bd-crm-analytics

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose: economics metrics, conversion funnel, forecast, velocity/cycle, win rate, leads listing, and metadata discovery. No overlap in functionality.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern using 'get_' for metrics and 'list_' for data retrieval. The naming is uniform and predictable.
Tool Count5/5
Seven tools is appropriate for a CRM analytics server, covering key analytic dimensions without being overwhelming or too sparse.
Completeness5/5
The tool set covers the primary analytics needs: economics, funnel, forecast, velocity, win rates, plus leads listing and metadata. No obvious gaps for the intended purpose.
Average 3.9/5 across 7 of 7 tools scored. Lowest: 3.3/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 6 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
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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?
With no annotations, the description should disclose behavioral traits. It only mentions a snapshot of current pipeline positions but fails to describe whether the operation is read-only, any side effects, or limitations like data freshness or pagination.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences. The first sentence front-loads the main purpose and key metrics, and the second adds context without waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description explains the output includes per-step conversion %, drop-off, and biggest-leak stage, which is helpful but lacks specifics on the exact structure or fields returned. Given no output schema, more detail on output format would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All three parameters are described in the schema (100% coverage). The description mentions custom and preset ranges, but this adds little beyond the schema's parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it provides a stage-conversion funnel with per-step conversion percentages, drop-off, and the biggest-leak stage. It distinguishes itself from sibling tools like get_forecast and get_win_rate by focusing on pipeline positions and conversion steps.
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 lacks explicit guidance on when to use this tool versus alternatives. No context on prerequisites, exclusions, or best-fit scenarios is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It states the tool returns economic metrics but does not explicitly declare the operation type (read-only), mention side effects, auth needs, or rate limits. The behavior is partially transparent through the listed outputs.
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 sentence that efficiently conveys the key outputs. It is concise with no redundancy, though it could benefit from slight structural separation for readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 4 parameters, no output schema, and no annotations, the description provides a reasonable overview but lacks details on return format, required parameters (none required), and how the filters affect results. It is adequate but not fully self-contained.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with each parameter having a description. The tool description adds minimal extra meaning beyond the schema; it mentions 'segment' which aligns with the 'dimension' parameter but does not elaborate on usage or constraints. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as providing 'connects economics' metrics like overall connects-per-win, segmented ROI data, and boosted-vs-not comparison, using a specific verb (implied 'get') and resource. It distinguishes from sibling tools like get_conversion_funnel or get_forecast by the focus on connects economics.
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 listing the output metrics, but does not explicitly state when to use this tool versus alternatives or provide any contextual guidance. No exclusions or when-not-to-use information is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description notes deal value is an estimate but omits details on data freshness, recalculation logic, or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences front-loading key functionality with zero unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, description hints at per-stage breakdown; covers essential purpose but could clarify default range behavior.
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 provides full parameter descriptions (100% coverage); description adds no extra meaning beyond what schema already offers.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool computes a weighted pipeline forecast with per-stage breakdown, distinguishing it from siblings like win rate or conversion funnel.
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; lacks context on prerequisites or exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It discloses the output structure (velocity, inputs, cycle length breakdowns) but does not mention behavioral traits like being read-only, idempotent, or any permissions needed. It is adequate but not rich.
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, well-structured sentence with no fluff. It efficiently conveys the core output and breakdown dimensions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given moderate complexity, the description covers the return structure adequately without needing an output schema. It explains what metrics are returned and the breakdowns. Leaves out only minor details like data format or freshness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and each parameter is described in the schema. The description adds no additional meaning beyond what the schema provides (date range filters). Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns 'Sales velocity ($/day) with its four inputs' and 'average cycle length broken down by Profile and by Country'. The verb 'get' plus the specific resource 'velocity_and_cycle' is precise, and the breakdown distinguishes it from sibling tools like 'get_win_rate' or 'get_conversion_funnel'.
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 sales velocity and cycle analysis but lacks any explicit guidance on when to use this tool versus alternatives (e.g., when to prefer this over get_win_rate or get_forecast). No exclusions or context dependency mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses read-only and paginated behavior, which are key traits. However, with no annotations provided, the description carries full burden. It does not mention rate limits, authentication requirements, sorting order, or error conditions, leaving some behavioral aspects implicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences with no filler. The first sentence captures the core purpose, the second lists filter capabilities, and the third provides cross-reference. Every sentence adds unique value and the front-loading is optimal.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 8 optional parameters, no output schema, and no annotations, the description covers the tool's purpose, read-only nature, pagination, filters, and where to get valid values. It does not detail pagination parameters (but schema covers them) or explicitly state the output format beyond 'key fields + custom fields', which is sufficient for a list tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by summarizing filter categories (state, profile, country, date range) and directing to list_metadata for valid values, which goes beyond individual parameter 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 lists BD leads with key fields and custom fields, specifies read-only and paginated behavior, and enumerates filter dimensions. It is distinct from all sibling tools (analytics reports and metadata lookup), so there is no ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: use this tool to list leads with pagination and filters. It recommends list_metadata for valid filter values, which is helpful. However, it does not explicitly exclude any scenarios or compare with alternatives; since no sibling does the same thing, this is a minor gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool lists metadata, which implies a read-only operation, but it does not explicitly confirm no side effects, authentication requirements, or rate limits. For a simple listing tool, this is adequate but lacks explicit transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence that immediately states the action and resource. It is front-loaded with the most important information and contains no fluff. Every word contributes meaning, making it highly concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters and no output schema, the description adequately explains what the tool does and its purpose (discover filters). However, it does not describe the output format or any potential limits. For a simple metadata tool, this is sufficient but just shy of fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and schema coverage is 100% (empty schema). The description adds no parameter information because none exist. According to guidelines, 0 parameters gives a baseline of 4. The description does not need to compensate for missing parameter details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'List' and the resource: 'available custom fields (with their options) and pipeline states'. It explicitly states that these are valid values for filtering, distinguishing it from sibling tools like list_leads which list leads, not metadata. The instruction 'Call this first to discover filters' further clarifies its unique role.
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 a clear when-to-use directive: 'Call this first to discover filters.' This implies it should be used before utilizing filter parameters in other tools. However, it does not explicitly mention when not to use it or provide alternatives, which prevents a top score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It explains the slicing behavior and output structure (leads, wins, closed, win %), though it omits details like read-only nature or rate limits. This is adequate but not exhaustive.
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, well-structured sentence. It front-loads the purpose and efficiently conveys the two main use cases without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Without an output schema, the description hints at the return format (leads, wins, closed, win %). For a 4-param tool with no required parameters, this is fairly complete, though it could mention default behavior or typical usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (all params described). The description adds significant value for 'dimension' by explaining the difference between 'bd' and other values. For date parameters, it adds no extra meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates win rate for the BD Leads pipeline and distinguishes two modes: dimension='bd' gives overall and per-rep rates, while other dimensions slice by field. This specificity distinguishes it from sibling tools like get_conversion_funnel.
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 explains the effect of different dimension values, providing clear context for when to use each. However, it does not explicitly compare to sibling tools or state when not to use this tool, leaving a minor gap.
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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