Smartlead MCP Server

Server Quality Checklist

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Latest release: v0.2.1
Disambiguation4/5
Most tools have distinct purposes targeting specific resources and actions, but there is some overlap between analytics tools (get_campaign_analytics, get_campaign_analytics_by_date, get_campaign_statistics) that could cause confusion. The lead management tools (pause_lead, resume_lead, unsubscribe_lead_from_campaign, unsubscribe_lead_globally) are well-differentiated.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern with clear action verbs (add, create, delete, get, list, pause, reconnect, remove, resume, save, unsubscribe, update). The naming is uniform throughout, using snake_case exclusively without any deviations.
Tool Count3/5
With 30 tools, the count is borderline high for an email campaign management server. While it covers many operations, it may feel heavy and could benefit from consolidation or better scoping. The number is not extreme but pushes the upper limit of typical well-scoped sets.
Completeness5/5
The tool set provides comprehensive coverage for email campaign management, including full CRUD for campaigns, email accounts, and leads, plus analytics, scheduling, warmup, and sequence management. There are no obvious gaps, and agents can handle complete workflows without dead ends.
Average 3/5 across 30 of 30 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 status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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}
```
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How is the quality score calculated?

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

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

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

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

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves statistics but doesn't mention whether this is a read-only operation, if it requires specific permissions, what the output format looks like, or any rate limits. For a tool with 5 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 a single, efficient sentence that front-loads the core purpose. It avoids redundancy and wastes no words, though it could be slightly more informative without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (5 parameters, no annotations, no output schema), the description is inadequate. It doesn't explain what 'detailed campaign statistics' includes, how results are structured, or behavioral aspects like pagination handling. For a data retrieval tool with multiple filters, more context is needed to guide effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds minimal value by implying filtering capabilities ('optional filters'), but doesn't provide additional context beyond what's in the schema, such as how filters combine or typical use cases. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the verb ('Get') and resource ('campaign statistics') with a qualifier ('detailed'), which provides a basic purpose. However, it doesn't distinguish this tool from sibling tools like 'get_campaign_analytics' or 'get_campaign_analytics_by_date', leaving ambiguity about what specific statistics are retrieved or how this differs from other analytics 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 mentions 'optional filters' but provides no guidance on when to use this tool versus alternatives like 'get_campaign_analytics'. There's no explicit mention of prerequisites, exclusions, or comparisons to sibling tools, 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 mentions 'Add' which implies a mutation, but doesn't specify if this requires special permissions, whether it's idempotent, what happens on duplicate accounts, or any rate limits. This leaves significant gaps in understanding the tool's behavior 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 a single, clear sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the essential information, making it highly efficient and easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what the tool returns, potential side effects, error conditions, or how it interacts with other tools like 'list_campaign_email_accounts'. Given the complexity implied by the sibling tools, more context is needed for safe and effective use.
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 100%, so the schema already documents both parameters ('campaign_id' and 'email_account_ids') adequately. The description doesn't add any additional semantic context about these parameters beyond what's in the schema, such as format examples or constraints, meeting the baseline for good schema coverage.
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') and resources ('email accounts to a campaign'), making the purpose immediately understandable. It distinguishes itself from siblings like 'remove_campaign_email_accounts' by specifying addition rather than removal, though it doesn't explicitly mention how it differs from tools like 'create_email_account' or 'update_campaign_settings'.
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. For example, it doesn't clarify if this should be used instead of 'create_email_account' for existing accounts, or whether there are prerequisites like the campaign needing to be active. The description only states what it does, not when it's appropriate.
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 'Create' implies a write/mutation operation, the description doesn't disclose any behavioral traits like required permissions, whether this operation is idempotent, what happens on failure, rate limits, or what the response contains. 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that states the core purpose without unnecessary words. It's appropriately sized and front-loaded with the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool (creating campaigns) with no annotations and no output schema, the description is inadequate. It doesn't explain what happens after creation, what permissions are needed, whether client_id is required for certain contexts, or what the tool returns. Given the complexity of campaign creation and the lack of structured data, the description should provide more 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 100%, so the schema already documents both parameters ('name' and 'client_id') with their types and descriptions. The description adds no additional parameter information beyond what the schema provides, so it meets the baseline expectation when schema coverage is complete.
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') and resource ('new email campaign in Smartlead'), providing a specific verb+resource combination. However, it doesn't differentiate this from sibling tools like 'save_campaign_sequences' or 'update_campaign_settings' which might also involve campaign creation or modification.
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 available (like update_campaign_settings, save_campaign_sequences, etc.), there's no indication of when create_campaign is appropriate versus modifying existing campaigns or using other campaign-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?
With no annotations provided, the description carries full burden but offers limited behavioral insight. It implies a write operation ('create') but doesn't disclose permissions needed, whether it's idempotent, error handling, or what happens on success (e.g., returns an account ID). For a mutation tool with 11 parameters, this lack of detail 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 a single, efficient sentence with zero wasted words. It's front-loaded with the core action and includes useful parenthetical examples. Every element earns its place, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex creation tool with 11 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what the tool returns, error conditions, or how it integrates with sibling tools (e.g., campaign-related functions). The agent lacks sufficient context to use this tool effectively in isolation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so parameters are well-documented in the schema itself. The description adds minimal value by hinting at credential types (e.g., Gmail, Outlook) which loosely relates to the 'type' enum, but doesn't explain parameter interactions or provide examples. Baseline 3 is appropriate given the schema does the heavy lifting.
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 email account') and specifies the mechanism ('by connecting existing SMTP/IMAP credentials'), which distinguishes it from tools like 'update_email_account' or 'get_email_account'. However, it doesn't explicitly differentiate from sibling 'add_campaign_email_accounts', which might have overlapping functionality in a campaign context.
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_email_account' or 'add_campaign_email_accounts'. It mentions credential types (Gmail, Outlook, etc.) but doesn't specify prerequisites, constraints, or typical use cases, leaving the agent with minimal 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?
With no annotations, the description carries full burden but provides minimal behavioral insight. It states permanence, hinting at irreversibility, but lacks details on permissions, side effects (e.g., impact on leads or analytics), error conditions, or confirmation requirements. This is inadequate for a destructive 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 a single, efficient sentence with zero waste. It's front-loaded with the core action and resource, making it easy to parse quickly. Every word earns its place by conveying essential information without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a destructive tool with no annotations and no output schema, the description is incomplete. It lacks critical context such as return values (e.g., success/failure indicators), error handling, dependencies on other tools, or safety warnings. This leaves significant gaps for an AI agent to 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 100%, so the schema already documents the 'campaign_id' parameter. The description adds no additional meaning beyond implying the ID targets a campaign for deletion, aligning with but not enhancing the schema. Baseline 3 is appropriate as the schema handles parameter documentation.
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 ('Delete') and resource ('a campaign'), specifying it's permanent. It distinguishes from siblings like 'pause_lead' or 'update_campaign_status' by indicating irreversible removal, but doesn't explicitly contrast with all deletion-related tools like 'delete_lead_from_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?
No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing campaign ID from 'get_campaign' or 'list_campaigns'), exclusions (e.g., not for paused campaigns), or comparisons to similar tools like 'delete_lead_from_campaign'.
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. 'Delete' implies a destructive mutation, but the description doesn't specify whether this action is reversible, what permissions are required, how it affects related data, or any rate limits. This leaves significant gaps for a tool that performs a deletion 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 a single, direct sentence with no unnecessary words, making it highly concise and front-loaded. Every word contributes to stating the tool's purpose efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity as a destructive operation with no annotations and no output schema, the description is insufficient. It lacks details on behavioral traits, error handling, return values, and differentiation from siblings, making it incomplete for safe and effective use by an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with clear parameter definitions for 'campaign_id' and 'lead_id'. The description doesn't add any additional semantic context beyond what the schema provides, such as format examples or interdependencies, so it meets the baseline for high schema coverage.
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 ('Delete') and the target ('a lead from a campaign'), which is specific and unambiguous. However, it doesn't distinguish this tool from similar siblings like 'unsubscribe_lead_from_campaign' or 'remove_campaign_email_accounts', which limits its 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. With siblings like 'unsubscribe_lead_from_campaign' and 'remove_campaign_email_accounts' available, there's no indication of the specific context, prerequisites, or exclusions for choosing this deletion tool over others.
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 implies a read-only operation ('Get details'), but doesn't specify permissions required, error handling (e.g., for invalid IDs), rate limits, or response format. For a tool with zero annotation coverage, this leaves critical behavioral traits undocumented.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('Get details of a specific campaign by ID'). There is no wasted verbiage, repetition, or unnecessary elaboration, making it optimally concise for its function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (single parameter, no output schema, no annotations), the description is incomplete. It lacks behavioral context (e.g., error cases, permissions), usage guidelines relative to siblings, and details on return values. Without annotations or output schema, the description should compensate more to be fully helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the single parameter 'campaign_id' documented as a number. The description adds no additional semantic context beyond what the schema provides (e.g., format examples, ID sourcing, or validation rules). According to scoring rules, baseline is 3 when schema coverage is high (>80%).
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 details') and resource ('specific campaign by ID'), making the purpose unambiguous. It distinguishes from siblings like 'list_campaigns' (which retrieves multiple campaigns) by specifying retrieval of a single campaign. However, it doesn't explicitly differentiate from other single-campaign tools like 'get_campaign_analytics'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a valid campaign ID), contrast with siblings like 'list_campaigns' for multiple campaigns or 'get_campaign_analytics' for performance data, or specify use cases (e.g., for editing vs. viewing).
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 this is a 'Get' operation, implying read-only behavior, but doesn't clarify if it requires specific permissions, has rate limits, returns real-time or cached data, or what the output format looks like (e.g., summary metrics). For a tool with no annotations, 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 a single, efficient sentence with zero wasted words. It's front-loaded with the core action ('Get') and resource ('campaign analytics summary'), making it easy to parse quickly. Every word earns its place by conveying essential purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of analytics tools and the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'top-level' entails (e.g., key metrics like opens, clicks), how the data is structured, or any limitations (e.g., date ranges, aggregation). For a tool that likely returns detailed data, this leaves the agent under-informed about what to expect.
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 input schema has 100% description coverage, with the single parameter 'campaign_id' documented as 'Campaign ID'. The description adds no additional semantic context about this parameter, such as where to find the ID or valid ranges. Since schema coverage is high, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.
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 'Get top-level campaign analytics summary' clearly states the verb ('Get') and resource ('campaign analytics summary'), making the purpose understandable. However, it doesn't distinguish this tool from sibling 'get_campaign_analytics_by_date' or 'get_campaign_statistics', which likely provide similar analytics with different scopes or details.
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_campaign_analytics_by_date' or 'get_campaign_statistics'. It lacks context about what 'top-level' means or when this summary is preferred over more detailed analytics, leaving the agent to guess based on tool names 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. It states this is a 'Get' operation (implying read-only), but doesn't mention authentication requirements, rate limits, error conditions, or what format the analytics data returns. For a data retrieval 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's appropriately sized for a straightforward data retrieval tool and gets directly to the point without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations, no output schema, and multiple sibling tools performing similar functions, the description is inadequate. It doesn't explain what 'analytics' includes, how results are structured, or how this differs from other campaign analytics tools. The agent would need to guess about the tool's behavior and output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with all three parameters clearly documented in the schema. The description adds minimal value beyond what's already in the schema - it mentions 'date range' which aligns with start_date and end_date parameters, but doesn't provide additional context about parameter interactions 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 verb 'Get' and resource 'campaign analytics' with the specific scope 'for a specific date range', making the purpose unambiguous. However, it doesn't distinguish this tool from its sibling 'get_campaign_analytics' (without date range), which could cause confusion about when to use each.
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 'get_campaign_analytics' or 'get_campaign_statistics'. 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. It states this is a 'Get' operation, implying read-only behavior, but doesn't clarify aspects like authentication requirements, rate limits, error handling, or what details are returned (e.g., account settings, status). This leaves significant gaps for a tool that likely involves sensitive account data.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words, making it highly concise and front-loaded. It directly states the tool's purpose without unnecessary elaboration, which is efficient for an AI agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of email account management and the lack of annotations and output schema, the description is insufficient. It doesn't explain what 'details' are returned (e.g., configuration, status), potential side effects, or error cases, leaving the agent with incomplete information for proper tool invocation in a real-world 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?
The input schema has 100% description coverage, with the 'account_id' parameter documented as 'Email account ID'. The description adds no additional semantic context beyond this, such as format examples (e.g., numeric ID) or where to find the ID. Given the high schema coverage, a baseline score of 3 is appropriate, as the schema adequately covers parameter meaning without extra help from the description.
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') and resource ('details of a specific email account'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'list_email_accounts' or 'update_email_account', which would require mentioning this retrieves a single account by ID rather than listing all accounts or modifying one.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. For example, it doesn't specify that this is for retrieving a single account by ID, as opposed to 'list_email_accounts' for multiple accounts or 'update_email_account' for modifications, 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'Get' implies a read-only operation, the description doesn't specify whether this requires authentication, what happens if the email isn't found (e.g., returns null vs. error), rate limits, or the format of returned 'lead details'. This is inadequate for a 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 extremely concise with a single, front-loaded sentence that directly states the tool's purpose without any wasted words. Every element ('Get', 'lead details', 'by email address') earns its place by contributing essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'lead details' includes (e.g., fields returned), error conditions, or behavioral aspects like idempotency. For a tool that presumably returns structured data, more context is needed to 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?
The schema description coverage is 100%, with the single parameter 'email' fully documented in the schema as 'Lead email address'. The description adds no additional parameter semantics beyond what's already in the schema, so it meets the baseline score of 3 for high schema coverage without adding 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 with a specific verb ('Get') and resource ('lead details'), and identifies the lookup mechanism ('by email address'). However, it doesn't explicitly differentiate this tool from potential siblings like 'get_lead_campaigns' or 'list_campaign_leads', which might also retrieve lead information through different mechanisms.
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 available (e.g., 'get_lead_campaigns', 'list_campaign_leads'), there's no indication of whether this is the primary method for retrieving lead details, if it's for single-record lookups, or what distinguishes it from other lead-related 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?
With no annotations provided, the description carries full burden but only states the basic action. It doesn't disclose behavioral traits such as whether this is a read-only operation, what format the campaigns are returned in, if there are pagination limits, or any authentication requirements. This is inadequate 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It is front-loaded and appropriately sized for its purpose, with zero waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'campaigns' entail, the return format, or any error conditions. For a tool in a complex server with many siblings, more context is needed to guide the agent 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?
The input schema has 100% description coverage, with the 'lead_id' parameter clearly documented. The description adds no additional semantic context beyond implying the parameter is used to fetch associated campaigns, so it meets the baseline score of 3 where the schema does the heavy lifting.
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 ('Get') and resource ('campaigns associated with a lead'), making the purpose understandable. It distinguishes from siblings like 'list_campaigns' by specifying lead association, though it doesn't explicitly contrast with 'list_campaign_leads' which might have similar 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 like 'list_campaign_leads' or 'get_campaign'. It simply states what it does without context about prerequisites, timing, or exclusions, leaving the agent to infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 statistics, implying a read-only operation, but doesn't mention authentication needs, rate limits, error conditions, or what the statistics include (e.g., metrics like emails sent, open rates). This leaves significant gaps for a tool that likely returns complex data.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. Every part ('Get warmup statistics', 'for an email account', 'last 7 days') contributes essential information, making it appropriately sized for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's likely complexity (returning statistics), no annotations, and no output schema, the description is incomplete. It doesn't explain what 'warmup statistics' entail, the format of the return data, or any behavioral traits like pagination or data freshness. This leaves the agent with insufficient context to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the single parameter 'account_id' fully documented in the schema. The description adds no additional parameter details beyond implying the account is for email. This meets the baseline of 3 since the schema does the heavy lifting, but the description doesn't enhance understanding of the parameter's role in warmup statistics.
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' and resource 'warmup statistics for an email account' with a specific time constraint 'last 7 days'. It distinguishes from siblings like 'get_email_account' or 'update_warmup_settings' by focusing on statistics rather than general account info or settings updates. However, it doesn't explicitly contrast with all potential sibling 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 'get_campaign_statistics' or 'get_campaign_analytics', nor does it mention prerequisites or exclusions. The time constraint 'last 7 days' implies a recency focus but doesn't specify when this tool is preferred over other analytics 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states it's a list operation, implying read-only behavior, but doesn't address critical aspects like permissions required, pagination, rate limits, error conditions, or what 'all' entails (e.g., whether it returns active/inactive accounts). This is inadequate for a tool with potential complexity in data retrieval.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with zero wasted words. It front-loads the core purpose ('List all email accounts') and efficiently specifies the context ('associated with a campaign'), making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete for a tool that likely returns a list of email accounts. It doesn't explain the return format (e.g., array of objects with fields like email, status), pagination, or error handling. For a read operation with potential data volume, this leaves significant gaps for an agent to 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 100%, with the single parameter 'campaign_id' clearly documented in the schema. The description adds no additional parameter semantics beyond implying the tool filters by campaign, which is already evident from the parameter name. This meets the baseline for high schema coverage but doesn't enhance 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 ('List all') and resource ('email accounts associated with a campaign'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_email_accounts' (which likely lists all email accounts regardless of campaign) or 'get_campaign' (which retrieves campaign details rather than associated accounts), 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. It doesn't mention prerequisites (e.g., needing an existing campaign), exclusions, or comparisons to siblings like 'list_email_accounts' or 'get_campaign', leaving the agent to infer usage context 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 the full burden of behavioral disclosure. It mentions pagination but doesn't specify rate limits, authentication needs, error handling, or what the output looks like (e.g., format of leads). 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('List all leads in a campaign') and includes essential detail ('with pagination') without any waste. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete. It doesn't explain the return values (e.g., lead details format), error cases, or behavioral constraints like rate limits. For a paginated list tool with 3 parameters, this leaves too much unspecified for reliable agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents the three parameters (campaign_id, offset, limit). The description adds no additional meaning beyond implying pagination use, which is already covered in the schema descriptions for offset and limit. Baseline 3 is appropriate as the schema does the heavy lifting.
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 ('List all leads') and resource ('in a campaign'), specifying the scope with pagination. It distinguishes from siblings like 'get_lead_by_email' or 'get_lead_campaigns' by focusing on campaign-specific listing, but doesn't explicitly differentiate from similar list tools like 'list_campaigns'.
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. For example, it doesn't mention when to choose this over 'get_lead_by_email' for individual leads or 'list_campaigns' for campaigns themselves, leaving usage context 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.
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 'pagination' but doesn't detail how pagination works, what the response format includes, or any limitations like rate limits or permissions required. This leaves significant gaps for a tool that likely returns a list of resources.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste, clearly front-loading the core functionality. It's appropriately sized for a simple list tool, making it easy to parse and understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete for a tool that likely returns a list of email accounts. It doesn't explain what data is included in the response, how errors are handled, or any behavioral nuances, leaving the agent with insufficient context for reliable use.
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 input schema has 100% description coverage, fully documenting the 'offset' and 'limit' parameters. The description adds no additional semantic context beyond implying pagination, which is already covered by the schema. This meets the baseline for high schema coverage without extra 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 verb ('List') and resource ('all email accounts'), making the purpose specific and understandable. However, it doesn't explicitly distinguish this tool from sibling tools like 'get_email_account' or 'list_campaign_email_accounts', 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, such as 'get_email_account' for single accounts or 'list_campaign_email_accounts' for campaign-specific accounts. It lacks context about prerequisites, exclusions, or typical use cases, offering only basic functional information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It implies a state change ('pause') but doesn't clarify if this is reversible, what permissions are required, how it affects campaign metrics, or what happens to scheduled communications. For a mutation 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is inadequate. It doesn't explain what 'pause' entails operationally, what the expected outcome is, or how it differs from similar tools. Given the complexity of lead management and rich sibling toolset, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both parameters clearly documented in the schema. The description adds no additional parameter context beyond implying that 'campaign_id' and 'lead_id' identify the target, which the schema already covers. Baseline 3 is appropriate when the schema does the heavy lifting.
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 resource ('a lead in a campaign'), making the purpose immediately understandable. It distinguishes from siblings like 'resume_lead' by specifying the opposite action, though it doesn't explicitly contrast with other lead management tools like 'delete_lead_from_campaign' or 'unsubscribe_lead_from_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?
No guidance is provided on when to use this tool versus alternatives like 'resume_lead', 'delete_lead_from_campaign', or 'unsubscribe_lead_from_campaign'. The description lacks context about prerequisites (e.g., lead must be active) or typical scenarios for pausing versus other actions.
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. 'Remove' implies a destructive mutation, but the description doesn't disclose whether this operation is reversible, what permissions are required, whether it affects campaign functionality, or what happens to the removed accounts. For a destructive 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that states the core functionality without unnecessary words. It's appropriately sized for a simple removal operation and gets straight to the point.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a destructive mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what happens after removal, whether there are side effects, what error conditions might occur, or what the tool returns. Given the complexity of campaign-email relationships and the lack of structured data, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters (campaign_id and email_account_ids) adequately. The description doesn't add any meaningful parameter context beyond what the schema provides, such as explaining what constitutes valid IDs or how the removal affects the campaign.
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 resources ('email accounts from a campaign'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'delete_campaign' or 'unsubscribe_lead_from_campaign' which also involve removal operations, 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. With siblings like 'delete_campaign' (removes entire campaigns) and 'unsubscribe_lead_from_campaign' (removes leads), there's clear potential for confusion about which removal operation to use, but the description offers no clarification.
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 state change (resuming), but doesn't disclose permissions needed, whether the action is reversible, rate limits, or what happens if the lead isn't paused. 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core action and target, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't cover behavioral aspects like side effects, error conditions, or return values, leaving significant gaps for an agent to operate safely and effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so parameters are documented in the schema. The description adds no additional meaning beyond implying 'resume' action, which aligns with the tool name but doesn't explain parameter interactions (e.g., how 'resume_lead_with_delay_days' affects timing). Baseline 3 is appropriate as the schema does the heavy lifting.
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 ('resume') and target ('a paused lead in a campaign'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'pause_lead' or 'unsubscribe_lead_from_campaign', which would require mentioning it's specifically for reversing a paused state rather than other lead status changes.
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., the lead must be paused), exclusions, or compare it to siblings like 'pause_lead' or 'unsubscribe_lead_from_campaign', leaving the agent to infer context from tool names 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 action ('Unsubscribe') but does not explain what this entails—whether it's a soft/hard removal, if it affects campaign analytics, requires specific permissions, or has side effects. 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It is front-loaded with the core action and resource, making it easy to parse quickly without unnecessary details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool performs a mutation (unsubscribing) with no annotations and no output schema, the description is incomplete. It lacks details on behavioral implications, success/error responses, or integration with sibling tools, which are critical for an agent to use it correctly in 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?
The input schema has 100% description coverage, with clear parameter descriptions ('Campaign ID', 'Lead ID'). The description adds no additional semantic context beyond what the schema provides, such as format examples or relationship details, so it meets the baseline for high schema coverage.
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 ('Unsubscribe') and the target ('a lead from a specific campaign'), providing a specific verb+resource combination. However, it does not explicitly distinguish this tool from its sibling 'unsubscribe_lead_globally', which handles global unsubscriptions versus campaign-specific ones.
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 the sibling 'unsubscribe_lead_globally' for global unsubscriptions or other related tools like 'delete_lead_from_campaign', leaving the agent without context for 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?
With no annotations provided, the description carries full burden but only states it 'updates' settings without disclosing behavioral traits like permission requirements, whether changes are reversible, rate limits, or error handling. It mentions the fields but not the consequences of updates.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the purpose and enumerates the main fields without unnecessary words. Every part earns its place by specifying the scope of updates.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a mutation tool with 8 parameters, the description is incomplete. It lacks details on behavioral context, return values, error cases, or how it fits with sibling tools, leaving significant gaps for agent understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so parameters are well-documented in the schema. The description lists key fields (timezone, days, hours, lead limits) which align with some parameters but adds minimal semantic value beyond what the schema already provides, meeting the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('update') and resource ('campaign schedule settings') with specific fields mentioned (timezone, days, hours, lead limits). It distinguishes from some siblings like 'update_campaign_settings' by focusing on schedule aspects, though not all alternatives are explicitly differentiated.
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 'update_campaign_settings' or 'update_campaign_status' is provided. The description implies usage for modifying schedule parameters but offers no context about prerequisites, exclusions, or specific 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. 'Update' implies a mutation, but it doesn't specify if this requires specific permissions, whether changes are reversible, or what the response looks like. It lacks details on rate limits, error handling, or side effects, leaving 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core action and includes helpful examples without any wasted words. It's appropriately sized for the tool's complexity and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with 8 parameters, no annotations, and no output schema, the description is incomplete. It lacks behavioral context (e.g., permissions, side effects), detailed usage guidelines, and output information, making it inadequate for safe and effective use by an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, so the schema already documents all 8 parameters with descriptions. The description adds minimal value by hinting at the scope ('general settings') and examples like 'tracking, unsubscribe text', but doesn't provide additional syntax, constraints, or usage details beyond what's in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Update') and resource ('campaign general settings'), with specific examples like 'tracking, unsubscribe text, etc.' that help distinguish it from siblings like update_campaign_schedule or update_campaign_status. However, it doesn't explicitly differentiate from all siblings (e.g., update_email_account), 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 update_campaign_schedule or update_campaign_status, nor does it mention prerequisites such as needing an existing campaign. It only states what the tool does, not when or why to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states what the tool does, not how it behaves. It doesn't disclose whether this is a destructive operation, what permissions are required, whether changes are reversible, what happens to active campaigns when paused/stopped, or what the response looks like. 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 a single, efficient sentence that gets straight to the point with no wasted words. It could be slightly improved by front-loading more critical information about behavioral aspects, but within its limited scope, it's appropriately concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool that changes campaign states with no annotations and no output schema, the description is insufficient. It doesn't explain the implications of status changes, error conditions, response format, or how this interacts with other campaign operations. Given the complexity of campaign management and the many sibling tools, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already fully documents both parameters. The description adds no additional parameter information beyond what's in the schema - it doesn't explain what 'START' means versus other statuses, or provide context about campaign_id format or sourcing. Baseline 3 is appropriate when schema does all the work.
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 'Update' and resource 'campaign status', specifying the exact status values (PAUSED, STOPPED, START). It distinguishes from siblings like update_campaign_settings or update_campaign_schedule by focusing specifically on status changes, though it doesn't explicitly name these alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like pause_lead, resume_lead, or other campaign update tools. The description lacks context about prerequisites, timing considerations, or what happens when changing between specific statuses.
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 operation ('update') but doesn't disclose critical traits like authentication requirements, whether changes are reversible, rate limits, or error conditions. The mention of 'message limits' hints at constraints but lacks specifics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose. It uses parentheses to compactly list example settings without unnecessary elaboration. However, it could be slightly more structured by separating core function from examples.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex mutation tool with 12 parameters, no annotations, and no output schema, the description is inadequate. It lacks information on behavioral traits, error handling, side effects, and output format. The high parameter count and mutation nature demand more contextual guidance than provided.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all 12 parameters. The description adds marginal value by grouping parameters into categories like 'SMTP/IMAP credentials' and 'message limits', but doesn't explain interactions (e.g., if 'type' affects which other parameters are relevant) or provide usage context beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'update' and the resource 'email account settings', with specific examples like SMTP/IMAP credentials and message limits. It distinguishes from sibling tools like 'create_email_account' by focusing on updates rather than creation, though it doesn't explicitly contrast with other update tools like 'update_campaign_settings'.
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., needing an existing email account ID), differentiate from similar update tools (e.g., 'update_campaign_settings'), or specify use cases like correcting misconfigured accounts versus changing limits.
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 'Update' implying a mutation, but does not disclose behavioral traits like required permissions, whether changes are reversible, rate limits, or what happens to unspecified settings. This is inadequate 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, with zero waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral aspects, error handling, or return values, leaving significant gaps for an agent to understand the tool's full 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 100%, so the schema fully documents all parameters. The description does not add meaning beyond the schema, such as explaining interactions between parameters or providing examples. Baseline 3 is appropriate as the schema handles the heavy lifting.
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 ('Update') and resource ('warmup settings for an email account'), making the purpose understandable. However, it does not differentiate this tool from sibling tools like 'update_email_account' or 'update_campaign_settings', which could involve overlapping concepts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, such as 'update_email_account' or 'update_campaign_settings', nor does it mention prerequisites or exclusions. 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states it's a list operation but doesn't mention if it's paginated, sorted, or filtered, nor does it describe the return format or any rate limits. This leaves significant gaps for a tool that likely returns multiple items.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded and wastes no space, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (listing multiple items) and lack of annotations or output schema, the description is insufficient. It doesn't explain what data is returned, how results are structured, or any behavioral aspects like pagination, leaving the agent with incomplete information.
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 inputs. The description doesn't need to add parameter details, and it correctly implies no filtering options (e.g., 'all campaigns'), aligning with the empty 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 ('List') and resource ('all campaigns in your Smartlead account'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get_campaign' or 'list_campaign_email_accounts', 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 'get_campaign' (for specific campaigns) or 'list_campaign_email_accounts' (for related resources). It lacks context about prerequisites or typical use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 'bulk operation' but doesn't disclose critical behavioral traits: whether this requires admin permissions, if it's idempotent, what happens on partial failures, rate limits, or expected outcomes. 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It's front-loaded with the core purpose ('Reconnect all failed email accounts') and adds clarifying context ('bulk operation') concisely.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a bulk mutation operation), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what 'reconnect' entails, success/failure responses, or side effects. For a tool that likely modifies system state, more detail is needed.
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 adds no parameter-specific information, which is appropriate here. Baseline is 4 for zero parameters as no compensation is needed.
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 ('Reconnect') and target ('all failed email accounts'), specifying it's a bulk operation. It distinguishes from siblings like 'update_email_account' or 'create_email_account' by focusing on reconnection rather than creation/modification. However, it doesn't explicitly differentiate from potential similar tools like 'resume_lead' which might handle related states.
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., only when accounts are in a 'failed' state), exclusions, or related tools like 'update_email_account' for individual fixes. The context is implied but not explicit.
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 maximum lead limit (100 per request), which is useful operational context, but fails to disclose critical behavioral traits: whether this is a mutating operation (implied but not stated), what permissions are required, how duplicates are handled, whether leads are validated, or what happens on partial failures. For a write operation with complex parameters, 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise - a single sentence that communicates the core purpose and a key operational constraint. Every word earns its place with zero redundancy. The information is front-loaded and immediately actionable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutating tool with 3 parameters (including complex nested objects), no annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns, error conditions, side effects, or important behavioral constraints beyond the lead limit. The agent would need to guess about success/failure responses, validation rules, and integration consequences.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds minimal value beyond the schema - it implies the 'lead_list' parameter accepts leads and mentions the 100-item limit, but doesn't explain the semantics of 'settings' parameters or clarify required fields beyond what's in the schema. This meets the baseline for high schema coverage.
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 leads') and target resource ('to a campaign'), making the purpose immediately understandable. It distinguishes from sibling tools like 'create_campaign' or 'delete_lead_from_campaign' by focusing on adding leads to existing campaigns. However, it doesn't explicitly differentiate from similar tools like 'list_campaign_leads' or 'unsubscribe_lead_from_campaign' beyond the verb choice.
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 add leads to an existing campaign, but provides no explicit guidance on when to use this versus alternatives like 'create_campaign' (for new campaigns) or 'update_campaign_settings' (for modifying campaigns). The maximum lead limit (100) offers some operational constraint, but doesn't address strategic selection among 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the create/update logic and A/B testing support, but doesn't address critical behavioral aspects like whether this is a destructive operation (overwrites existing sequences), what permissions are required, rate limits, error handling, or what happens when sequences conflict. For a mutation tool with complex nested parameters, 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 extremely concise (two sentences) with zero wasted words. The first sentence states the core purpose and create/update logic, while the second adds the A/B testing capability. Every sentence earns its place, and the information is front-loaded with the most critical details first.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex mutation tool with 3 parameters (including deeply nested objects), no annotations, and no output schema, the description is inadequate. It doesn't explain what the tool returns, error conditions, side effects, or behavioral constraints. While the schema provides parameter documentation, the description fails to compensate for the lack of annotations and output schema, leaving the agent with insufficient context for safe and effective usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds minimal value beyond what's in the schema - it clarifies the ID parameter's role in create/update decisions and mentions A/B testing, but doesn't provide additional semantic context about parameter relationships, constraints, or usage patterns beyond what's already in the structured schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('Create or update email sequences for a campaign') and distinguishes it from siblings by focusing on sequence management rather than campaign creation, lead management, or analytics. It explicitly mentions A/B testing support, which is unique among the listed sibling tools.
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 on when to use this tool (create vs. update based on ID presence) and mentions A/B testing capabilities. However, it doesn't explicitly state when to use alternatives like 'create_campaign' for initial campaign setup or 'update_campaign_settings' for other campaign modifications, leaving some sibling differentiation implicit rather than explicit.
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 ('Unsubscribe') but does not disclose behavioral traits such as whether this is irreversible, requires specific permissions, affects lead status in other tools, or has rate limits. The description is minimal and lacks critical operational context 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that is front-loaded with the core action. There is no wasted text, making it highly concise and well-structured for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a mutation tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral implications, success/failure responses, or integration with sibling tools. For a tool that performs a global unsubscribe action, more context is needed to ensure safe and correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the parameter 'lead_id' documented in the schema. The description does not add any meaning beyond what the schema provides, such as format examples or constraints. With high schema coverage, the baseline score of 3 is appropriate as the schema handles parameter documentation adequately.
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 ('Unsubscribe') and resource ('a lead from all campaigns globally'), distinguishing it from the sibling tool 'unsubscribe_lead_from_campaign' by emphasizing the global scope versus campaign-specific scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by specifying 'from all campaigns globally', suggesting this tool is for broad opt-outs rather than targeted ones. However, it does not explicitly state when to use this versus the sibling tool 'unsubscribe_lead_from_campaign' 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.

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