FeedMob MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Every tool has a clearly distinct purpose targeting specific resources (campaigns, clients, metrics, etc.) with no overlap. The 'get_' tools retrieve single entities by ID, while 'list_' tools return collections with filters, creating a clean separation. An agent can easily distinguish between tools like get_campaign and list_campaigns based on whether they need details or a filtered list.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern with perfect uniformity. The 'get_' prefix is used for retrieving single entities, and 'list_' for collections, applied consistently across all resources (campaigns, clients, partners, etc.). This predictable naming makes it easy for agents to infer tool purposes and navigate the set.
Tool Count4/5
With 18 tools, the count is slightly high but reasonable for a comprehensive advertising/campaign management domain. It covers multiple resource types (campaigns, clients, partners, playbooks, etc.) with both detail and listing operations, avoiding bloat. A minor reduction might streamline it, but each tool earns its place by serving a distinct function.
Completeness4/5
The tool set provides strong coverage for a FeedMob advertising platform, including core CRUD-like operations (get and list) for key entities like campaigns, clients, and partners. Minor gaps exist, such as missing update/delete tools or campaign creation, but agents can work around these for read-heavy use cases. The inclusion of metrics, documents, and playbooks adds useful breadth.
Average 3/5 across 18 of 18 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
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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 this is a 'Get' operation, implying read-only behavior, but doesn't confirm if it's safe, whether it requires authentication, what happens with invalid IDs, or any rate limits. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words. It's front-loaded with the core purpose and efficiently conveys the essential information. Every part of the sentence earns its place, making it highly concise and well-structured.
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 retrieves 'detailed information'. It doesn't specify what details are returned, potential error cases, or how it differs from list operations. For a read operation with no structured output documentation, 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 description adds minimal semantic context beyond the input schema, which has 100% coverage for the single parameter 'id'. It mentions 'by ID', reinforcing the schema's description of 'The campaign ID', but doesn't provide additional details like format examples or constraints. With high schema coverage, the baseline is 3, and the description doesn't significantly enhance parameter 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 tool's purpose: 'Get detailed information about a specific campaign by ID.' It specifies the verb ('Get'), resource ('campaign'), and key constraint ('by ID'). However, it doesn't explicitly differentiate from sibling tools like 'list_campaigns' beyond the singular vs. plural naming, which is why it doesn't reach a perfect 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'list_campaigns' for browsing campaigns or clarify that this is for retrieving details of a known campaign ID. Without any context on prerequisites or exclusions, the agent must infer usage from the name and description alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states this is a read operation ('Get detailed information'), but doesn't mention authentication requirements, rate limits, error conditions, or what format the detailed information will be in. For a 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 simple lookup tool and front-loads the essential information 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 and no output schema, the description is insufficiently complete. It doesn't explain what 'detailed information' includes, what format it returns, or any behavioral aspects like error handling. Given the lack of structured data elsewhere, the description should provide more context about the tool's operation 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%, so the schema already documents the single parameter 'legacy_id' completely. The description adds no additional parameter semantics beyond what's in the schema, which is acceptable but not additive. The baseline of 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 verb ('Get detailed information') and resource ('about a specific click URL by legacy ID'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'list_click_urls', which would be needed for a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'list_click_urls' or other get_* tools. It mentions 'by legacy ID' but doesn't explain when this identifier is appropriate or what prerequisites might exist for using it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states this is a read operation ('Get detailed information'), which implies it's non-destructive, but doesn't cover aspects like authentication requirements, rate limits, error handling, or what 'detailed information' includes. 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 directly states the tool's purpose without unnecessary 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?
Given the lack of annotations and output schema, the description is incomplete for a tool that presumably returns detailed app data. It doesn't specify what information is included (e.g., version, developer, ratings), how errors are handled, or any prerequisites. For a tool with no structured output documentation, this leaves the agent with insufficient 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 description adds minimal value beyond the input schema, which has 100% coverage for the single parameter 'id'. It mentions 'by ID', reinforcing the schema's description, but doesn't provide additional context like ID format, examples, or where to find IDs. With high schema coverage, the baseline score of 3 is appropriate.
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 detailed information') and resource ('about a specific mobile app by ID'), making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'list_mobile_apps' or 'get_client', which could help an agent choose between them more effectively.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'list_mobile_apps' for listing apps or 'get_client' for client details, leaving the agent to infer usage 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. It states it 'gets' information, implying a read operation, but lacks details on permissions, rate limits, error handling, or what 'detailed information' entails. For a tool with zero annotation coverage, this is insufficient behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
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 appropriately sized and front-loaded, directly stating the tool's purpose 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?
Given the tool's simplicity (1 parameter, 100% schema coverage) but lack of annotations and output schema, the description is incomplete. It doesn't explain what 'detailed information' includes or potential behavioral aspects like authentication needs, leaving gaps for an AI 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?
The description mentions the parameter 'ID' but adds no meaning beyond what the input schema provides, which has 100% coverage with a clear description for 'id'. With high schema coverage, the baseline is 3, as the description doesn't compensate with extra context like ID format or examples.
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 ('detailed information about a specific partner by ID'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_partners' or 'get_client', which would require mentioning it retrieves a single partner's details rather than a list or different entity type.
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 siblings like 'list_partners' for multiple partners or 'get_client' for different entities, nor does it specify prerequisites such as needing a partner ID or context for retrieval.
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 'Get' implies a read operation but lacks details on permissions, error handling, rate limits, or response format. For a tool with no annotations, this is insufficient behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with zero wasted words. It's front-loaded with the core action and resource, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
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 what 'full content' entails, potential return values, or error cases. For a tool with these gaps, more context is needed 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%, so the input schema already documents the 'id' parameter. The description adds no additional meaning beyond what the schema provides, such as format examples or constraints, meeting 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 verb 'Get' and resource 'full content of a specific playbook item', making the purpose understandable. However, it doesn't differentiate from sibling tools like 'get_playbook' or 'list_playbooks', which likely retrieve different scopes of playbook data, so it misses 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, context, or exclusions, leaving the agent to infer usage from the name alone without explicit direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool lists campaigns with filters but fails to describe key behaviors such as pagination, sorting, default limits, error handling, or what the output looks like (e.g., list format, fields included). This is a significant gap for a listing tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded with the core purpose in the first sentence, followed by a clarifying definition. Both sentences earn their place by stating the action and resource context efficiently, with no redundant or verbose language.
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 (6 parameters, no output schema, no annotations), the description is incomplete. It lacks details on output format, behavioral traits like pagination, and usage guidelines compared to siblings. While the schema covers parameters well, the description doesn't address other critical aspects needed for effective tool invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all 6 parameters with descriptions and defaults. The description adds no parameter-specific information beyond mentioning 'optional filters' generically. This meets the baseline of 3 since the schema does the heavy lifting, but the description doesn't compensate or enhance understanding of the parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('campaigns') with a brief definition of what campaigns are. It distinguishes the tool's purpose from siblings like 'get_campaign' (singular retrieval) by focusing on listing with filters, but doesn't explicitly differentiate from other list tools like 'list_clients' or 'list_partners' beyond the resource type.
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. It doesn't specify scenarios for filtering (e.g., when to use client_id vs. partner_id) or compare it to sibling tools like 'get_campaign' for single-campaign retrieval, 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool lists documents and supports filtering, but doesn't describe what 'list' entails (e.g., pagination, format, sorting), permissions required, rate limits, or error conditions. For a read operation with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('List documents associated with clients') and briefly mentions filtering capabilities. There's no wasted text, though it could be slightly more structured (e.g., separating purpose from options).
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 with three parameters and read functionality. It lacks details on return values, pagination, error handling, and usage context. While the purpose is clear, the description doesn't compensate for the missing structured information, leaving the agent with insufficient guidance.
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 input schema fully documents all three parameters. The description adds minimal value beyond the schema by mentioning the filterable fields (client ID, title, category), but doesn't provide additional context like default behaviors or interaction between filters. 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 verb ('List') and resource ('documents associated with clients'), making the purpose immediately understandable. It distinguishes from siblings like 'list_clients' or 'list_partner_documents' by specifying the client-document relationship, though it doesn't explicitly contrast with them. The description is specific but lacks explicit sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It mentions filtering capabilities but doesn't specify prerequisites, context, or exclusions. With sibling tools like 'list_clients' and 'list_partner_documents' available, there's no indication of when this tool is preferred or how it relates to them.
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 returns (client names, IDs, legacy IDs) but lacks critical behavioral details: pagination behavior, default sorting, rate limits, authentication requirements, or whether this is a read-only operation. For a list tool with no annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that covers purpose, optionality, and return values. It's appropriately sized for a list tool, though it could be slightly more structured by separating purpose from return details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a list tool with 3 parameters (fully documented in schema) and no output schema, the description is minimally adequate. It covers what the tool does and what it returns, but lacks behavioral context (pagination, sorting, limits) and sibling differentiation. With no annotations, it should do more to compensate.
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 three parameters. The description adds no parameter-specific semantics beyond mentioning 'optional filters' generically. Baseline 3 is appropriate when the schema does all 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 verb ('List') and resource ('clients'), and mentions optional filters and return values. However, it doesn't explicitly differentiate from sibling tools like 'get_client' (singular) or 'list_client_documents', leaving some ambiguity about when to choose this specific list operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'get_client' or other list tools. It mentions optional filters but doesn't specify scenarios where filtering is appropriate or when to prefer this over other client-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 for behavioral disclosure. It states the tool lists mobile apps with optional filters but doesn't mention whether this is a read-only operation, if it requires authentication, what the return format looks like, or any rate limits. For a tool with zero annotation coverage, this is inadequate for safe invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single sentence that efficiently conveys the core functionality. There's no wasted language, and it's appropriately 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?
Given the tool has no annotations, no output schema, and the description lacks behavioral details, this is incomplete for safe agent use. While the schema covers parameters well, the description doesn't compensate for missing context about the operation's safety, return values, or usage boundaries.
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%, meaning all parameters are documented in the schema. The description adds minimal value by mentioning 'optional filters' but doesn't provide additional context beyond what the schema already specifies for each parameter. 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 verb ('List') and resource ('mobile apps'), and mentions optional filtering capability. However, it doesn't specifically differentiate this tool from sibling tools like 'get_mobile_app' or other list tools, which would require a more specific scope or distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'get_mobile_app' or other list tools. It mentions optional filters but doesn't specify scenarios or prerequisites for usage, leaving the agent to infer context without explicit direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states this is a 'Get' operation, implying it's read-only, but doesn't clarify aspects like authentication requirements, rate limits, error handling, or what 'detailed information' includes beyond 'list of items.' For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
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 detailed information about a playbook') and adds a useful detail ('including its list of items'). There's no wasted wording, making it appropriately sized for a simple retrieval tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (1 parameter, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on usage context, behavioral traits, and output specifics. With no output schema, the description doesn't explain return values, which is a gap, but the simplicity of the tool keeps it from being severely incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the single parameter 'id' documented as 'The playbook ID or slug.' The description doesn't add any meaning beyond this, such as examples or constraints on the ID format. According to the rules, when schema coverage is high (>80%), the baseline score is 3 even with no param info in 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 tool's purpose: 'Get detailed information about a playbook, including its list of items.' It specifies the verb ('Get') and resource ('playbook') with additional detail about what information is retrieved. However, it doesn't explicitly differentiate from sibling tools like 'get_playbook_item' or 'list_playbooks', which would be needed for a score of 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. There are multiple sibling tools that might overlap (e.g., 'get_playbook_item' for individual items, 'list_playbooks' for listing playbooks), but the description doesn't mention any of them or specify contexts like retrieving a specific playbook by ID versus browsing all playbooks.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the tool lists URLs but doesn't disclose behavioral traits like whether it requires authentication, has rate limits, returns paginated results, or what format the output takes. For a list operation with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the key information: action, resource, and purpose. There is no wasted text, and it directly communicates the tool's function 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?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the output looks like (e.g., list format, fields included), any dependencies, or error conditions. For a tool with no structured metadata, the description should provide more context about behavior and results to be fully helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameters need documentation. The description adds value by specifying the resource type ('click URLs/tracking links') and context ('campaign attribution'), which provides semantic clarity beyond the empty schema. This compensates adequately for the lack of parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('click URLs/tracking links') with a specific purpose ('used for campaign attribution'). It distinguishes from siblings like 'get_click_url' (singular) by indicating it returns multiple items. However, it doesn't explicitly differentiate from other list tools like 'list_campaigns' beyond the resource type.
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, context for campaign attribution, or when to choose this over other list tools like 'list_campaigns'. The agent must infer usage solely from the tool name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions listing documents but fails to describe key traits like pagination behavior, rate limits, authentication needs, or what 'associated with partners' entails (e.g., ownership vs. sharing). This leaves significant gaps for an agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized for a listing tool and front-loaded with the core functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a listing tool with no annotations and no output schema, the description is minimally adequate but incomplete. It covers the basic purpose but lacks behavioral details (e.g., response format, error handling) that would help an agent use it effectively, especially given the absence of structured safety or output information.
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 three parameters. The description adds no additional parameter semantics beyond what's in the schema, such as explaining how filters combine or default behaviors. 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 ('List') and resource ('documents associated with partners'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'list_client_documents' or 'list_partners' beyond the resource focus, 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 'list_client_documents' or 'list_partners', nor does it mention prerequisites such as authentication or context requirements. It merely states what the tool does without operational context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'List all' implies a read-only operation, it doesn't specify whether this requires authentication, how results are returned (e.g., pagination, format), or any rate limits. This leaves significant gaps for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states what the tool does without any wasted words. It's appropriately sized and front-loaded, making it easy to understand at a glance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is adequate as a basic listing tool. However, it lacks details on output format or behavioral context, which would be helpful since there's no output schema. It meets minimum viability but has clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so the schema fully documents the lack of parameters. The description appropriately doesn't add parameter details, maintaining focus on the tool's purpose. With zero parameters, the baseline is 4, as there's nothing to compensate for.
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 ('partner categories with their IDs'), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling tools like 'list_partners' or 'list_partner_documents', which would require a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With sibling tools like 'list_partners' and 'list_partner_documents' available, there's no indication of when this specific listing is appropriate or what distinguishes it from other listing tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions 'optional filters' but doesn't disclose behavioral traits such as pagination, rate limits, authentication requirements, or what happens when no filters are applied (e.g., returns all partners). For a list tool with no annotation coverage, this leaves significant gaps in understanding its operation and constraints.
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 partners') and adds clarifying details ('vendors/ad networks') and functionality ('optional filters') without waste. Every word contributes to understanding, making it appropriately sized and well-structured.
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 with four parameters. It doesn't explain return values (e.g., format of the list, fields included), error conditions, or behavioral aspects like pagination. For a list tool, this leaves the agent with insufficient context to use it effectively beyond basic filtering.
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 four parameters. The description adds minimal value beyond the schema by noting 'optional filters,' but doesn't provide additional context like default behaviors (e.g., 'status' defaults to 'running') or interactions between parameters. Baseline 3 is appropriate as the schema handles most of the 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 verb ('List') and resource ('partners'), with additional clarification about what partners are ('vendors/ad networks'). It distinguishes the tool from sibling 'get_partner' by indicating it lists multiple partners rather than retrieving a single one. However, it doesn't explicitly differentiate from other list tools like 'list_partner_categories' beyond the resource name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage through 'optional filters,' suggesting this tool is for retrieving partners with specific criteria. It doesn't provide explicit guidance on when to use this versus alternatives like 'get_partner' (for single partner) or 'list_partner_categories' (for categories), nor does it mention prerequisites or exclusions. The context is clear but lacks comparative direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It states this is a listing operation but doesn't disclose behavioral traits like pagination, sorting, default limits, error conditions, authentication requirements, or rate limits. The mention of 'accessible to the current user' hints at permission-based filtering but lacks detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately brief (two sentences) and front-loaded with the core functionality. The second sentence provides useful context about what playbooks are without being redundant. Every sentence adds value, though it could be slightly more structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple listing tool with one optional parameter and no output schema, the description covers basic purpose but lacks completeness regarding behavioral aspects. Without annotations or output schema, it should ideally describe response format, pagination, or error handling to be fully complete for 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 already documents the single parameter 'name_cont' with its filtering purpose. The description doesn't add any parameter-specific information beyond what's in the schema, maintaining the baseline score 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 ('List') and resource ('playbooks accessible to the current user'), with additional context about what playbooks are ('guides and documentation'). It distinguishes from siblings like 'get_playbook' (singular retrieval) by specifying listing functionality, though it doesn't explicitly contrast with other list_* tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving multiple playbooks rather than single items (contrasting with 'get_playbook'), but doesn't provide explicit when-to-use guidance, alternatives for different filtering needs, or prerequisites. It mentions 'accessible to the current user' which gives some context about access scope.
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 'List all pods' implies a read-only operation, it doesn't address important behavioral aspects like pagination, rate limits, authentication requirements, or what 'all' means in practice (e.g., scope limitations). For a list operation 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 perfectly concise with two sentences that each add value. The first sentence states the core functionality, and the second provides helpful domain context about what pods are. There's zero wasted verbiage or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, no output schema), the description is minimally adequate. However, the lack of annotations means the description should provide more behavioral context (like pagination or scope limitations) for a complete understanding. The description covers the basic purpose but leaves gaps in usage and behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, earning a baseline score of 4 for this dimension since it doesn't need to compensate for any schema gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('List') and resource ('pods'), and provides additional context about what pods are ('organizational units that group clients and team members'). However, it doesn't explicitly differentiate this tool from sibling tools like 'list_clients' or 'list_partners', which would require a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, limitations, or relationships with sibling tools like 'list_clients' (which might be related to pods). This leaves the agent with insufficient context for optimal tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves 'detailed information', but does not specify what details are included, whether authentication is required, potential error conditions, or rate limits. This leaves significant gaps in understanding the tool's behavior beyond the basic read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that efficiently conveys the core purpose without unnecessary words. It is front-loaded and wastes no space, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read tool with one parameter and no output schema, the description is minimally adequate. It covers the basic purpose but lacks details on return values, error handling, or behavioral traits. Without annotations or an output schema, the description should provide more context to be fully helpful, but it meets the minimum for a straightforward lookup tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with the 'id' parameter fully documented in the schema. The description adds no additional semantic context beyond what the schema provides, such as format examples or constraints. Given the high schema coverage, a baseline score of 3 is appropriate, as the description does not compensate but also does not 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 clearly states the verb ('Get') and resource ('detailed information about a specific client'), making the purpose evident. However, it does not explicitly differentiate from sibling tools like 'list_clients', which retrieves multiple clients rather than a single one by ID, leaving some ambiguity in 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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by specifying 'by ID', suggesting it's for retrieving a single client when the ID is known. However, it lacks explicit guidance on when to use this versus alternatives like 'list_clients' or other sibling tools, leaving the agent to infer context without clear exclusions or named alternatives.
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 return format ('time-series suitable for charting') and date range scope, but fails to address critical aspects like rate limits, authentication needs, data freshness, or error handling for a tool with 9 parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly concise with two sentences that are front-loaded and waste no words. Every sentence directly contributes to understanding the tool's core functionality without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (9 parameters, no output schema, no annotations), the description is incomplete. It adequately explains the basic operation but lacks guidance on usage context, behavioral constraints, and output details that would help an agent use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all 9 parameters. The description adds minimal value beyond the schema by implying date-range filtering and metric selection, but doesn't provide additional context about parameter interactions or business logic.
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 ('Get aggregated daily metrics') and resource ('as a time-series suitable for charting'), distinguishing it from sibling tools that focus on retrieving individual entities or lists rather than aggregated metrics over time.
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 sibling tools (e.g., get_campaign, list_campaigns) or other metric-retrieval methods. It lacks context on prerequisites, exclusions, or comparative use cases.
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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