnects') and resource ('a specific LinkedIn account from the seat on the platform'), making the purpose understandable. It doesn't explicitly differentiate from its sibling 'connect_linkedin_account', but the verb 'disconnect' vs 'connect' provides implicit distinction, so it's not a perfect 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 explicit guidance on when to use this tool versus alternatives is provided. The description mentions it disconnects 'a specific LinkedIn account from the seat', but doesn't explain prerequisites, consequences, or when this operation is appropriate versus other seat management tools like 'cancel_seat' or 'suspend_or_unsuspend_seat'.
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 behavioral disclosure. It mentions the output format (CSV) and suggests either direct CSV data or a download URL, which is helpful. However, it doesn't address important behavioral aspects: whether this is a synchronous or asynchronous operation, potential rate limits, file size limitations, authentication requirements beyond the parameters, or what happens if no campaigns exist. For an export tool with zero annotation coverage, this leaves significant gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with clear sections: purpose statement, arguments, and returns. Each section is brief and focused. The formatting with headings makes it scannable. However, the 'Args' section could be more informative, and some redundancy exists between the opening statement and the 'Returns' section about CSV format.
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 this is an export tool with 2 required parameters, 0% schema description coverage, no annotations, but with an output schema (implied by 'Has output schema: true'), the description is moderately complete. It covers the basic purpose and parameters, and the output schema should handle return value documentation. However, for a data export operation, it lacks important context about performance characteristics, data scope (all campaigns for which timeframe?), and practical usage considerations that would help an agent use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter documentation. The description includes an 'Args' section that lists the two parameters (user_id and account_id) but provides minimal semantic context - it only states they are IDs without explaining their purpose, format, or relationship. While it identifies the parameters, it doesn't add meaningful context about why both are needed or how they interact, leaving the agent to infer usage from parameter names alone.
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 exports all campaigns in CSV format, providing a specific verb ('Export') and resource ('all campaigns'). It distinguishes from sibling tools like 'export_leads_from_campaign' and 'export_statistics_csv' by focusing on campaigns rather than leads or statistics. However, it doesn't explicitly contrast with 'get_campaign_list' or 'get_all_campaigns_statistics', which might provide similar data in different formats.
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. It doesn't mention when this export is appropriate compared to 'get_campaign_list' (which might return structured data) or 'export_statistics_csv' (which focuses on statistics). There's also no information about prerequisites, limitations, or typical use cases for CSV export versus API consumption.
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 burden. It states the tool 'retrieves' data, implying a read-only operation, but doesn't disclose behavioral traits like authentication needs, rate limits, pagination, or what 'summary statistics' entails. For a tool with zero annotation coverage, this leaves significant gaps in understanding its 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 appropriately sized with a clear headline, brief elaboration, and structured 'Args' and 'Returns' sections. It's front-loaded with the main purpose. Minor verbosity in repeating 'summary statistics' could be trimmed, but overall efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, 0% schema coverage, but an output schema exists, the description is moderately complete. It covers purpose and parameters superficially but lacks depth on behavior, error handling, or output details. The output schema reduces need to explain return values, but more context on usage and constraints is needed for full adequacy.
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 lists parameters in an 'Args' section with brief explanations (e.g., 'User ID', 'Optional campaign state filter'), adding meaning beyond the bare schema. However, it doesn't fully clarify parameter formats, constraints, or the significance of 'campaign_state' default value 1, leaving some 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 verb ('Get', 'retrieves') and resource ('summary statistics for all campaigns'), specifying it provides 'platform-wide summary statistics (totals)'. It distinguishes from siblings like 'get_statistics' or 'get_step_statistics' by emphasizing 'all campaigns' scope. However, it doesn't explicitly contrast with these siblings in the description text.
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 'get_statistics' or 'get_campaign_list'. The description mentions retrieving 'platform-wide' data but doesn't specify prerequisites, exclusions, or comparative contexts with 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 full burden. While 'Retrieve' implies a read-only operation, the description doesn't disclose important behavioral traits like authentication requirements, rate limits, error conditions, or whether this requires specific permissions. For a tool with 3 required parameters and no annotation coverage, this leaves significant gaps in understanding how the tool behaves.
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 clear sections (purpose, Args, Returns) and uses minimal sentences. The first sentence states the core purpose, followed by organized parameter and return information. While efficient, the Returns section could be slightly more specific about what 'etc.' encompasses.
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 3 required parameters with 0% schema coverage and no annotations, the description provides basic parameter listing and return indication. The existence of an output schema means the description doesn't need to detail return values. However, for a read operation with multiple required IDs, more context about parameter relationships and authentication would improve completeness.
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 schema provides no parameter documentation. The description lists the three parameters (user_id, account_id, campaign_id) in the Args section, which adds basic semantic meaning. However, it doesn't explain what these IDs represent, their format, or relationships between them, leaving the agent with incomplete understanding despite the parameter listing.
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 verb ('Retrieve') and resource ('detailed information about a specific campaign'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_campaign_list' or 'get_all_campaigns_statistics', which likely retrieve campaign lists or aggregated statistics rather than detailed info for a specific campaign.
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. With many sibling tools like 'get_campaign_list' (likely for listing campaigns) and 'get_statistics' (likely for aggregated data), the agent receives no explicit direction about when this specific detailed retrieval is appropriate versus other campaign-related queries.
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 of behavioral disclosure. It states the tool retrieves/finds conversations, implying a read-only operation, but doesn't clarify permissions, rate limits, pagination, or what happens if no matches are found. For a tool with three required parameters and no annotation coverage, this leaves significant behavioral gaps, such as whether it's idempotent or has side effects.
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 clear sections (purpose, Args, Returns) and uses bullet-like formatting. It's appropriately sized at four sentences, with no redundant information. However, the 'Args' and 'Returns' sections could be more integrated into the flow, and some wording is slightly repetitive (e.g., 'identifiers' mentioned multiple times), preventing a perfect score.
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 (3 required parameters, no annotations, but an output schema exists), the description is minimally adequate. It covers the basic purpose and parameters but lacks behavioral context and usage guidelines. The presence of an output schema means the description doesn't need to explain return values, but it should still address how the tool behaves in different scenarios. This results in a baseline score with clear room for improvement.
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 includes an 'Args' section that lists parameters (user_id, account_id, identifiers) with brief examples (e.g., 'List of identifiers to search for (e.g., LinkedIn IDs)'). However, schema description coverage is 0%, so the schema provides no additional documentation. The description adds some semantic value by clarifying the purpose of 'identifiers,' but it doesn't fully compensate for the lack of schema details, such as format constraints or relationships between parameters.
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's purpose: 'Retrieve conversations using specific identifiers' and 'finds all conversations associated with the provided identifiers.' It specifies the resource (conversations) and action (retrieve/find) with examples of identifier types (LinkedIn profile IDs, email addresses). However, it doesn't explicitly differentiate from sibling tools like 'get_all_conversations' or 'get_other_conversations,' which prevents a perfect score.
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. It doesn't mention when this tool is appropriate compared to other conversation-retrieval tools in the sibling list (e.g., 'get_all_conversations,' 'get_campaign_conversations'), nor does it specify prerequisites or exclusions. The only implied context is needing identifiers to search, but this is basic parameter information rather than usage guidance.
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 states the tool retrieves messages but doesn't disclose behavioral traits such as permissions needed, rate limits, pagination, or error handling. It mentions the return value ('All messages for the specified lead'), but without details on format or structure. This is a significant gap for a tool with no annotation coverage.
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 appropriately sized and front-loaded: the first sentence states the purpose clearly, followed by elaboration and parameter details. It avoids unnecessary fluff, though the 'Args' and 'Returns' sections could be integrated more seamlessly. Overall, it's efficient with minimal 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's moderate complexity (3 parameters, no annotations, but an output schema exists), the description is somewhat complete. It covers purpose and parameters but lacks behavioral context and usage guidelines. The presence of an output schema means return values are documented elsewhere, reducing the burden, but gaps in transparency and guidelines keep it from being fully 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?
The description lists the parameters (user_id, account_id, lead_id) and their purpose, adding meaning beyond the input schema, which has 0% description coverage. However, it doesn't provide details like format, examples, or constraints for these IDs. With low schema coverage, the description compensates partially but not fully, warranting a baseline 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 the tool's purpose: 'Retrieve all messages for a specific lead' and elaborates with 'This gets all conversation messages associated with a particular lead.' It specifies the verb (retrieve/get) and resource (messages for a lead). However, it doesn't explicitly differentiate from sibling tools like 'get_messages_for_leads' or 'get_messages_from_a_specific_thread', which appear related, so it doesn't reach the highest score.
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. It doesn't mention sibling tools like 'get_messages_for_leads' or 'get_messages_from_a_specific_thread', nor does it specify prerequisites or exclusions. The usage is implied by the description but lacks explicit context for selection.
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 of behavioral disclosure. It states the tool retrieves data (implying a read operation) but doesn't specify whether it's paginated, rate-limited, requires authentication, or what happens with invalid inputs. The return format is mentioned ('List of leads'), but without details on structure or error handling, leaving significant gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the core purpose, followed by parameter and return details. It uses clear sections ('Args', 'Returns') and avoids redundancy. However, the 'Args' section could be more integrated into the flow rather than a separate block, and some sentences are slightly verbose.
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 moderate complexity (3 parameters, read operation) and the presence of an output schema (implied by 'Has output schema: true'), the description is adequate but incomplete. It covers the purpose and parameters but lacks behavioral context like error cases or performance characteristics. The output schema likely details the return structure, so the description doesn't need to elaborate further on returns.
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 schema description coverage is 0%, but the description includes an 'Args' section that documents all three parameters (user_id, account_id, thread_id) with brief explanations. This compensates somewhat for the schema gap, though it doesn't provide format details, constraints, or examples. The baseline is 3 since the description adds meaningful context beyond the bare 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 action ('Retrieve leads') and resource ('who are part of a specific conversation thread'), making the purpose immediately understandable. It distinguishes this tool from other lead-related tools like 'get_leads_from_campaign' or 'get_lead' by specifying the thread-based filtering, though it doesn't explicitly contrast with all siblings.
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. It doesn't mention prerequisites, typical use cases, or compare it to similar tools like 'get_conversations_by_identifiers' or 'get_messages_from_a_specific_thread' that might overlap in functionality. The agent must infer usage from the name and description alone.
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 of behavioral disclosure. It states the tool retrieves messages, implying a read-only operation, but doesn't clarify authentication needs, rate limits, error conditions, or pagination behavior. While it mentions a default limit, it lacks details on what happens if lead_ids is null or how results are structured, leaving significant gaps in understanding the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear title-like statement, a brief elaboration, and a parameter-return breakdown. It's front-loaded with the core purpose and avoids unnecessary fluff. However, the 'Args' and 'Returns' sections could be more integrated into flowing text, and some sentences are slightly redundant (e.g., 'Retrieve messages for specific leads' and 'This gets conversation messages...'), but overall it's efficient.
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 moderate complexity (4 parameters, 2 required), no annotations, and an output schema present, the description is minimally adequate. It covers the basic purpose and parameters but lacks behavioral details (e.g., error handling, pagination) and doesn't leverage the output schema to explain return values. For a read operation with sibling tools, it should do more to guide usage and clarify semantics, but it meets a bare minimum.
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 lists all four parameters with brief explanations (e.g., 'Optional list of lead IDs to get messages for', 'Maximum number of results to return'), adding meaningful context beyond the bare schema. However, it doesn't specify formats (e.g., what user_id or account_id represent), constraints, or examples, leaving some ambiguity. This partial compensation justifies a baseline 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 the tool's purpose: 'Retrieve messages for specific leads' and elaborates with 'This gets conversation messages associated with specific lead IDs.' It specifies the verb (retrieve/get) and resource (messages for leads), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_lead_messages' or 'get_messages_from_a_specific_thread', which prevents a perfect score.
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. It doesn't mention prerequisites, exclusions, or compare it to sibling tools such as 'get_lead_messages' or 'get_all_conversations'. The agent must infer usage from the tool name and parameters alone, which is insufficient for optimal selection.
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 of behavioral disclosure. It states the tool 'retrieves' statistics, implying a read-only operation, but doesn't confirm if it's safe, requires specific permissions, has rate limits, or describes the return format beyond 'step-by-step statistics.' For a tool with zero annotation coverage, this leaves significant behavioral gaps, such as whether it's idempotent or how errors are handled.
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 clear purpose statement, elaboration, and separate sections for Args and Returns. It's appropriately sized at four sentences, with no redundant information. However, the 'Returns' section is somewhat vague ('step-by-step statistics'), and the structure could be more front-loaded by integrating parameter details more seamlessly, but overall 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.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (3 parameters, no annotations, but has an output schema), the description is minimally adequate. It covers the purpose and parameters but lacks behavioral context (e.g., safety, permissions) and detailed usage guidelines. The presence of an output schema reduces the need to explain return values, but without annotations, more disclosure on operation traits would improve completeness. It's functional but has clear gaps.
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 includes an 'Args' section that lists and briefly describes the three parameters (user_id, account_id, campaign_id), adding meaning beyond the input schema, which has 0% description coverage. However, it doesn't specify data formats (e.g., string vs. integer for campaign_id is only in schema), constraints, or examples. With low schema coverage, this compensates partially but not fully, meeting the baseline for some added value.
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's purpose: 'Get step statistics for a specific campaign' and elaborates with 'retrieves statistics for individual campaign steps within a specific campaign.' This specifies the verb ('get'/'retrieve'), resource ('step statistics'), and scope ('within a specific campaign'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_statistics' or 'get_all_campaigns_statistics,' which prevents a perfect score.
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. It mentions retrieving statistics for 'individual campaign steps' but doesn't clarify if this is for detailed analysis versus aggregate statistics from other tools, nor does it reference sibling tools like 'get_statistics' or 'get_all_campaigns_statistics' for comparison. Usage is implied by the purpose but lacks explicit when/when-not instructions 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 carries full burden for behavioral disclosure. It states this is a retrieval operation, implying read-only behavior, but doesn't mention any permissions required, rate limits, error conditions, or what happens if lead IDs are invalid. For a tool with no annotation coverage, this leaves significant behavioral 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 well-structured with clear sections for purpose, arguments, and returns. It's appropriately sized with no redundant information, though the 'Args' and 'Returns' labels add slight verbosity. Every sentence serves a purpose, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, 0% schema coverage, but an output schema exists, the description is moderately complete. It covers the basic purpose and parameters but lacks behavioral context and usage guidance. The output schema handles return values, so the description doesn't need to explain returns, but it should do more to compensate for missing annotations and schema documentation.
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 schema provides no parameter documentation. The description lists parameters in an 'Args' section with brief explanations, adding meaning beyond the bare schema. However, it doesn't explain parameter formats (e.g., ID structure), constraints, or relationships, leaving some semantic gaps despite covering all three parameters.
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 action ('Retrieve tags') and target resource ('for specific leads'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get_tags_for_seat' or 'get_tags_of_a_specific_seat' that also retrieve tags but for different entities, missing full sibling distinction.
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. With sibling tools like 'get_tags_for_seat' and 'get_tags_of_a_specific_seat' available, there's no indication of whether this tool is preferred for lead-based tag retrieval or if there are specific prerequisites or constraints for its 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 burden but offers minimal behavioral insight. It mentions the return format (list with roles and permissions) but doesn't cover authentication needs, rate limits, pagination, error conditions, or whether this is a read-only operation (though implied by 'retrieve').
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 clear sections (Args, Returns, Example) and front-loaded the core purpose. The example is helpful but could be more concise. No wasted sentences, though the formatting is slightly verbose.
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?
For a simple retrieval tool with 2 parameters and an output schema, the description provides basic coverage but lacks important context. With no annotations and 0% schema coverage, it should explain more about authentication, error handling, and parameter constraints to be fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description adds basic semantics for both parameters ('Your user ID' and 'The ID of the team'). However, it doesn't explain format requirements, validation rules, or why user_id is required when retrieving team members, leaving significant gaps.
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 verb 'retrieve' and resource 'all members from a specific team', making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_team_roles' or 'update_team_member', which prevents a perfect score.
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 'get_team_roles' or 'list_users_associated_with_a_specific_seat'. The description only states what it does, not when it's appropriate or what distinguishes it from similar 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 of behavioral disclosure. It states the action ('marks all messages in a specific conversation thread as read/seen') but lacks critical details: it doesn't specify if this requires specific permissions, whether it's idempotent, what happens if the thread doesn't exist, or any rate limits. For a mutation tool with zero annotation coverage, 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and appropriately sized: it starts with a clear purpose statement, elaborates in a second sentence, and includes separate sections for Args and Returns. However, the 'Returns' section ('Success confirmation') is vague and could be more informative, slightly reducing efficiency.
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 moderate complexity (a mutation with 3 parameters), no annotations, and an output schema present (which should cover return values), the description is minimally adequate. It explains the action and parameters but lacks behavioral context and usage guidelines. The output schema likely details the 'Success confirmation', so the description doesn't need to elaborate further on returns, keeping it from being incomplete.
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 lists the three parameters (user_id, account_id, thread) and briefly describes 'thread' as 'Thread ID to mark as seen', adding minimal semantics beyond the schema. With 0% schema description coverage, the description partially compensates by naming parameters but doesn't explain their relationships (e.g., how user_id and account_id interact) or formats. This meets the baseline for low coverage but doesn't fully address the gap.
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's purpose with a specific verb ('mark') and resource ('messages in a thread'), and it elaborates on what 'as seen' means ('read/seen'). However, it doesn't explicitly differentiate this tool from potential sibling tools like 'get_unread_conversations' or 'get_messages_from_a_specific_thread', which are related to message status but serve different purposes.
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. It doesn't mention prerequisites (e.g., whether the user must have access to the thread), exclusions, or related tools like 'get_unread_conversations' for checking status before marking. This leaves the agent without context for optimal tool selection.
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 of behavioral disclosure. It states the action is 'Remove' (implying a mutation) and mentions a return value ('Confirmation of tag removal'), but lacks critical details: whether this requires specific permissions, if the operation is reversible, what happens if the tag isn't on the lead, or any rate limits. For a mutation tool with zero annotation coverage, this is insufficient.
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 appropriately sized and front-loaded: the first sentence states the purpose clearly, followed by structured 'Args' and 'Returns' sections. There's no wasted text, though the formatting with bullet-like lists could be slightly more polished. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (4 parameters, mutation operation) and no annotations, the description is partially complete. It covers the basic purpose and parameters but lacks behavioral context (e.g., error cases, permissions). The presence of an output schema (implied by 'Has output schema: true') means the description doesn't need to detail return values, but other gaps remain.
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 schema provides no parameter descriptions. The description adds value by listing all four parameters with brief explanations (e.g., 'The ID of the tag to remove'), which clarifies their roles. However, it doesn't specify format constraints (e.g., UUID), dependencies between parameters, or example values, leaving gaps in understanding.
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 action ('Remove') and target ('a specific tag from a specific lead'), which is a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'assign_tag_to_lead' or 'update_lead', which could involve tag management. The purpose is clear but lacks sibling differentiation.
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. There's no mention of prerequisites (e.g., the tag must already be assigned), when not to use it, or how it differs from related tools like 'assign_tag_to_lead' or 'update_lead'. The agent must infer usage from the tool name alone.
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 states the action 'sends a reply' which implies a write operation, but doesn't mention authentication needs, rate limits, side effects, or what 'Sent email reply details' includes. For a mutation tool with zero annotation coverage, this leaves significant behavioral 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 appropriately sized with a clear purpose statement followed by parameter and return sections. However, the second sentence 'This sends a reply to an existing email conversation thread' is somewhat redundant with the first. Overall structure is good but could be more efficient.
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 7 parameters with 0% schema coverage and no annotations, the description provides basic parameter listing and states there's an output schema (which handles return values). However, for a mutation tool that sends emails, it lacks crucial context about permissions, error conditions, and behavioral details that would help the agent use it correctly.
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 schema provides no parameter documentation. The description lists all 7 parameters with brief labels, adding basic semantics beyond the schema. However, it doesn't explain parameter relationships, formats, or constraints (e.g., what thread ID format, whether lead_id must match thread). This partial compensation justifies a baseline 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 the verb 'send' and resource 'email reply to an existing thread', making the purpose evident. It distinguishes from sibling 'send_new_email' by specifying it's a reply to an existing thread, though it could be more explicit about this differentiation. The title is null, so the description carries the full burden.
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 like 'send_new_email' or other communication tools. It mentions it's for replying to an existing thread, but doesn't specify prerequisites, constraints, or when not to use it. The agent must infer usage from context alone.
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 of behavioral disclosure. It states the action ('initializes', 'sends') but lacks critical details: whether this requires admin permissions, if it's idempotent, rate limits, what happens if the email doesn't exist, or if it triggers side effects. For a security-sensitive tool, this is insufficient.
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 clear sections (title, action, args, returns) and uses minimal sentences. Every sentence adds value, though the title repetition ('Send Password Reset Email') is slightly redundant with the action statement.
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 moderate complexity (security-sensitive operation), no annotations, and an output schema (implied by 'Returns'), the description covers basics but lacks depth. It explains what the tool does and its parameter, but misses behavioral nuances and security implications, making it minimally viable but incomplete.
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 explicitly documents the single parameter ('email: Email address to receive the password reset link'), adding meaningful context beyond the bare schema. However, it doesn't specify format constraints (e.g., valid email patterns) or edge cases, keeping it at baseline adequacy.
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's purpose with specific verbs ('initializes', 'sends') and resource ('password reset email'). It distinguishes itself from siblings by focusing on password reset functionality, though it doesn't explicitly contrast with similar tools like 'change_a_password' or 'resend_email_confirmation_message'.
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. It doesn't mention prerequisites (e.g., user must exist), exclusions, or compare it to sibling tools like 'change_a_password' or 'resend_email_confirmation_message', leaving the agent without contextual usage 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 provided, so the description carries full burden. It mentions 'connects' implying a write/mutation operation, but does not disclose behavioral traits like authentication requirements, rate limits, side effects (e.g., if it overwrites existing connections), or error conditions. The return statement is vague ('status and details') without specifics.
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 structured with sections (Args, Returns) but includes redundant text ('This actions connects' has a typo). The parameter list is necessary given low schema coverage, but some explanations are minimal (e.g., 'Account/Seat ID'). It could be more front-loaded with critical context.
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 with 0% schema coverage and no annotations, the description partially compensates by listing parameters. An output schema exists, so return values need not be detailed. However, for a mutation tool with sensitive data (passwords, proxy setup), it lacks warnings, prerequisites, and error handling context, making it incomplete for safe use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It lists all 8 parameters with brief explanations (e.g., 'User ID', 'LinkedIn account email'), adding meaning beyond the bare schema. However, it lacks details on formats (e.g., what 'country_code' values are valid) or dependencies between parameters.
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 action ('connects a specific LinkedIn account to a specific seat') with specific resources (LinkedIn account, seat). It distinguishes from the sibling 'disconnect_linkedin_account' by being the opposite operation, though not explicitly mentioned. The purpose is specific and actionable.
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 prerequisites. The description does not mention when this should be used (e.g., initial setup vs. reconnection) or what happens if the account is already connected. It lacks context for decision-making.
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 burden. It discloses that the tool creates an account and sends emails (implying mutation and side effects), but lacks critical behavioral details: required permissions, whether it's idempotent, error conditions (e.g., if user already has warm-up), rate limits, or what 'Success confirmation' entails. For a mutation tool with zero annotation coverage, 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 well-structured with a clear title line, a brief explanation, and separate Args/Returns sections. It's appropriately sized for a single-parameter tool, with no redundant sentences. The front-loaded purpose statement is effective, though the formatting could be slightly more streamlined.
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 1 parameter with 0% schema coverage and an output schema (implied by 'Has output schema: true'), the description is minimally adequate. It covers the parameter meaning and return intent, but as a mutation tool with no annotations, it should ideally include more behavioral context (e.g., permissions, idempotency) to fully guide the agent.
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 compensate. It explicitly documents the single parameter 'user_id' with its purpose ('User ID to activate warm-up for'), adding essential meaning beyond the bare schema. However, it doesn't specify format constraints (e.g., UUID, integer) or examples, leaving some 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 action ('activate', 'creates an account', 'sends credentials') and the resource ('InboxFlare warm-up for a user'). It specifies the exact outcome (account creation and credential emailing), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'create_seat' or 'register_new_user', which might involve user account creation in different contexts.
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. It doesn't mention prerequisites (e.g., user must exist), exclusions (e.g., don't use if warm-up is already active), or related tools like 'create_seat' or 'register_new_user' from the sibling list. The agent must infer usage solely from the purpose statement.
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 behavioral disclosure. It states this is a creation operation but doesn't mention required permissions, whether this affects existing webhooks, rate limits, or what happens on failure. The return statement is minimal and doesn't describe format 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 well-structured with clear sections (purpose, Args, Returns) and uses bullet points for webhook configuration. It's appropriately sized at 6 sentences, though the 'Returns' line is somewhat redundant given the output schema exists.
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?
For a creation tool with 3 parameters, 0% schema coverage, no annotations, but with an output schema, the description provides adequate parameter semantics and clear purpose. However, it lacks important behavioral context like permissions, side effects, and error handling that would be needed for safe invocation.
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's Args section provides meaningful context for all 3 parameters: user_id as 'User ID', account_id as 'Account ID', and webhooks as a list with url and events details. This compensates well for the schema's lack of descriptions, though it doesn't specify event type formats or URL validation.
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 creates a global webhook that listens for events across all campaigns and resources in the account. It specifies the verb 'create' and resource 'global webhook' with scope information, though it doesn't explicitly differentiate from the sibling 'create_webhook' tool.
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 like 'create_webhook' or 'list_global_webhooks'. It mentions the scope ('across all campaigns and resources') but gives no explicit usage context, 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?
With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a creation operation (implying mutation) and mentions the return format, but lacks critical details like required permissions, whether tag names must be unique, error conditions, or side effects. The description adds minimal behavioral context 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?
The description is well-structured with clear sections for Args and Returns, and every sentence serves a purpose. It's appropriately sized for a 3-parameter creation tool, though the 'seat (account)' parenthetical could be slightly more elegant.
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 mutation nature (creation), 0% schema description coverage, and presence of an output schema (which handles return values), the description does an adequate but minimal job. It covers the basic action and parameters but lacks important context about permissions, constraints, and error handling that would be valuable for a mutation 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 explicitly lists all three parameters with brief explanations, adding meaningful context beyond the 0% schema description coverage. It clarifies that 'account_id' refers to a 'seat' and that 'tag_name' is the name to create. However, it doesn't provide format requirements, constraints, or examples for these parameters.
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 action ('Create a new tag') and the target ('for a specific seat (account)'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'assign_tag_to_lead' or 'get_tags_for_seat', which handle related but different tag operations.
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 like 'assign_tag_to_lead' (which assigns existing tags) or 'get_tags_for_seat' (which retrieves tags). There's no mention of prerequisites, constraints, or typical use cases beyond the basic action.
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 of behavioral disclosure. It states the tool retrieves conversations with filtering and pagination, but lacks critical details: whether this is a read-only operation, potential rate limits, authentication requirements, or what happens with large datasets. For a tool with 6 parameters and no annotation coverage, this is a significant gap in 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 clear purpose statement followed by parameter documentation and return information. It's appropriately sized for a 6-parameter tool. The only inefficiency is repeating 'all' in both the title and description, but overall it's front-loaded and each section earns its place without unnecessary verbosity.
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 (6 parameters, no annotations, but with output schema), the description is minimally adequate. It documents parameters well and mentions the return type, but lacks behavioral context about safety, performance, or error handling. The output schema existence means it doesn't need to detail return values, but for a data retrieval tool with filtering, more operational guidance would be helpful.
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' section that documents all 6 parameters with clear explanations, default values, and optional status. Since schema description coverage is 0%, this documentation fully compensates by providing semantic meaning beyond the bare schema. The only minor gap is not specifying format constraints (e.g., tag_ids as 'comma-separated list'), but overall it adds substantial value.
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's purpose: 'Retrieve all conversations from all channels' with optional filtering by name and tags. It specifies the verb ('retrieve'), resource ('conversations'), and scope ('from all channels'), making the intent unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_campaign_conversations' or 'get_other_conversations', which would require 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?
The description provides no guidance on when to use this tool versus alternatives. It mentions filtering capabilities but doesn't compare with sibling tools like 'get_campaign_conversations' (for campaign-specific conversations) or 'get_conversations_by_identifiers' (for targeted retrieval). There's no mention of prerequisites, exclusions, or typical use cases, leaving the agent to infer usage from context alone.
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 of behavioral disclosure. It states the tool retrieves data, implying a read-only operation, but doesn't specify permissions required, rate limits, error conditions, or whether the seat must be valid. This leaves significant gaps for a tool that likely accesses user data.
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 title, brief action statement, and clear sections for Args and Returns. It's front-loaded and avoids unnecessary details, though the title repetition in the first line is slightly redundant.
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 moderate complexity (2 required parameters, no annotations, but with an output schema), the description is adequate but incomplete. It explains the parameters and return value, but lacks behavioral details like error handling or usage context. The output schema likely covers the return structure, so the description doesn't need to elaborate further on 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?
The description adds meaningful context beyond the input schema, which has 0% description coverage. It clarifies that 'user_id' and 'account_id' correspond to 'User ID' and 'Account/Seat ID', respectively, and explains their role in identifying the specific seat. 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 the action ('retrieves all tags') and resource ('related to a specific seat'), making the purpose explicit. However, it doesn't differentiate from sibling tools like 'get_tags_for_seat' or 'get_tags_for_leads', which appear to serve similar purposes, preventing a perfect score.
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 lacks context about prerequisites, such as whether the seat must exist or be active, and doesn't mention sibling tools like 'get_tags_for_seat' or 'get_tags_for_leads' for comparison.
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 of behavioral disclosure. It states the tool retrieves data (implying read-only) and returns a list with permissions, but doesn't mention authentication requirements, rate limits, error conditions, or whether the operation is idempotent. For a tool with zero annotation coverage, this leaves significant behavioral 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 well-structured with clear sections (purpose, Args, Returns, Example) and front-loaded the core functionality. It's appropriately sized for a simple retrieval tool, though the example could be more concise (e.g., omitting 'Your user ID' explanation). Every sentence earns its place, but minor verbosity in the example prevents a perfect score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (2 required parameters, no nested objects) and the presence of an output schema (which handles return values), the description is reasonably complete. It covers purpose, parameters, and return overview, though it lacks behavioral context like error handling or permissions. The output schema reduces the need for detailed return documentation, making this adequate for the 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 description coverage is 0%, but the description compensates by documenting both parameters in the 'Args' section, explaining their purpose and marking them as required. It adds meaning beyond the bare schema (which only shows types), though it doesn't specify format constraints (e.g., ID format, user validation). Given the coverage gap, this provides adequate but not comprehensive parameter semantics.
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's purpose: 'Retrieve all roles for a specific team' - a specific verb ('Retrieve') and resource ('roles for a specific team'). It distinguishes from sibling tools like 'get_team_members' or 'create_team_role', but doesn't explicitly differentiate from them. The purpose is clear but lacks explicit sibling differentiation for a perfect score.
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. It doesn't mention prerequisites (e.g., team existence, user permissions), nor does it suggest when other tools like 'get_team_members' or 'create_team_role' might be more appropriate. The example shows usage but offers no contextual guidance.
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 states the action 'retrieves' and mentions the return includes 'profile, settings, and permissions', but lacks details on authentication needs, rate limits, error conditions, or whether it's a read-only operation. For a tool with zero annotation coverage, this is insufficient behavioral disclosure.
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 appropriately sized with two sentences: one stating the purpose and one detailing the return. It's front-loaded with the main action, though the title repetition 'Get User Information' is slightly redundant. Every sentence adds value without 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 an output schema (which covers return values), no parameters, and no annotations, the description is moderately complete. It explains the purpose and return scope, but for a tool with zero annotations, it should provide more behavioral context (e.g., read-only nature, auth implications) to be fully 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?
The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the lack of inputs. The description doesn't need to add parameter details, and it correctly implies no inputs are required by not mentioning any. Baseline is 4 for zero parameters.
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 verb 'retrieves' and the resource 'all information on the authorized user', specifying it's the user whose API key is being used. It distinguishes from siblings by focusing on the authorized user rather than other users or data types, though it doesn't explicitly contrast with specific sibling tools like 'get_linkedin_user_info'.
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. It doesn't mention prerequisites, timing, or contrast with similar tools like 'get_lead' or 'get_linkedin_user_info', leaving the agent to infer usage based on the purpose alone.
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 of behavioral disclosure. It mentions the tool imports keywords, implying a write operation, but doesn't specify permissions required, potential side effects (e.g., overwriting existing blacklist entries), rate limits, or error handling. The description adds minimal context beyond the basic action, leaving significant gaps in understanding how the tool behaves.
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 clear purpose statement followed by organized sections for Args and Returns. It avoids redundancy and is appropriately sized for a 5-parameter tool. However, the 'Returns' section is vague ('Success confirmation with import results'), which slightly reduces efficiency.
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 5 parameters with 0% schema coverage and no annotations, the description does a decent job by documenting all parameters and stating the purpose. However, it lacks details on behavioral aspects like permissions or side effects, and the output schema exists but isn't described, leaving the return value ambiguous. For a mutation tool with no annotations, this is minimally adequate but incomplete.
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' section that documents all 5 parameters with clear semantics, including options for 'keyword_type' and 'comparison_type'. Since schema description coverage is 0%, this section fully compensates by providing essential details not in the schema, such as enum values and parameter purposes, though it lacks examples or formatting specifics for the CSV file.
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's purpose: 'Import keywords to your seat's blacklist from a CSV file.' This specifies the verb (import), resource (keywords to blacklist), and mechanism (CSV file). However, it doesn't explicitly differentiate from its sibling 'import_keywords_to_global_blacklist_csv' beyond the 'seat's blacklist' vs 'global blacklist' distinction, which is implied but not directly contrasted.
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 like 'add_keywords_to_blacklist' or 'import_keywords_to_global_blacklist_csv'. It lacks context about prerequisites, such as whether the CSV file must be pre-uploaded or formatted in a specific way, and doesn't mention any exclusions or typical use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 of behavioral disclosure. It mentions the tool 'retrieves' data (implying read-only) and includes pagination details, but lacks critical information such as authentication requirements, rate limits, error conditions, or whether the operation is safe or has side effects. This is insufficient for a tool with potential access control implications.
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 clear title, action statement, and bullet points for args and returns. It's front-loaded with the core purpose and avoids unnecessary verbosity, though the formatting could be slightly more streamlined (e.g., integrating the title into the first sentence).
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 moderate complexity (2 parameters, no annotations, but has an output schema), the description covers the basic purpose and parameters adequately. However, it lacks context on permissions, error handling, and comparison to siblings, which are important for a whitelabel operation. The output schema existence reduces the need to detail return values, but behavioral gaps remain.
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 meaningful context for both parameters: it explains that 'limit' controls the maximum number of results (default: 30) and 'offset' sets the starting position (default: 0), which clarifies pagination behavior. Since schema description coverage is 0%, this compensates well by providing essential usage details beyond the bare 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 action ('retrieves the list of all your users') and specifies the context ('as a whitelabel'), making the purpose evident. However, it doesn't explicitly differentiate from sibling tools like 'get_user_information' or 'list_users_associated_with_a_specific_seat', which might offer similar user-related data but with different scopes or filters.
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. It doesn't mention prerequisites (e.g., whitelabel permissions), exclusions, or compare it to other user-listing tools in the sibling list, leaving the agent to infer usage context solely from the tool name and description.
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 of behavioral disclosure. It states this is a retrieval operation, implying it's read-only, but doesn't mention authentication requirements, rate limits, error handling, or whether it returns paginated results (despite having limit/offset parameters). The description lacks details on permissions or side effects.
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 brief purpose statement followed by Args and Returns sections. Each sentence earns its place by defining parameters and return value. It could be slightly more concise by integrating the purpose into the Args section, but overall it's efficient 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 4 parameters with 0% schema coverage and no annotations, the description does a fair job explaining parameters and return value. However, it lacks context on authentication, error cases, or how global webhooks differ from regular ones. With an output schema presumably present, the return description is adequate, but overall completeness is moderate due to missing behavioral details.
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 compensate. It documents all 4 parameters with clear explanations: user_id and account_id as identifiers, limit with default and purpose, offset with default and pagination role. This adds substantial meaning beyond the bare schema, though it doesn't specify format constraints (e.g., string patterns for IDs).
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's purpose with 'List global webhooks' and 'retrieves all global webhooks configured for the account', providing a specific verb (list/retrieve) and resource (global webhooks). It distinguishes from siblings like 'list_webhooks' by specifying 'global' scope, though it doesn't explicitly contrast them.
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 'list_webhooks' or 'get_webhook'. The description mentions retrieving 'all global webhooks' but doesn't clarify if this is for administrative purposes, auditing, or integration setup, leaving usage context implied at best.
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 but offers minimal behavioral insight. It implies a mutation ('reactivate') but doesn't disclose permissions required, whether changes are reversible, rate limits, or error conditions. The return statement mentions 'confirmation with updated seat status' but lacks detail on format or possible outcomes. For a mutation tool with zero annotation coverage, this is inadequate.
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 action, followed by structured Args and Returns sections. It avoids fluff and each sentence adds value, but the formatting with separate sections could be slightly more integrated for flow. Overall, it's efficient and well-organized.
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 3 parameters with 0% schema coverage, no annotations, and an output schema present, the description does a fair job. It explains parameters and hints at return values, but as a mutation tool, it lacks critical behavioral details (e.g., side effects, error handling). The output schema reduces need for return explanation, but overall completeness is moderate with room for improvement.
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 compensates well by explaining all three parameters: 'user_id' as 'User ID who owns the seat', 'account_id' as 'Account/Seat ID to reactivate', and 'proxy_country' as 'Optional proxy country code' with examples. This adds meaningful context beyond the bare schema, though it doesn't detail format constraints (e.g., ID patterns) or proxy country implications.
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 action ('reactivate'), resource ('inactive seat'), and scope ('within a specific team'). It distinguishes from siblings like 'cancel_seat' and 'suspend_or_unsuspend_seat' by focusing on reactivation of inactive seats. However, it doesn't explicitly contrast with 'create_seat' or other seat-related tools, keeping it from a perfect score.
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 like 'suspend_or_unsuspend_seat' or 'create_seat'. It mentions the tool is for 'inactive seats' but doesn't clarify prerequisites (e.g., seat must be inactive) or exclusions (e.g., not for active seats). This lack of contextual usage information is a significant gap.
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 burden. It states this is a transfer action but doesn't disclose critical behavioral traits: whether it's idempotent, requires specific permissions, has rate limits, validates credit availability, or handles errors. The mention of 'authenticated user' implies some auth need, but this is insufficient 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 well-structured with a clear title, brief purpose statement, and organized parameter/return sections. It's appropriately sized for a 3-parameter tool, though the 'Args' and 'Returns' headers are slightly redundant given the schema. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a mutation tool with 3 parameters, 0% schema coverage, no annotations, but an output schema exists, the description is moderately complete. It covers parameters and return purpose but lacks behavioral context (safety, side effects) and doesn't fully compensate for missing annotations. The output schema reduces need to explain 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?
Schema description coverage is 0%, so the description must compensate. It explicitly lists all three parameters with brief semantics: 'user_id: Source user ID (authenticated user)', 'destination_user_id: Destination user ID to receive credits', 'quantity: Number of credits to transfer'. This adds meaningful context beyond the bare schema types, though it doesn't specify formats or constraints.
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's purpose: 'transfers credits from the authenticated user to a specified destination user.' It specifies the verb ('transfers'), resource ('credits'), and direction (from authenticated user to destination). However, it doesn't differentiate from siblings, as no other credit-related tools exist in the sibling list.
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. It doesn't mention prerequisites (e.g., sufficient credits), exclusions, or related tools. The sibling list includes no obvious credit-related alternatives, but the description still lacks any 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states this is an update/edit operation but doesn't mention permissions required, whether changes are reversible, rate limits, or error conditions. The example shows a mutation, but no safety or operational context is given.
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 clear sections (Args, Returns, Example) and uses bullet-like formatting. While somewhat lengthy due to the example, every sentence adds value, and the information is front-loaded with the core purpose first.
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?
For a mutation tool with 5 parameters, 0% schema coverage, and no annotations, the description does a decent job explaining parameters and providing an example. However, it lacks behavioral context (permissions, side effects) and doesn't mention the output schema exists, though the 'Returns' section helps. It's adequate but has 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 provides detailed parameter explanations beyond the schema (which has 0% coverage). It clarifies required vs. optional parameters, explains 'account_roles' structure, and describes 'can_manage_team_global_webhooks'. However, it doesn't explain 'team_id' or 'user_id' beyond labeling them as required.
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 action ('Edit and update') and resource ('a team member from a specific team'), making the purpose understandable. However, it doesn't explicitly differentiate this tool from sibling tools like 'invite_team_member' or 'update_lead', which could help with tool selection.
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 'invite_team_member' or 'update_lead'. The description lacks context about prerequisites (e.g., needing existing team membership) or typical use cases, leaving the agent without clear usage 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?
With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a creation operation but doesn't mention permission requirements, rate limits, side effects, or what happens on duplicate emails. The 'Returns' section describes output format, but lacks details on error conditions or system behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with clear sections (Args, Returns) and uses bullet-like formatting. Every sentence adds value: the opening statement defines the tool's purpose, and the parameter/return sections provide essential information without 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?
For a creation tool with 8 parameters and no annotations, the description covers the basic purpose and parameters adequately. However, it lacks important context about authentication needs, error handling, and behavioral constraints. The presence of an output schema reduces the need to fully document return values, but more operational guidance would be beneficial.
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 for 8 parameters, the description compensates well by listing all parameters with brief explanations. It clarifies which parameter is required (email) and provides basic semantic context for each field, though it doesn't specify format constraints or validation rules.
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 action ('Create a new lead') and the resource ('in Multilead'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'update_lead' or 'add_leads_to_campaign', but the verb 'Create' is specific enough for basic distinction.
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 like 'update_lead' or 'add_leads_to_campaign'. It also doesn't mention prerequisites, dependencies, or typical use cases, leaving the agent without contextual usage instructions.
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 of behavioral disclosure. While 'Create a new team' implies a write operation, it doesn't mention permissions required, whether the user_id must be valid, what happens if a team with that name exists, rate limits, or error conditions. This is inadequate for a mutation tool with zero annotation coverage.
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 well-structured and efficiently organized: a clear purpose statement, followed by Args, Returns, and Example sections. Every sentence adds value, with no redundant information. The front-loaded purpose statement makes the tool's function immediately apparent.
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?
For a creation tool with 2 parameters, 0% schema coverage, no annotations, but with an output schema present, the description does an adequate job. It explains the parameters well and mentions the return value, but lacks behavioral context (permissions, constraints). The output schema reduces the need to detail return values, but more behavioral transparency 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?
The description adds meaningful context for both parameters: 'user_id' is explained as 'who will own the team' and 'name' as 'the name of the team to create.' With schema description coverage at 0%, this significantly compensates by providing semantic understanding beyond the bare schema types. The example further clarifies usage.
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 action ('Create a new team') and the resource ('team for a specific user'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'create_team_role' or 'list_teams_under_the_users_white_label', which would be needed for a perfect score.
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. There's no mention of prerequisites, constraints, or when other tools like 'create_team_role' or 'invite_team_member' might be more appropriate. The example shows usage but doesn't explain 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 are provided, so the description carries the full burden. It mentions retrieving conversations and includes pagination (limit/offset) and filtering (name), but lacks details on permissions, rate limits, error handling, or response format. For a tool with 6 parameters and no annotation coverage, this is insufficient behavioral disclosure.
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 brief purpose statement, elaboration, and a parameter/return section. It is front-loaded and efficient, though the 'Args' and 'Returns' sections are slightly verbose; every sentence earns its place by clarifying parameters and output.
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 6 parameters with 0% schema coverage and an output schema present, the description does a good job explaining parameters and stating the return value. However, it lacks behavioral context (e.g., auth needs, error cases) and does not fully compensate for the absence of annotations, keeping it from a score of 5.
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 compensate. It provides clear explanations for all 6 parameters: user_id, account_id, campaign_id, limit, offset, and name, including defaults and optionality. This adds significant meaning beyond the bare schema, though it could include more context (e.g., format of IDs).
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's purpose: 'Retrieve conversations from a specific campaign' and elaborates with 'This gets all conversations associated with a particular campaign.' It specifies the verb ('retrieve') and resource ('conversations'), but does not explicitly differentiate from sibling tools like 'get_all_conversations' or 'get_conversations_by_identifiers', which prevents a score of 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?
The description provides no guidance on when to use this tool versus alternatives. It does not mention sibling tools like 'get_all_conversations' or 'get_conversations_by_identifiers', nor does it specify prerequisites or exclusions. Usage is implied by the focus on campaigns, but explicit alternatives are missing.
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 of behavioral disclosure. It mentions a prerequisite ('if you previously started a conversation with them'), which adds useful context about when the tool works. However, it doesn't describe other behavioral traits such as rate limits, authentication needs, error conditions, or what happens if the conversation hasn't been started. For a tool with no annotation coverage, this leaves significant gaps in understanding its operational 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 well-structured and appropriately sized, with clear sections for the main purpose, arguments, and returns. It uses bullet-like formatting for 'Args' and 'Returns,' making it easy to scan. However, the 'Args' section could be more concise by integrating parameter explanations directly, and the 'Returns' section is somewhat vague ('including name, headline, company, etc.'), which slightly reduces efficiency.
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 that there is an output schema (which should document the return structure), the description doesn't need to detail return values extensively. However, with no annotations, 0% schema description coverage for inputs, and three required parameters, the description falls short in fully compensating for these gaps. It provides basic purpose and some usage context but lacks crucial details on parameter meanings and behavioral constraints, making it incomplete for reliable tool invocation.
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 schema description coverage is 0%, meaning none of the three parameters (user_id, account_id, linkedin_user_id) have descriptions in the input schema. The description lists these parameters in the 'Args' section but only provides their names without explaining what they represent, their formats, or how to obtain them. This adds minimal value beyond the schema, as it doesn't clarify the semantics or usage of these IDs, leaving them largely undocumented.
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's purpose: 'Retrieve LinkedIn profile information for a specific user.' It specifies the verb ('Retrieve') and resource ('LinkedIn profile information'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'get_user_information' or 'connect_linkedin_account,' which could cause confusion about when to use this specific LinkedIn-focused tool versus other user-related tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides some implied usage guidance: 'This returns profile information if you previously started a conversation with them.' This suggests a prerequisite (having an existing conversation) but doesn't explicitly state when to use this tool versus alternatives like 'get_user_information' or 'connect_linkedin_account.' It lacks clear exclusions or comparisons with sibling tools, leaving room for ambiguity in tool selection.
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 states this is a retrieval operation but doesn't disclose behavioral traits like whether it requires specific permissions, rate limits, pagination behavior, error conditions, or what happens when threads don't exist. The description is minimal beyond stating the basic operation.
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 appropriately sized with a clear purpose statement followed by parameter documentation and return information. It's front-loaded with the core functionality. The structure is logical, though the 'Args' and 'Returns' sections could be more integrated with the narrative flow.
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 there's an output schema (which handles return values), no annotations, and 4 parameters with 0% schema coverage, the description does provide parameter documentation and states the return purpose. However, for a tool with multiple required parameters and no annotation coverage, it should ideally include more about authentication needs, error handling, or example usage to be fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter documentation. The description includes an 'Args' section that documents all 4 parameters with brief explanations, adding meaningful semantics beyond the bare schema. However, it doesn't provide format details (e.g., what constitutes valid thread IDs) or examples, leaving some 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's purpose: 'Retrieve messages from specific conversation threads' with optional filtering by timestamp. It specifies the verb ('retrieve') and resource ('messages from specific conversation threads'), but doesn't explicitly differentiate from sibling tools like 'get_lead_messages' or 'get_messages_for_leads' which might retrieve messages from different contexts.
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 context through 'retrieve messages from one or more specific threads' and mentions optional filtering for recent updates. However, it doesn't provide explicit guidance on when to use this tool versus alternatives like 'get_all_conversations' or 'get_conversations_by_identifiers', nor does it mention any 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?
With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a retrieval operation but doesn't mention permission requirements, rate limits, pagination behavior, error conditions, or whether it's idempotent. For a tool with zero annotation coverage, this leaves significant behavioral 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 efficiently structured with a clear purpose statement followed by separate Args and Returns sections. Every sentence serves a purpose, though the parenthetical '(account)' in the first sentence is slightly redundant with the parameter description.
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 (though not shown), the description doesn't need to detail return values. It covers the purpose and parameters adequately for a simple retrieval tool. The main gap is the lack of differentiation from the nearly identical sibling tool 'get_tags_of_a_specific_seat'.
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 well by explaining both parameters in the Args section: 'user_id: The ID of the user' and 'account_id: The ID of the account (seat)'. This clarifies what each parameter represents, though it doesn't provide format examples or validation rules.
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 verb 'retrieve' and the resource 'all tags from a specific seat (account)', making the purpose unambiguous. However, it doesn't distinguish this tool from the sibling 'get_tags_of_a_specific_seat' which appears to serve an identical function, preventing a perfect score.
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 like 'get_tags_for_leads' or 'get_tags_of_a_specific_seat'. It mentions no prerequisites, exclusions, or specific contexts, leaving the agent to guess about appropriate usage 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions role-based access control, which adds useful context about permissions, but doesn't cover other critical behaviors like whether this is a read-only operation, potential rate limits, error conditions, or pagination. The description is insufficient for a tool that likely accesses sensitive user data.
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 clear sections (title, role-based access, Args, Returns) and uses bullet points efficiently. It's appropriately sized at 6 sentences, though the role-based section could be more concise. Every sentence adds value, with no redundant 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's moderate complexity (user-specific data retrieval), no annotations, and the presence of an output schema (which handles return values), the description is partially complete. It covers purpose, basic usage, and parameter semantics, but lacks behavioral details like safety, performance, or error handling. The output schema relieves the description from explaining return values, but other gaps remain.
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 schema has 0% description coverage for its single parameter 'search', but the description provides basic semantics: 'Optional search query to filter seats (e.g., "John Smith")'. This adds meaning beyond the bare schema, explaining it's a filter with an example, though it doesn't detail search syntax, fields searched, or case sensitivity. With only one parameter, the baseline is 4, but the limited detail reduces it to 3.
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's purpose: 'List All Seats of a Specific User' with the action 'Retrieves information about the seats'. It specifies the resource (seats) and scope (user-specific), though it doesn't explicitly differentiate from sibling tools like 'get_leads_from_seat' or 'list_users_associated_with_a_specific_seat'.
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 implied usage guidance through role-based access (team members, co-workers, platform admins), indicating when different users might use it. However, it doesn't explicitly state when to choose this tool over alternatives like 'get_tags_of_a_specific_seat' or 'list_all_users_as_a_whitelabel', nor does it mention 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?
With no annotations provided, the description carries full burden. It states the tool pauses 'all upcoming steps' but doesn't disclose whether this requires specific permissions, whether paused steps can be resumed, what happens to in-progress steps, or any rate limits. The mention of 'campaign workflow' adds some context but lacks operational details.
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 efficiently structured with a clear purpose statement, elaboration on scope, and separate Args/Returns sections. Every sentence earns its place, and information is front-loaded appropriately.
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 (returns confirmation), the description doesn't need to detail return values. However, for a mutation tool with no annotations and incomplete parameter guidance, the description should provide more behavioral context about what 'pause' entails operationally.
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 for the single parameter, the description compensates by explaining that 'lead_id' is 'The ID of the lead to pause'. This adds essential meaning beyond the bare schema. However, it doesn't specify format requirements or where to obtain this ID.
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 action ('pause') and target ('execution of campaign steps for a specific lead'), with the first sentence providing a specific verb+resource. However, it doesn't explicitly differentiate from sibling tools like 'resume_lead_execution' or 'return_lead_to_campaign' beyond the obvious action difference.
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 'resume_lead_execution' or 'update_lead_in_campaign'. The description only states what it does, not when it's appropriate or what prerequisites might exist.
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 of behavioral disclosure. While it states the tool sends a message, it doesn't describe what happens after sending (e.g., delivery confirmation, error handling), whether there are rate limits, authentication requirements beyond the listed parameters, or what constitutes a valid 'existing thread'. For a messaging tool with zero annotation coverage, 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly structured and concise: a clear purpose statement, followed by organized Args and Returns sections. Every sentence earns its place, with no redundant information. The front-loaded purpose statement immediately communicates the tool's function.
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 (7 required parameters, messaging operation) and the presence of an output schema (implied by 'Has output schema: true'), the description is moderately complete. The parameter documentation is thorough, but behavioral aspects are under-specified. The output schema existence means the description doesn't need to detail return values, but other operational 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?
With 0% schema description coverage for all 7 required parameters, the description provides excellent compensation by listing all parameters with brief explanations in the Args section. Each parameter gets a clear label and basic semantic meaning (e.g., 'Message content to send', 'LinkedIn user ID of the recipient'). This adds substantial value beyond the bare 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 action ('send a LinkedIn message') and target ('to an existing thread'), providing a specific verb+resource combination. It distinguishes this from sibling tools like 'send_new_email' or 'send_email_reply' by specifying the LinkedIn platform context. However, it doesn't explicitly differentiate from potential similar messaging tools that might exist in the sibling list.
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 mentions 'to an existing thread' which provides some context about when to use it (not for starting new conversations), but offers no guidance on when to choose this tool versus alternatives like 'send_email_reply' or 'send_new_email'. There are no explicit when-not-to-use instructions or prerequisite information about required account connections.
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 burden. It mentions 'Add' implying a write operation and 'Success confirmation' for returns, but lacks details on permissions, rate limits, idempotency, or error handling. For a mutation tool with zero annotation coverage, this is insufficient 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?
Well-structured with a brief introductory sentence followed by clear 'Args' and 'Returns' sections. Each sentence earns its place by explaining key aspects without fluff. Slightly verbose in listing all enum options, but overall efficient 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 5 parameters with 0% schema coverage and no annotations, the description does well on parameter semantics but lacks behavioral details like side effects or error cases. An output schema exists, so return values needn't be explained. It's adequate but misses mutation-specific 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 description coverage is 0%, so the description must compensate. It provides detailed semantics for all 5 parameters: 'user_id' and 'account_id' are identified, 'keywords' is explained with an example, and 'keyword_type' and 'comparison_type' list all enum options. 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Add' and resource 'keywords to your seat's blacklist', specifying the action and target. It distinguishes from sibling 'add_keywords_to_global_blacklist' by specifying 'seat's blacklist' rather than global, though not explicitly contrasting them. The purpose is specific but could be more explicit about differentiation.
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 'add_keywords_to_global_blacklist' or 'import_keywords_to_blacklist_csv'. The description implies usage for adding keywords via JSON, but lacks context on prerequisites, timing, or exclusions. It's a basic statement without operational guidance.
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 of behavioral disclosure. While it states this is a creation action and mentions the return value, it doesn't address critical behavioral aspects like required permissions, whether this is a mutating operation (implied but not explicit), potential side effects, error conditions, or rate limits. For a tool with 8 required parameters and no annotations, 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 well-structured with clear sections (action statement, Args, Returns) and uses bullet-like formatting for parameters. It's appropriately sized for an 8-parameter tool, though the initial 'Create Seat' line is redundant with the tool name. Every sentence adds value, but minor trimming could improve efficiency.
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 (8 required parameters, no annotations, but has output schema), the description is partially complete. It excels at parameter semantics but lacks behavioral context and usage guidelines. The output schema existence means the description doesn't need to detail return values, but for a creation tool with no annotations, more behavioral transparency would be beneficial.
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 providing clear semantic explanations for all 8 parameters. Each parameter is listed with a brief explanation that adds meaning beyond the bare schema (e.g., 'User ID who owns the seat', 'Start time in UTC (e.g., "08:00")', 'Timezone (e.g., "Europe/Belgrade", "America/New_York")'). This is exactly what's needed when the schema lacks 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 action ('creates a new seat') and specifies the resource ('within a specific team'), providing a specific verb+resource combination. However, it doesn't explicitly distinguish this tool from sibling tools like 'cancel_seat', 'reactivate_seat', or 'suspend_or_unsuspend_seat' in terms of purpose, which prevents a perfect score.
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 like 'cancel_seat' or 'reactivate_seat'. It mentions the team context but doesn't specify prerequisites, dependencies, or exclusions. The agent must infer usage from the tool name alone.
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 mentions retrieval and CSV output but fails to disclose critical behavioral traits such as whether this is a read-only operation, potential rate limits, file size considerations, or authentication needs. For a tool with 6 parameters and no annotation coverage, 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a brief overview followed by parameter explanations and return information. It uses bullet points for clarity and avoids redundancy. However, the first two sentences are somewhat repetitive ('Export campaign statistics as a CSV file' and 'This retrieves statistics for all campaigns in CSV format'), slightly reducing efficiency.
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 6 parameters, no annotations, and an output schema (implied by 'Returns: CSV file data'), the description does an adequate job. It covers parameter semantics and output format but lacks behavioral context like safety, performance, or error handling. For a data export tool, this leaves gaps in 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?
Schema description coverage is 0%, so the description must compensate. It provides clear semantics for all 6 parameters, explaining each one's purpose (e.g., 'user_id: User ID', 'curves: List of statistic types to retrieve'). This adds substantial value beyond the bare schema, though it could benefit from examples or format details for timestamps and time zones.
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 exports campaign statistics as a CSV file, specifying the resource (campaign statistics) and format (CSV). It distinguishes from siblings like 'export_all_campaigns' and 'export_leads_from_campaign' by focusing on statistics rather than campaigns or leads. However, it doesn't explicitly differentiate from 'get_all_campaigns_statistics' or 'get_statistics' beyond the CSV format, keeping it from a perfect score.
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 statistics in CSV format, with a reference to 'get_statistics' for curve values, providing some context. However, it lacks explicit guidance on when to use this tool versus alternatives like 'get_statistics' (e.g., for API vs. file export) or prerequisites, leaving room for ambiguity.
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 burden. It states 'Retrieve' which implies a read-only operation, but doesn't disclose behavioral traits like authentication requirements, error handling (e.g., what happens if lead_id doesn't exist), rate limits, or whether it's idempotent. The description adds minimal context beyond the basic action.
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 appropriately sized and front-loaded: the first line states the core purpose, followed by structured 'Args' and 'Returns' sections. Every sentence earns its place by providing essential information without redundancy. The formatting enhances readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (single parameter, no nested objects) and the presence of an output schema (which handles return values), the description is reasonably complete. It covers the action, parameter meaning, and return content. However, it lacks behavioral details like error cases or prerequisites, which would be beneficial despite 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?
Schema description coverage is 0%, so the description must compensate. It adds meaning by explaining 'lead_id' as 'The unique identifier of the lead', which clarifies the parameter's purpose beyond the schema's type declaration. However, it doesn't provide format examples (e.g., numeric vs. string ID) or constraints, leaving some gaps.
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 verb 'Retrieve' and resource 'lead by ID', making the purpose specific and understandable. It distinguishes from siblings like 'list_leads' (which lists multiple) and 'create_lead' (which creates new). However, it doesn't explicitly contrast with 'get_lead_messages' or 'get_leads_from_campaign', which slightly limits differentiation.
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. It doesn't mention when to prefer 'get_lead' over 'list_leads' for single-record access, or how it relates to other lead-related tools like 'update_lead' or 'delete_lead'. Usage is implied by the action 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.
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 of behavioral disclosure. It states the tool retrieves data (implied read-only) and mentions pagination via limit/offset, but lacks critical details: authentication requirements (user_id, account_id), rate limits, error conditions, or whether the operation marks conversations as read. For a tool with 5 parameters and no annotations, this is insufficient.
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 efficiently structured: a brief purpose statement followed by well-organized 'Args' and 'Returns' sections. Every sentence earns its place, with no redundant or verbose content. It's front-loaded with the core functionality and uses clear formatting for 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 5 parameters with 0% schema coverage and no annotations, the description does a solid job: it explains the purpose, documents all parameters with defaults, and specifies the return value. An output schema exists, so return details aren't needed. However, it lacks behavioral context (e.g., auth needs, side effects), keeping it from a 5.
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 compensates well by documenting all 5 parameters in the 'Args' section with clear semantics: user_id, account_id, limit (default 100), offset (default 0), and name (optional contact filter). It adds meaning beyond the bare schema, though it doesn't explain parameter formats or constraints (e.g., ID formats).
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's purpose: 'Retrieve unread conversations' with optional filtering by contact name. It specifies the verb ('retrieve'), resource ('unread conversations'), and scope ('all conversations that have not been marked as read'). However, it doesn't explicitly differentiate from sibling tools like 'get_all_conversations' or 'get_other_conversations', which would require 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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_all_conversations' or 'get_other_conversations', nor does it specify prerequisites, exclusions, or contextual usage scenarios. The agent must infer usage from the tool name alone.
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 behavioral disclosure. While 'Import' implies a write operation, it doesn't specify permissions required, whether the operation is idempotent, how duplicates are handled, or what happens to existing blacklist entries. The return statement mentions 'import results' but gives no detail about format or potential errors.
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 clear sections (purpose, args, returns) and uses bullet-like formatting for parameter explanations. Every sentence adds value, though the 'Returns' section could be slightly more specific about what 'import results' includes.
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?
For a 5-parameter mutation tool with no annotations, the description provides good parameter documentation but lacks behavioral context about permissions, side effects, and error handling. The existence of an output schema helps, but the description should do more to explain what 'Success confirmation with import results' entails given this is a write operation.
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 provides excellent parameter documentation. It clearly explains all 5 parameters, including detailed options for 'keyword_type' and 'comparison_type' with specific enum values. This fully compensates for the schema's lack of descriptions and adds substantial semantic value beyond basic type 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 clearly states the action ('Import keywords to global blacklist') and resource ('from a CSV file'), making the purpose immediately understandable. It distinguishes from sibling 'import_keywords_to_blacklist_csv' by specifying 'global' blacklist, though it doesn't explicitly contrast with other blacklist tools like 'add_keywords_to_global_blacklist'.
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 about when to use this tool versus alternatives like 'add_keywords_to_global_blacklist' or 'import_keywords_to_blacklist_csv'. The description lacks context about prerequisites, appropriate scenarios, or exclusions for this batch import approach.
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 behavioral disclosure. It states the action ('send a new email') but doesn't mention authentication requirements, rate limits, error conditions, or what happens if the email fails. For a mutation tool with zero annotation coverage, this leaves significant behavioral 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 well-structured with a clear purpose statement followed by parameter documentation and return information. It's appropriately sized with no redundant information, though the 'Args' and 'Returns' sections could be integrated more seamlessly into the narrative flow.
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 with 0% schema description coverage and no annotations, the description compensates somewhat with parameter documentation. However, as a mutation tool with behavioral implications, it lacks sufficient context about authentication, error handling, and operational constraints. The presence of an output schema reduces the need to describe return values, but overall completeness remains moderate.
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' section that documents all 6 parameters with brief explanations, providing essential semantic meaning beyond the schema's 0% description coverage. It clarifies what each parameter represents (e.g., 'signature_id: ID of the signature to use'), though it could offer more detail on format expectations or constraints.
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's purpose: 'Send a new email to a recipient' with additional context about sending 'through the platform to a recipient who may not have an existing thread.' This distinguishes it from reply tools but doesn't explicitly differentiate from all sibling tools like 'send_email_reply' beyond the 'new email' vs 'reply' distinction.
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 context by specifying 'to a recipient who may not have an existing thread,' suggesting this is for initiating conversations rather than replying. However, it doesn't provide explicit guidance on when to use this versus alternatives like 'send_email_reply' or mention any 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?
With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a creation operation (implying mutation) and shows an example, but doesn't address permission requirements, rate limits, error conditions, or what happens if a role with the same name already exists. For a mutation tool with zero annotation coverage, this is insufficient.
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 clear sections (purpose, args, returns, example) and efficiently communicates essential information. The example is helpful but slightly lengthens the description. Every sentence earns its place, though the structure could be more 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's complexity (4 required parameters, mutation operation) and the presence of an output schema (which handles return values), the description does well by covering all parameters and providing an example. However, with no annotations, it should ideally address more behavioral aspects like authentication needs or error handling.
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 documenting all 4 parameters in the 'Args' section with clear explanations, including required status and format details for the permissions array. The example further clarifies parameter usage, adding significant value beyond the bare 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 action ('create a role') and target resource ('for a specific team with custom permissions'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'create_team' or 'create_tag', which would be needed for a perfect score.
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, prerequisites, or context. While sibling tools like 'get_team_roles' and 'update_team_member' exist, there's no mention of relationships or when this creation tool is appropriate versus those other team-related operations.
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 states 'removes' (implying mutation) but doesn't disclose behavioral traits like required permissions, whether deletion is reversible, rate limits, or error conditions. For a destructive operation with zero annotation coverage, 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 appropriately sized with a clear header, brief explanation, and structured Args/Returns sections. Every sentence adds value, though the 'Returns' line is somewhat redundant given the output schema.
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?
For a destructive tool with 5 parameters and no annotations, the description covers purpose and parameters adequately but lacks behavioral context. The existence of an output schema reduces the need to explain returns, but critical details like auth needs or side effects are 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?
Schema description coverage is 0%, so the description must compensate. It adds meaningful context for all 5 parameters: explaining that 'array_of_actions' are event action types, 'array_of_ids' are resource IDs, and 'url' is the target to delete. This goes beyond the bare schema types, though it doesn't specify formats or examples.
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 specific action ('Delete a global webhook') and the mechanism ('by matching URL and event subscriptions'), which distinguishes it from the sibling tool 'delete_webhook' (likely for non-global webhooks). It provides a precise verb+resource combination with scope differentiation.
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 offers no guidance on when to use this tool versus alternatives like 'delete_webhook' or prerequisites for deletion. It lacks explicit when/when-not instructions or named alternatives, leaving usage context unclear.
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 of behavioral disclosure. It mentions 'Retrieve' which implies a read-only operation, but doesn't specify permissions, rate limits, pagination behavior beyond the parameters, or what happens if no conversations match. The description adds minimal behavioral context beyond the basic operation.
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 clear purpose statement, followed by a context note, then parameter documentation, and finally return information. It's appropriately sized with no wasted sentences, though the 'Args' and 'Returns' sections could be integrated more seamlessly into the flow.
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 there's an output schema (though not shown in the context), the description doesn't need to detail return values. It covers the purpose, provides parameter semantics (compensating for 0% schema coverage), and gives basic context about what 'other conversations' means. For a retrieval tool with 5 parameters, this is reasonably 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?
The description provides an 'Args' section that documents all 5 parameters with clear explanations, including defaults for limit, offset, and name. Since schema description coverage is 0%, this description fully compensates by adding complete parameter semantics that aren't available in the schema alone.
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's purpose: 'Retrieve other conversations (not categorized as unread)' and specifies it gets conversations from the 'All other messages' section. This provides a specific verb ('retrieve') and resource ('other conversations'), but it doesn't explicitly distinguish from sibling tools like 'get_all_conversations' or 'get_unread_conversations' beyond the 'not categorized as unread' qualifier.
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 context by stating 'not categorized as unread' and referencing the 'All other messages' section, which suggests this is for non-unread conversations. However, it doesn't explicitly state when to use this tool versus alternatives like 'get_all_conversations' or 'get_unread_conversations', nor does it provide any exclusions 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 carries full burden. It states the tool 'retrieves' data, implying read-only behavior, and mentions pagination via 'limit' and 'offset,' which is helpful. However, it doesn't disclose critical behavioral traits such as authentication requirements, rate limits, error conditions, or whether the operation is idempotent, leaving significant gaps for a tool with no annotation coverage.
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 brief purpose statement followed by labeled sections for 'Args' and 'Returns.' It's front-loaded and efficient, with no wasted sentences. However, the 'Returns' section is somewhat redundant given the output schema, slightly reducing conciseness.
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 moderate complexity (4 parameters, no annotations, but with output schema), the description is reasonably complete. It covers purpose, parameters, and return value, and the output schema handles return details. However, it lacks behavioral context like error handling or usage constraints, which would be beneficial for full 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?
Schema description coverage is 0%, so the description must compensate. It provides a clear 'Args' section explaining all four parameters: 'user_id' and 'account_id' as identifiers, and 'limit' and 'offset' for pagination with defaults. This adds substantial meaning beyond the bare schema, though it could benefit from more detail on parameter formats or constraints.
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's purpose: 'retrieves all non-global webhooks configured for the account.' It specifies the verb ('retrieves') and resource ('non-global webhooks'), and distinguishes from the sibling tool 'list_global_webhooks' by explicitly mentioning 'non-global.' However, it doesn't fully differentiate from other webhook-related tools like 'create_webhook' or 'delete_webhook' beyond scope.
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 context by specifying 'non-global webhooks' and mentioning the sibling 'list_global_webhooks' in the tool list, suggesting when to use this vs. that alternative. However, it lacks explicit guidance on when to use this tool over other webhook tools (e.g., 'create_webhook') or prerequisites like required permissions.
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 the full burden. It implies a write operation ('registers', 'Created user object') and mentions email confirmation behavior via 'skip_confirmation_email'. However, it lacks details on authentication requirements, rate limits, error conditions, or whether registration is immediate versus pending confirmation.
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 clear sections (Args, Returns) and uses bullet-like formatting for parameters. Each sentence adds value, though the opening line 'This action registers a new user on the platform' is somewhat redundant with the title-equivalent 'Register New User' header.
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 mutation tool with no annotations, the description does a good job: it explains the action, documents all parameters thoroughly, and notes the return value. The presence of an output schema means it doesn't need to detail the response structure. However, it could better address behavioral aspects like permissions or side effects.
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 compensates well by documenting all 7 parameters with clear semantics: it distinguishes required vs. optional fields, provides examples (e.g., phone format), explains default values, and clarifies purpose (e.g., 'invitation_id for secure registration'). 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('registers a new user') and specifies the platform context. It distinguishes from siblings like 'create_seat' or 'invite_team_member' by focusing on user registration rather than team management or invitation workflows. However, it doesn't explicitly contrast with 'get_user_information' or other user-related 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?
The description provides no guidance on when to use this tool versus alternatives like 'invite_team_member' or 'create_seat', nor does it mention prerequisites such as admin permissions or whitelabel access. It simply states what the tool does without contextual usage instructions.
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 of behavioral disclosure. It mentions the action and return value but lacks critical details: it doesn't specify required permissions, whether the action is reversible, side effects on the seat or user, or any rate limits. For a mutation 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a title-like header, brief action statement, and organized sections for Args and Returns. It's appropriately sized with no redundant sentences, though the 'Args' and 'Returns' labels are slightly verbose compared to just listing parameters.
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 a mutation tool with no annotations, 3 parameters at 0% schema coverage, and an output schema present, the description is moderately complete. It covers parameters well and notes the return value, but lacks behavioral context like permissions or effects. The output schema reduces the need to detail returns, but more guidance on usage and risks is warranted.
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 compensate. It clearly explains all three parameters: 'user_id' as 'User ID who owns the seat', 'account_id' as 'Account/Seat ID to suspend/unsuspend', and 'suspended' as 'True to suspend, False to unsuspend'. This adds essential meaning beyond the bare schema, though it could note data formats 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?
The description clearly states the action ('suspend or unsuspend') and the resource ('a specific seat within a specific team'), with the title reinforcing this. It distinguishes itself from sibling tools like 'cancel_seat' and 'reactivate_seat' by focusing on suspension status rather than cancellation or reactivation.
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 like 'cancel_seat' or 'reactivate_seat', nor does it mention prerequisites or context for suspension/unsuspension. It only states what the tool does without indicating appropriate 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?
With no annotations, the description must fully disclose behavioral traits. It mentions deletion but fails to specify if it's irreversible, requires specific permissions, or has side effects (e.g., removing associated data). The return statement hints at confirmation but doesn't detail error handling or rate limits.
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 front-loaded with the core purpose ('Delete a lead by ID'), followed by structured sections for Args and Returns. Every sentence adds value without redundancy, making it efficient and easy to parse.
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?
For a destructive tool with no annotations and an output schema, the description is minimally adequate. It covers the basic action and parameter but lacks critical context like irreversible effects, permissions, or error scenarios. The presence of an output schema reduces the need to detail return values, but behavioral gaps remain.
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 carries the burden. It explains 'lead_id' as 'The unique identifier of the lead to delete', adding essential meaning beyond the schema's type definition. However, it doesn't specify format (e.g., UUID, numeric) or validation rules.
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 specific action ('Delete') and target resource ('a lead by ID'), distinguishing it from sibling tools like 'create_lead', 'update_lead', or 'get_lead'. It precisely communicates the tool's function without redundancy.
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., 'update_lead' for modifications, 'pause_lead_execution' for temporary halts). The description lacks context about prerequisites, such as confirming the lead exists or ensuring no active campaigns are affected.
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 of behavioral disclosure. It states the tool resumes a paused workflow, which implies a mutation operation, but doesn't disclose critical details such as required permissions, whether the action is reversible, potential side effects (e.g., restarting automated steps), or rate limits. For a mutation tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and concise, with three sentences that each serve a distinct purpose: stating the tool's purpose, providing context, and outlining args and returns. There's no wasted text, and key information is front-loaded, making it easy to scan and understand quickly.
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 complexity (a mutation operation with one parameter) and the presence of an output schema (implied by 'Returns: Confirmation of lead resumption'), the description is mostly complete. It covers purpose, parameter semantics, and return intent. However, without annotations, it lacks behavioral details like safety or permissions, and the output schema's existence means it doesn't need to explain return values further.
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 meaningful context for the single parameter: 'lead_id: The ID of the lead to resume.' With schema description coverage at 0%, the schema only indicates it's a required string. The description clarifies it's a lead ID, specifying the target entity, which compensates well for the low schema coverage. However, it doesn't detail format constraints (e.g., UUID) or where to find this ID.
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's purpose: 'Resume the execution of campaign steps for a specific lead.' It specifies the verb ('resume'), resource ('campaign steps'), and target ('lead'). However, it doesn't explicitly differentiate from sibling tools like 'pause_lead_execution' or 'return_lead_to_campaign' beyond mentioning 'previously paused lead,' which is implicit rather than explicit differentiation.
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 context by stating 'previously paused lead,' suggesting it should be used after pausing. However, it doesn't provide explicit guidance on when to use this tool versus alternatives like 'return_lead_to_campaign' or 'update_lead_in_campaign,' nor does it mention prerequisites or exclusions. The guidance is present but limited to implied 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 full burden but only states the action ('removes') without detailing behavioral aspects like permissions required, whether deletion is reversible, error responses, or rate limits. It mentions 'Success confirmation' but lacks specifics on what that entails.
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 clear sections (purpose, args, returns) and uses minimal sentences. The first sentence efficiently states the core action, though the 'Args' and 'Returns' sections could be more integrated into natural language.
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?
For a destructive operation with no annotations, 3 parameters, and an output schema, the description covers the basic purpose and parameters but lacks critical context like authentication needs, side effects, or error handling. The presence of an output schema reduces the need to detail return values, but behavioral gaps remain.
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 lists all three parameters with brief labels (e.g., 'User ID', 'Account ID', 'Webhook ID to delete'), adding basic semantic context beyond the schema's type definitions. However, it doesn't explain format, validation rules, or relationships between parameters.
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 specific action ('Delete'), resource ('a non-global webhook'), and mechanism ('by its ID'). It distinguishes from the sibling tool 'delete_global_webhook' by specifying 'non-global' scope, providing clear differentiation.
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 implicitly provides usage context by specifying 'non-global webhook' and mentioning the sibling 'delete_global_webhook' in the tool list, suggesting when to use this tool versus its global counterpart. However, it lacks explicit guidance on prerequisites or error conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that the tool retrieves data (implied read-only) and mentions pagination metadata, but lacks details on permissions, rate limits, error handling, or what specific data fields are returned in the campaign list. It adds some behavioral context 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 well-structured with clear sections (Args, Returns, Example) and front-loaded purpose. However, the example is lengthy and could be more concise, and some redundancy exists (e.g., repeating defaults in both description and 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?
Given 7 parameters, no annotations, and an output schema present, the description does a good job explaining inputs and general returns. It covers parameter semantics thoroughly but could improve by clarifying output structure or linking to sibling tools for better 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 description coverage is 0%, so the description must compensate fully. It provides detailed explanations for all 7 parameters, including defaults, enums (e.g., campaign_state codes, sort options), and usage examples, adding significant meaning beyond the bare 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 verb ('Retrieve') and resource ('list of all campaigns'), making the purpose evident. However, it doesn't explicitly differentiate this tool from sibling tools like 'get_all_campaigns_statistics' or 'get_campaign_info', which appear to serve related but distinct purposes.
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 like 'get_all_campaigns_statistics' or 'get_campaign_info', nor does it mention prerequisites or exclusions. Usage context is implied through parameter descriptions 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It describes a read operation ('retrieves statistics'), which is clear, but lacks details on permissions, rate limits, data format, or pagination. The description does not contradict annotations, but for a tool with 7 parameters and no annotations, it provides minimal behavioral context beyond the basic operation.
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 clear purpose statement followed by parameter details and return information. It is appropriately sized for a tool with 7 parameters, though the curves enum list is lengthy but necessary. Every sentence adds value, and it is front-loaded with the main 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 tool's complexity (7 parameters, no annotations, but with output schema), the description is largely complete. It covers purpose, parameters in detail, and mentions returns. With an output schema present, it need not explain return values. The main gap is lack of behavioral details like permissions or rate limits, but parameter documentation is thorough.
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 fully. It provides detailed semantics for all parameters: user_id, account_id, from_timestamp, to_timestamp, curves (with a comprehensive enum list), time_zone, and campaign_id (noting it's optional). This adds significant meaning beyond the bare schema, effectively documenting each parameter's purpose and constraints.
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's purpose: 'Get statistics for campaigns within a time range' and specifies it retrieves statistics for all campaigns or a specific one. It distinguishes itself from siblings like 'get_all_campaigns_statistics' by mentioning optional campaign_id filtering, though not explicitly contrasting with that sibling. The verb 'Get' and resource 'statistics for campaigns' are specific.
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 context by stating it retrieves statistics for all campaigns or a specific one if campaign_id is provided, but does not explicitly state when to use this tool versus alternatives like 'get_all_campaigns_statistics' or 'get_step_statistics'. No exclusions or prerequisites are mentioned, leaving usage guidance at an implied level.
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 the full burden. It discloses that this is a retrieval action (not destructive) and mentions the return format (list with IDs), but doesn't cover behavioral aspects like authentication needs, rate limits, pagination, or error handling. It adds basic context but lacks depth for a tool with no annotation support.
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 clear title, action statement, parameter explanations, and return information in separate sections. It's appropriately sized with no redundant sentences, though the second sentence about using IDs could be slightly more integrated.
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 (which handles return values), no annotations, and simple parameters, the description is reasonably complete. It covers purpose, parameters, and usage context. However, for a tool with no annotations, it could benefit from more behavioral details like permissions or limitations.
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 schema provides no parameter details. The description compensates by explaining both parameters: 'user_id' as 'ID of the user whose saved sequences to retrieve' and 'team_id' as 'ID of the team that the user is part of'. This adds meaningful semantics beyond the bare schema, though it doesn't specify format or constraints.
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 action ('retrieves all sequence templates') and specifies the resource ('saved sequences from a user who is a part of certain team'). It distinguishes from siblings by focusing on user-specific sequence templates, though it doesn't explicitly contrast with similar tools like 'get_campaign_list' or 'get_user_information'.
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 by mentioning the returned IDs can be used in 'Create Campaign From A Sequence Template' endpoint, providing some context. However, it lacks explicit guidance on when to use this tool versus alternatives (e.g., other 'get_' tools for campaigns or users) or any prerequisites beyond the required parameters.
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 the full burden of behavioral disclosure. It mentions 'pagination' and describes the return format, which is helpful. However, it doesn't address important behavioral aspects like rate limits, authentication requirements, error conditions, or whether this is a read-only operation (though 'list' implies it likely is). The description adds some value but leaves significant gaps for a tool with no annotation coverage.
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 clear purpose statement followed by organized parameter documentation. It's appropriately sized for a tool with 6 parameters. The only minor inefficiency is the repetition of 'Filter' in multiple parameter descriptions, but overall it's front-loaded and 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 that there's an output schema (indicated by 'Has output schema: true'), the description doesn't need to explain return values in detail. It mentions the return format at a high level. With no annotations and 0% schema description coverage, the description does a good job documenting parameters. The main gap is lack of guidance on when to use this versus sibling tools, but otherwise it's reasonably complete for a listing/filtering 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?
The schema description coverage is 0%, meaning the input schema provides no parameter descriptions. The description compensates fully by documenting all 6 parameters with clear explanations of their purpose, optionality, data types, and constraints (e.g., 'ISO 8601 datetime', '1-1000, default: 100'). This adds substantial value beyond what the bare schema provides.
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's purpose: 'List and filter leads with pagination'. It specifies the verb ('list and filter'), resource ('leads'), and key capability ('pagination'). However, it doesn't explicitly differentiate this tool from sibling tools like 'get_leads_from_campaign' or 'get_lead', which might have overlapping functionality.
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. With many sibling tools like 'get_leads_from_campaign', 'get_lead', and 'export_leads_from_campaign', there's no indication of when this general listing/filtering tool is preferred over more specific ones. The description only documents parameters 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?
With no annotations provided, the description carries full burden for behavioral disclosure. It reveals that 'tags' parameter 'replaces existing tags' while 'custom_fields' 'merges with existing' - important behavioral details not evident from the schema. However, it doesn't mention authentication requirements, error conditions, rate limits, or whether this is a destructive operation (though 'update' implies mutation).
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 clear sections (Args, Returns) and front-loaded purpose. Every sentence earns its place by providing essential information. It could be slightly more concise by integrating the parameter explanations more tightly, but overall it's efficiently organized with minimal 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 this is a mutation tool with 9 parameters, 0% schema description coverage, no annotations, but with an output schema (implied by 'Returns: Updated lead object'), the description does a good job. It explains all parameters and their behaviors, though it could provide more context about error conditions, permissions, or system constraints. The presence of an output schema reduces the need to describe return values in detail.
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 - and it does so excellently. It provides clear semantic explanations for all 9 parameters, including crucial behavioral details about 'tags' (replaces) and 'custom_fields' (merges). The description adds significant value beyond the bare schema, explaining what each parameter represents and how they behave.
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's purpose: 'Update an existing lead's properties' - a specific verb ('update') and resource ('lead'). It distinguishes from obvious siblings like 'create_lead' and 'delete_lead', though it doesn't explicitly differentiate from 'update_lead_in_campaign' which appears to be a related but distinct operation.
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. There's no mention of prerequisites, when this should be used instead of 'update_lead_in_campaign', or any context about required permissions or system state. The agent must infer usage from the tool name alone.
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 burden. While it states this is an update operation, it doesn't disclose behavioral traits like required permissions, whether changes are reversible, rate limits, or what happens to existing values not mentioned. The example shows syntax but 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with clear sections (purpose, Args, Returns, Example). The first sentence efficiently states the core purpose. The example is helpful but makes the description longer than minimal.
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?
For a mutation tool with 4 parameters, 0% schema coverage, no annotations, but with output schema present, the description covers parameters adequately but lacks behavioral context. The output schema reduces need to explain returns, but permission requirements and mutation implications should be addressed.
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 well by explaining all 4 parameters in the Args section, including the structure of 'changed_values' and examples of field types. It adds meaningful semantics beyond the bare schema, though doesn't specify format constraints for IDs.
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 specific action ('Update one or more variables for a lead'), the resource ('lead in a specified campaign and LinkedIn account'), and scope ('including built-in fields and custom variables'). It distinguishes from sibling tools like 'update_lead' by specifying the campaign and LinkedIn account context.
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 needing to modify lead data within a specific campaign and LinkedIn account context, but doesn't explicitly state when to use this vs. alternatives like 'update_lead' or 'add_leads_to_campaign'. No prerequisites or exclusions 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the creation of a lead ('Created lead information') but lacks details on permissions required, whether the operation is idempotent, error handling, or rate limits. For a mutation tool with zero annotation coverage, 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear purpose statement, parameter explanations, return note, and example. Each sentence adds value, but the example could be more integrated or the parameter details slightly condensed for optimal brevity without losing clarity.
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 moderate complexity (4 parameters, mutation operation) and the presence of an output schema (which handles return values), the description is mostly complete. It covers parameter semantics well but lacks behavioral context like error cases or side effects, which is a minor gap given the output schema's support.
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 compensate. It effectively explains all four parameters: clarifies that 'campaign_id' is required, specifies the mutual exclusivity between 'profile_url' and 'email', and provides examples for 'custom_fields'. This adds substantial meaning beyond the bare schema, though it could detail data formats or constraints further.
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 'Add' and resource 'lead to a selected campaign', making the purpose specific and actionable. It distinguishes itself from sibling tools like 'create_lead' (which likely creates a lead without campaign association) and 'update_lead_in_campaign' (which modifies existing leads), establishing clear functional boundaries.
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 by specifying that either profileUrl or email is required, but it does not explicitly state when to use this tool versus alternatives like 'create_lead' or 'update_lead_in_campaign'. No exclusions or prerequisites are mentioned, leaving some ambiguity in tool selection.
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 discloses the admin requirement, which is crucial behavioral context. However, it lacks details on rate limits, pagination, error handling, or what 'List of all teams' entails structurally. The description adds value but misses comprehensive behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized with three sentences: purpose, admin requirement, and return value. It's front-loaded with the core action. The 'Args:' and 'Returns:' sections are slightly redundant with the prose but maintain clarity. No wasted sentences, though minor trimming is possible.
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 1 parameter, 0% schema coverage, no annotations, and an output schema exists, the description is fairly complete. It covers purpose, prerequisites, and return scope. The output schema handles return values, so no need to detail them. It could improve by addressing potential errors or limitations, but it's sufficient for basic use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds meaning by explaining 'user_id: User ID (must be platform admin)', clarifying the parameter's role and constraint beyond the bare schema. Since there's only one parameter, this adequately covers semantics, though it could specify format or validation.
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 verb 'retrieves' and resource 'all teams under one platform (White label)', making the purpose specific. It distinguishes from siblings like 'get_team_members' or 'create_team' by focusing on whitelabel scope, though it doesn't explicitly compare to them. The title-like first line is redundant but doesn't detract from clarity.
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 when to use this tool: 'The user who runs this endpoint must be the platform admin.' This provides clear context about prerequisites. However, it doesn't mention when not to use it or name alternatives among siblings, such as 'list_all_seats_of_a_specific_user' for different scopes.
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 of behavioral disclosure. It states the action ('resends') and outcome ('allows them to confirm their email address'), but does not disclose critical behavioral traits such as required permissions, rate limits, whether it triggers notifications, or error conditions. The description is insufficient for a mutation tool with zero annotation coverage.
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 well-structured with a title, action explanation, parameter details, and return value—all in four concise sentences. Each sentence adds value without redundancy, and key information is front-loaded. It efficiently communicates the tool's purpose and usage.
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 (implied by 'Returns: Confirmation that the email was sent'), the description does not need to detail return values. It covers the purpose, parameters, and basic outcome adequately. However, as a mutation tool with no annotations, it could benefit from more behavioral context (e.g., side effects, error handling) to be fully 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 description coverage is 0%, so the schema provides no parameter descriptions. The description compensates by explaining the semantics of both parameters: 'user_id: User ID to resend confirmation for' and 'email: Email address that should receive the confirmation email'. It adds clear meaning beyond the bare schema, though it could include format examples (e.g., email format requirements).
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 specific action ('resends an email confirmation message') and the target resource ('to the user's email'), with a distinct purpose from sibling tools like 'send_password_reset_email' or 'send_new_email'. It explicitly differentiates by focusing on email confirmation rather than password reset or general email sending.
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 context (when a user needs to confirm their email address) but does not explicitly state when to use this tool versus alternatives like 'send_password_reset_email' or 'register_new_user'. It provides basic context but lacks explicit 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.
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 discloses the action's purpose and outcome ('retrieves all LinkedIn messages', 'displays them inside the platform's inbox'), but doesn't mention behavioral traits like whether this is a one-time sync or continuous, potential rate limits, authentication requirements beyond the parameters, or what happens if messages already exist in the inbox. It adds some context but misses important operational details.
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 statement, parameter explanations, return information, and an example. Every sentence adds value, though the example could be integrated more seamlessly. It's appropriately sized for a 2-parameter tool with clear sections.
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 2 parameters with 0% schema coverage but an output schema exists, the description provides adequate context. It explains what the tool does, what parameters mean, what it returns, and includes an example. The output schema means the description doesn't need to detail return values, making this reasonably 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.
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 compensate. It provides clear semantic meaning for both parameters ('user_id: Your user ID', 'account_id: The ID of the seat'), explaining what they represent beyond just their names. However, it doesn't specify format constraints or provide examples of valid values beyond the single example.
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 with specific verbs ('sync', 'retrieves', 'displays') and resources ('LinkedIn messages', 'platform inbox'). It distinguishes this tool from siblings like 'get_messages_for_leads' or 'get_all_conversations' by specifying it's for syncing LinkedIn messages to a centralized inbox rather than just fetching messages.
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 context ('for centralized message management') and mentions prerequisites ('specific seat'), but doesn't explicitly state when to use this tool versus alternatives like 'get_linkedin_user_info' or 'connect_linkedin_account'. It provides basic context but lacks explicit guidance on when-not-to-use or direct alternatives.
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 this is a write operation ('Add'), which implies mutation, but doesn't disclose behavioral traits like required permissions, whether changes are reversible, rate limits, or error handling. The 'Returns: Success confirmation' provides minimal output information, but lacks detail on what that confirmation contains or failure modes.
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 appropriately sized with a clear purpose statement followed by structured parameter documentation. The 'Args:' and 'Returns:' sections provide organized information. While efficient, the 'via JSON' qualifier could be integrated more smoothly, and the return statement is somewhat terse.
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 with 0% schema coverage and no annotations, the description does well by documenting all parameters thoroughly. The output schema exists (though unspecified), so the description doesn't need to detail return values. For a mutation tool with complex parameters, it provides adequate context, though behavioral aspects could be more 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?
With 0% schema description coverage, the description fully compensates by providing detailed parameter documentation. It explains all 5 parameters with clear examples (e.g., keywords: ['test', 'test123']) and enumerates options for keyword_type and comparison_type. 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 specific action ('Add keywords to the global blacklist') and resource ('global blacklist'), distinguishing it from sibling tools like 'add_keywords_to_blacklist' (non-global) and 'import_keywords_to_global_blacklist_csv' (CSV import). It provides a complete verb+resource+scope statement.
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 adding keywords to a global blacklist via JSON, but doesn't explicitly state when to use this tool versus alternatives like the CSV import sibling. No prerequisites or exclusions are mentioned, leaving usage context somewhat implied rather than explicit.
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 the full burden. It discloses that this is a creation operation ('creates a lead source') and mentions the outcome ('connects it to a campaign for automatic lead import'), but lacks details on permissions, side effects, error handling, or rate limits. It's 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with purpose statement, parameter explanations, return info, and an example. The description is appropriately sized but could be slightly more concise by integrating the example more tightly. 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 the tool's complexity (8 parameters, creation operation) and no annotations, the description does well: clear purpose, detailed params, return info, and example. With an output schema present, it doesn't need to explain return values. Minor gaps in behavioral transparency keep it from a 5.
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 fully. It provides detailed explanations for all 8 parameters, including examples ('e.g., LinkedIn Sales Navigator search'), optional flags, and default behaviors. 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 tool's purpose: 'Create a lead source and link it to a campaign' with specific examples ('Sales Navigator search URL') and explains the outcome ('automatic lead import'). It distinguishes from sibling tools like 'create_lead' by focusing on lead source creation rather than lead creation.
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 context ('for automatic lead import') but doesn't explicitly state when to use this tool versus alternatives like 'add_leads_to_campaign' or 'create_lead'. It mentions linking to a campaign but doesn't specify prerequisites or exclusions.
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 the full burden of behavioral disclosure. It describes the filtering logic ('OR within groups, AND between groups') and output format ('CSV export data or download URL'), which adds useful context. However, it does not mention potential side effects, rate limits, authentication needs, or what happens with large exports, leaving gaps for a mutation-like export operation.
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 clear purpose statement, filtering logic explanation, parameter details, return information, and an example. It is appropriately sized for a complex tool with many parameters, though some sections like the parameter list are lengthy but necessary given the lack of schema descriptions.
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 (16 parameters, no annotations, schema coverage 0%, but has output schema), the description is quite complete. It explains the tool's purpose, filtering logic, all parameters, and return values. The output schema handles return structure, so the description's mention of 'CSV export data or download URL' is sufficient. Minor gaps remain in behavioral aspects like error handling or export limits.
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 fully. It provides detailed explanations for all 16 parameters, including the meaning of status codes (e.g., '[1]=Discovered'), relationships between parameters (e.g., 'filter_by_connection_degree' used with 'filter_by_status=[4]'), and practical usage notes. 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 specific action ('Export leads'), resource ('from a specific campaign'), and output format ('in CSV format with advanced filtering'). It distinguishes itself from sibling tools like 'export_all_campaigns' or 'get_leads_from_campaign' by emphasizing the export functionality and filtering capabilities.
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 context through the mention of 'advanced filtering' and the example, but does not explicitly state when to use this tool versus alternatives like 'get_leads_from_campaign' or 'export_all_campaigns'. It provides some guidance through the example parameters but lacks explicit when/when-not statements.
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 of behavioral disclosure. It effectively describes the action as a retrieval (non-destructive), specifies the paginated return format, and details user types based on seat relationships. However, it does not mention potential rate limits, authentication needs, or error conditions, which are gaps 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear title, purpose statement, user type breakdown, and sections for Args and Returns. It is appropriately sized without fluff, though the user type list could be slightly condensed. Every sentence adds value, making it efficient and front-loaded with key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 parameters with 0% schema coverage and no annotations, the description does a good job explaining parameters and return values. With an output schema present, it need not detail return structure further. However, for a tool with no annotations, it could better address behavioral aspects like error handling or performance limits to be fully 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 description coverage is 0%, so the description must compensate. It adds meaningful context for all 5 parameters: 'user_id' and 'account_id' are required for identifying the seat, while 'limit', 'offset', and 'search' are explained with defaults and purposes. This goes beyond the bare schema, though it could provide more detail on parameter interactions 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?
The description clearly states the verb 'retrieves' and the resource 'all users associated with the chosen seat', specifying the scope with 'in any way'. It distinguishes from sibling tools like 'get_team_members' or 'list_all_users_as_a_whitelabel' by focusing on seat-specific associations, making the purpose specific and differentiated.
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 needing to find users related to a specific seat, but does not explicitly state when to use this tool versus alternatives like 'get_team_members' or 'list_all_users_as_a_whitelabel'. It provides context on user types but lacks explicit guidance on exclusions or prerequisites, leaving usage somewhat inferred rather than clearly defined.
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 that this is a creation operation ('creates a webhook'), which implies mutation, and adds context about scoping ('non-global webhooks are scoped to specific campaigns or resources'). However, it lacks details on permissions, rate limits, error handling, or what 'Created webhook details' entails. For a mutation tool with zero annotation coverage, this is a moderate 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 appropriately sized and front-loaded: the first sentence states the purpose clearly, followed by explanatory context and structured parameter details. Every sentence earns its place, though the formatting with bullet points in Args could be slightly more concise. Overall, it's efficient with minimal 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 a mutation tool with no annotations, 3 parameters (0% schema coverage), and an output schema exists (so return values needn't be explained), the description is fairly complete. It covers purpose, usage context, and parameter semantics well. However, it lacks behavioral details like auth needs or error cases, which is a minor gap for a creation 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 adds significant meaning beyond the schema by explaining all three parameters: user_id and account_id are identified, and webhooks is detailed with its nested structure (url, events, campaignId). This fully documents the parameters, 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 the verb ('Create') and resource ('non-global webhook'), explicitly distinguishes it from sibling tools by specifying 'non-global' (vs. 'global' webhooks like create_global_webhook and delete_global_webhook), and explains the scope ('scoped to specific campaigns or resources'). This is specific and distinguishes from siblings effectively.
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 for when to use this tool: for creating webhooks that are 'non-global' and 'scoped to specific campaigns or resources.' It implies an alternative (global webhooks) through the sibling tool names, but does not explicitly name when-not-to-use scenarios or direct alternatives like 'use create_global_webhook for global webhooks.'
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 that the action is immediate by default but can be scheduled, which is useful behavioral context. However, it lacks details on permissions required, whether the action is reversible, rate limits, or what happens if the lead is already in the target campaign. For a mutation tool with zero annotation coverage, this leaves gaps in safety and operational 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 front-loaded with the core purpose in the first sentence, followed by behavioral context and a structured breakdown of args and returns. Every sentence earns its place: the first states the action, the second adds timing behavior, and the parameter/return sections provide essential details without redundancy. It is appropriately sized for a 5-parameter tool.
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 complexity (mutation with 5 parameters, no annotations, but has an output schema), the description is mostly complete. It covers purpose, timing behavior, and parameter semantics partially. The output schema exists, so the description need not explain return values beyond the brief confirmation statement. However, it could improve by addressing missing behavioral aspects like permissions or error 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?
Schema description coverage is 0%, so the description must compensate. It adds meaningful semantics: it explains that 'scheduled_time' is an 'Optional ISO 8601 datetime to schedule the action', which clarifies format and purpose beyond the schema's type definitions. However, it does not describe the semantics of other parameters (e.g., what user_id or account_id represent, or how lead_id and target_campaign_id are obtained), leaving some ambiguity.
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 specific action ('return a specific lead to a specific campaign') with precise verbs and resources. It distinguishes from sibling tools like 'add_leads_to_campaign' (which adds new leads) and 'update_lead_in_campaign' (which modifies existing leads) by focusing on returning a lead to a campaign, implying it was previously removed or elsewhere.
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 for usage: 'This action happens immediately unless a scheduled time is provided.' This indicates when to use the scheduled_time parameter. However, it does not explicitly state when to use this tool versus alternatives like 'add_leads_to_campaign' or 'update_lead_in_campaign', or mention any prerequisites (e.g., lead must exist, campaign must be active).
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 full burden. It discloses key behavioral traits: the campaign is 'URL-based,' created 'from the user's saved sequences,' and 'goes live immediately after creation.' This covers creation method, timing, and resource dependency, though it lacks details on permissions, error handling, or rate limits.
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 well-structured and front-loaded: the first sentence states the purpose, followed by behavioral details, then a parameter breakdown, return info, and an example. Every sentence earns its place without redundancy, making it 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 no annotations, 0% schema coverage, and an output schema present, the description does well: it explains purpose, behavior, and parameters thoroughly. However, it could improve by mentioning authentication needs or potential side effects, but the output schema reduces the need for return value details.
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 provides clear semantics for all parameters: 'user_id' and 'account_id' specify ownership, 'sequence_template_id' identifies the template, 'campaign_name' names the campaign, and 'lead_source_url' is optional for attaching a URL. This adds substantial 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 specific action ('Create a new campaign'), the resource ('from a saved sequence template'), and the type ('URL-based campaign'). It distinguishes this tool from sibling tools like 'create_lead' or 'create_lead_source' by focusing on campaign creation from templates.
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 context by mentioning 'saved sequences' and 'goes live immediately,' but doesn't explicitly state when to use this tool versus alternatives like 'create_campaign' (if it existed) or 'add_leads_to_campaign.' No exclusions or prerequisites are provided.
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 of behavioral disclosure. It effectively describes the filtering logic (7 groups with OR/AND logic), pagination behavior (limit/offset defaults), and return format (list with pagination metadata). It doesn't mention rate limits, authentication requirements, or error conditions, but provides substantial operational 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 clear sections (overview, filter groups, args, returns, example) but could be more concise. Some parameter explanations are verbose, and the filter group listing could be streamlined. However, information is front-loaded with the core purpose first.
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 (18 parameters, advanced filtering logic), no annotations, and the presence of an output schema, the description provides comprehensive context. It explains filtering semantics, parameter usage, return format, and includes a practical example, making it complete enough for effective tool 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?
With 0% schema description coverage for 18 parameters, the description fully compensates by providing detailed explanations for each parameter, including enum mappings for status and connection degree filters, default values for limit/offset, and clarification of parameter relationships (e.g., filter_by_connection_degree used with filter_by_status=[4]).
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 with a specific verb ('Retrieve') and resource ('leads from a specific campaign'), and distinguishes it from siblings by specifying 'advanced filtering' capabilities. The opening sentence immediately communicates the core function.
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 through the detailed filter explanations but doesn't explicitly state when to use this tool versus alternatives like 'get_leads_from_seat' or 'list_leads'. It provides context about filtering capabilities but lacks explicit guidance on tool selection criteria.
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 full burden and does well by disclosing key behavioral traits: it explains the complex filtering logic (6 groups with OR/AND combinations), describes pagination behavior (limit/offset defaults), and clarifies the return format. However, it doesn't mention rate limits, authentication requirements, or error conditions that would be helpful for a read operation.
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 appropriately front-loaded with purpose and filtering overview, but becomes verbose with detailed parameter listings that could be more efficiently structured. While all information is valuable given the complex parameter set, the Args/Returns/Example sections create redundancy with the initial overview, making it longer than 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?
For a complex filtering tool with 16 parameters, 0% schema coverage, and no annotations, the description provides excellent coverage of parameters and behavior. The presence of an output schema means return values don't need explanation. The main gap is lack of operational context like rate limits or error handling, but overall it's quite complete for agent usage.
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 for 16 parameters, the description fully compensates by providing comprehensive parameter documentation. Each parameter gets clear explanations, including enum values for status filters, relationships between parameters (e.g., filter_by_connection_degree used with filter_by_status=[4]), and practical examples of what each filter does.
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 with specific verb ('Retrieve') and resource ('leads from a specific seat'), and distinguishes it from siblings by mentioning 'advanced filtering' capabilities. It explicitly differentiates from tools like 'get_lead' (single lead) and 'list_leads' (likely simpler listing).
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 about when to use this tool: for retrieving leads with advanced filtering from a specific seat/account. It implies usage through the detailed filter explanations but doesn't explicitly state when NOT to use it or name specific alternatives among siblings, though the filtering focus suggests differentiation from simpler listing tools.
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 of behavioral disclosure. It effectively explains the two invitation modes (automatic acceptance vs. email-based acceptance/decline), which is crucial behavioral context. It also mentions default values for optional parameters. However, it doesn't cover error conditions, permission requirements, or rate limits.
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 clear sections (purpose, flag explanation, args, returns, example). The example is comprehensive but lengthy. Some redundancy exists between the flag explanation and parameter description. Overall efficient but could be more concise.
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 mutation tool with 7 parameters, 0% schema coverage, and no annotations, the description does an excellent job covering parameters and core behavior. The presence of an output schema means return values don't need explanation. However, it lacks information about error cases, authentication requirements, and system constraints.
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 providing detailed parameter documentation. Each parameter is clearly explained with purpose, required status, and default values where applicable. The 'account_roles' parameter gets specific structural guidance with 'roleId' and 'accounts' array details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Invite a user') and resource ('to become a member of a specific team'), distinguishing it from sibling tools like 'create_team' or 'update_team_member'. The verb+resource combination is precise and unambiguous.
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 about how the invitation works with the 'sendAnInvitationEmail' flag, explaining the two modes of operation. However, it doesn't explicitly state when to use this tool versus alternatives like 'create_team' or 'update_team_member', nor does it mention prerequisites or exclusions.
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 of behavioral disclosure. It effectively communicates the mutation nature ('changes'), authorization requirements (user vs co-owner permissions), and the expected outcome ('Confirmation of password change'). However, it doesn't mention potential side effects (e.g., session termination), rate limits, or error conditions that might be relevant for a password change operation.
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 well-structured and appropriately sized. It begins with a clear title-like statement, follows with usage context, then documents parameters and return value in labeled sections. Every sentence adds value with no redundancy or 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?
For a mutation tool with no annotations, 0% schema coverage, but with an output schema, the description does well overall. It covers purpose, usage guidelines, parameter meanings, and return confirmation. The main gap is lack of behavioral details like security implications, error cases, or what the confirmation contains. The output schema presumably documents the return structure, reducing the need for that in the description.
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 compensate. It provides clear semantic meaning for both parameters: 'user_id: User ID whose password to change' and 'new_password: New password to set'. This adds essential context beyond the bare schema types. However, it doesn't specify password complexity requirements or user_id format constraints that would be helpful.
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 action ('changes the password') and resource ('for a specific user'). It distinguishes this tool from sibling tools like 'send_password_reset_email' by specifying direct password modification rather than reset initiation. The purpose is specific and unambiguous.
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 description provides explicit usage guidance: 'Regular users can only change their own password and platform co-owners can change the password for all users within their platform.' This clearly defines when different users should use this tool based on their permissions, addressing the critical context of authorization levels.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![multilead-mcp MCP server](https://glama.ai/mcp/servers/vanman2024/multilead-mcp/badges/card.svg)](https://glama.ai/mcp/servers/vanman2024/multilead-mcp)

Score Badge

Copy to your README.md:

[![multilead-mcp MCP server](https://glama.ai/mcp/servers/vanman2024/multilead-mcp/badges/score.svg)](https://glama.ai/mcp/servers/vanman2024/multilead-mcp)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/vanman2024/multilead-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server