revenue-enablement-mcp

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose in the sales enablement domain, from account planning to win/loss analysis, with no overlapping functionality.
Naming Consistency4/5
All names use snake_case with descriptive keywords, though the suffix pattern varies (e.g., _builder, _kit, _generator), which is still predictable and readable.
Tool Count5/5
12 tools is well-scoped for a sales enablement server, covering the full pipeline without being overwhelming or too sparse.
Completeness4/5
The tools cover major sales enablement workflows (planning, discovery, proposals, analysis) with only minor gaps like lead scoring or CRM integration.
Average 3.3/5 across 12 of 12 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
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- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
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This repository is licensed under MIT License.
This repository includes a README.md file.
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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 present, and the description does not disclose behavioral traits such as side effects, authentication requirements, or that the tool generates new content without modifying existing data. This lack of transparency is a notable 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 concise with one sentence that front-loads the main purpose and lists examples. It could benefit from a more structured format, but it is efficient and 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?
Given the tool has 11 parameters and no output schema, the description should explain what the generated assets contain and how they are used. It only briefly mentions output types, leaving significant gaps for a complex 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?
Schema description coverage is 100%, meaning all parameters are documented in the input schema. The description adds no additional meaning or usage context beyond what is already in the schema, resulting in a baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool creates internal selling tools for champions and lists example outputs like executive briefs and objection responses. It distinguishes from sibling tools that focus on different aspects of sales enablement, but could be more specific about its exact scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance is provided on when to use this tool versus alternatives like roi_business_case_builder or proposal_section_writer. The list of asset types implies usage contexts, but users must infer this without direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description does not disclose any behavioral traits such as side effects, authorization requirements, or output format. The agent is left without critical behavior information for a tool that likely writes content.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences and is front-loaded with the main action. It could be slightly more informative, but it 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 the complexity (11 parameters, no output schema, no annotations), the description is too brief. It does not explain the output, how parameters interact, or prerequisites, leaving significant gaps for 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% parameter description coverage, so the schema already explains each parameter. The tool description adds no extra meaning beyond listing some section types, which are already enumerated 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 tool generates customized proposal sections and gives examples like executive summaries and pricing justifications. It distinguishes from sibling tools, which focus on other aspects of sales strategy, but the phrase 'and more' is slightly vague.
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 its siblings or when not to use it. The description only states the basic function without contextual cues.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It states that the tool 'generates' plans and 'creates alignment', but it does not disclose side effects, authorization needs, rate limits, or whether it modifies existing records. For a generative tool with no annotation safety signals, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the primary action, and contains no redundant information. 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?
Despite having 11 parameters and no output schema, the description does not explain the tool's return value or expected output format. It also lacks guidance on how required vs optional parameters interact. The tool's complexity demands 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?
All 11 parameters have descriptions in the input schema (100% coverage), so the baseline is 3. The description adds minimal new meaning about parameters beyond what the schema provides, mentioning 'milestones, owners, and dates' but not connecting these to specific parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Generate') and resource ('collaborative close plans'), clearly stating the tool's purpose. It distinguishes itself from sibling tools like 'account_plan_builder' by focusing specifically on close plans with milestones, owners, and dates.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus alternatives. It lacks guidance on prerequisites, when not to use it, or how it fits into the sales process compared to other tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full responsibility for behavioral disclosure. It only describes the tool's purpose without mentioning any safety traits, side effects, authentication requirements, or what happens upon invocation. For a tool that presumably reads data, it fails to confirm read-only 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 extremely concise at two sentences, containing only essential information with no redundant or verbose language. Every word serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 10 parameters (1 required) and no output schema, the description is minimal. While the schema covers parameter details, the description lacks guidance on how to effectively craft a request (e.g., which parameters are critical for different scenarios). It is complete enough for a straightforward tool but not rich.
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 10 parameters. The description adds no additional meaning or context about how parameters should be used together, and does not elaborate on any parameter beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it provides 'value-based pricing defense strategies and negotiation tactics' and specifies its goal of 'maintain[ing] deal value while addressing discount requests'. However, it does not differentiate from sibling tools like 'deal_strategy_coach' which might offer 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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when discount requests arise, but it lacks explicit guidance on when to use this tool over alternatives, nor does it specify when not to use it. No exclusion criteria or alternative tool references are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully convey behavioral traits. It only states it generates calculations and summaries, but omits details like side effects, data persistence, required permissions, or limitations. The agent cannot assess safety or dependencies.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the primary function and key outputs. Every word adds value, making it efficient and clear.
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 an 11-parameter tool without an output schema, the description provides a general sense of output (executive-ready summaries) but lacks specifics on return format, assumptions used, or what constitutes a 'defensible' calculation. More detail would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so each parameter is already well-documented. The tool description adds no further parameter specifics, meeting the baseline but not enhancing understanding 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 builds quantified ROI business cases with documented assumptions and benchmarks, distinguishing it from sibling tools like account_plan_builder or win_loss_analyzer which serve different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not specify when to use this tool versus alternatives. It lacks explicit guidance on prerequisites, scenarios, or when not to use it, leaving the agent to infer usage solely from the tool name and purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It only states the output (plans) but doesn't mention side effects, data handling, output format, or any limitations. The agent lacks knowledge of what happens with inputs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, short and front-loaded with the main action. No extraneous words – every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having 9 parameters and no output schema, the description doesn't explain the return format, how the 90-day plan is structured, or what 'actionable' means. More detail is needed for a tool of this complexity.
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 clear parameter descriptions. The tool's description adds no additional semantic value beyond what the schema already provides, so baseline score of 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 the tool generates strategic account plans with specific methodologies (power mapping, whitespace analysis, expansion strategies) and provides actionable 90-day plans. This distinguishes it from sibling tools like deal_strategy_coach or mutual_action_plan_generator.
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 strategic account planning but does not explicitly state when to use this tool versus alternatives. No prerequisites or context-specific guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It mentions generating questions and tactics but fails to disclose behavioral traits like whether it is read-only, requires permissions, or has side effects. The 'landmine' term hints at strategy but lacks concrete behavior details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences with a clear front-loaded action. No unnecessary words, but the second sentence is somewhat vague. Still efficient and 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?
With 8 parameters, 2 enums, and no output schema, the description is too sparse. It lacks explanation of key parameters like 'trap_type' or 'evaluation_stage' and does not cover return value or usage patterns, leaving gaps for 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?
Schema description coverage is 100%, meaning each parameter is already well-documented in the schema. The description adds no additional parameter-level meaning, so baseline 3 is appropriate; it does not enhance understanding of parameter interactions or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool generates landmine questions and competitive positioning tactics, with a specific verb and resource. It distinguishes from siblings like 'discovery_question_bank' by focusing on exposing competitor weaknesses during evaluation.
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?
Indicates use during evaluation and emphasizes positivity ('without being negative'), providing clear context. However, it does not explicitly state when not to use or name alternatives, missing a stronger differentiation from sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It mentions the tool includes discovery questions, feature-to-value mapping, and objection handling, giving insight into output content. But it does not state whether it's read-only or destructive, or if it requires specific permissions, leaving the agent uncertain about 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?
The description is two sentences with no wasted words. It front-loads the main action and each sentence earns its place by outlining key components, making it highly concise and 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?
Given 11 parameters, no output schema, and no annotations, the description provides a high-level overview but lacks details for fully informing an agent. It omits aspects like attendee roles, competitor context, and desired outcome, which are covered only in the schema. While adequate for selection, it falls short for confident 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 coverage is 100%, so the description does not need to add parameter details. It aligns with parameters like primary_audience and demo_type through phrases like 'tailored to specific personas,' but it does not add new meaning beyond the schema's parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool creates outcome-focused demo scripts tailored to personas and use cases, identifying the verb and resource. However, it does not explicitly differentiate from sibling tools like deal_strategy_coach or discovery_question_bank, which have overlapping purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use when creating a demo script for specific personas, providing clear context. However, it lacks explicit guidance on when not to use this tool or alternatives among siblings, such as champion_enablement_kit for building internal champions.
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 fully bears the burden. It mentions that questions 'adapt based on what you already know', which hints at context-aware behavior, but does not disclose side effects, authentication requirements, rate limits, or what happens when parameters are missing. Critical behavioral details are absent.
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 sentences, front-loaded with purpose, no redundant words. Efficiently communicates the core function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Without output schema, the description does not explain what is returned (list of questions, formatted text, etc.). The tool has 8 parameters but only 1 required; the description doesn't cover edge cases or typical usage scenarios. Adequate but incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (all 8 parameters have descriptions). The description adds general context about adaptation but does not provide specific meaning beyond the schema. 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 'Get contextual discovery questions using MEDDPICC, BANT, SPICED, or custom frameworks.' It specifies the verb 'get' and resource 'discovery questions', and distinguishes from sibling tools that focus on other sales activities like strategy or plans.
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 during discovery conversations but provides no explicit guidance on when to use this tool versus alternatives like deal_strategy_coach or account_plan_builder. No when-not-to-use or prerequisite conditions are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must fully convey behavioral traits. It only states that the tool generates sequences and lists types, but does not disclose what the output includes (e.g., complete email body vs. subject lines only), any rate limits, or whether it requires specific input formats. This is insufficient for a tool with 11 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 consists of two sentences that efficiently convey the tool's core purpose and output categories. Every word earns its place without extraneous 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?
Given 11 parameters, no output schema, and no annotations, the description is adequate but leaves gaps. It does not explain the return format (e.g., array of email objects) or how sequences are structured. A bit more detail would improve completeness for 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?
Schema description coverage is 100%, so baseline is 3. The description mentions persona, stage, and objective, aligning with parameters like target_persona and sequence_type, but does not add significant new meaning beyond what the schema already provides. It lacks clarification on how 'stage' maps to sequence_type.
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 generates multi-touch email sequences and lists specific types (prospecting, nurture, follow-up, re-engagement). This effectively differentiates it from sibling tools like demo_script_builder or proposal_section_writer, which focus on different content.
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 creating email sequences by mentioning persona, stage, and objective, and lists example sequence types. However, it provides no explicit guidance on when to use this tool versus alternatives, nor does it specify when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. The description only says 'analyze' and does not mention any side effects, auth requirements, rate limits, or what the tool returns. For a read-only analysis tool, 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?
Two sentences, front-loaded with the main action and scope, no redundant or tangential content. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 10 parameters, no output schema, and no annotations, the description covers the high-level purpose but lacks details on what the analysis produces, how to interpret results, or best practices for parameter combinations. It is adequate but has clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with each parameter described in the schema. The description adds no additional parameter-level meaning beyond the schema, meeting the baseline of 3.
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 analyzes deal outcomes to identify patterns and improve win rates, and specifies scope with 'single deals or deal portfolios'. This is a specific verb-resource pairing that distinguishes it from sibling tools like deal_strategy_coach or competitive_trap_setter.
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 stating it works with single deals or portfolios, but does not explicitly contrast against sibling tools or provide when-not-to-use guidance. The sibling context includes many related tools, so more explicit differentiation would help.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility. It states the tool 'provides' strategies and next steps, implying a read-only analysis. However, it does not disclose whether data is persisted, whether any side effects occur, or if authentication is required. This is adequate but not detailed.
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, front-loaded sentence that efficiently conveys the tool's core function and inputs. While concise, it could benefit from slightly more structure (e.g., listing outputs) but remains effective.
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 11 diverse parameters (many optional) and no output schema, the description provides a reasonable overview but lacks detail about return values or example usage. For a tool with no annotations, this is minimally sufficient but leaves gaps in understanding exactly what the agent receives.
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 each parameter. The description adds no extra meaning about the parameters, only summarizing the tool's purpose. Baseline of 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 the tool provides 'deal-specific winning strategies' based on specific factors (deal stage, competitive dynamics, stakeholder positions) and mentions outputs ('tactical next steps and risk mitigation'). This distinguishes it from sibling tools like 'account_plan_builder' or 'competitive_trap_setter'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context (deal analysis) but does not explicitly guide when to use this tool versus alternatives. With 11 sibling tools, the lack of direct comparisons or exclusions leaves the agent to infer appropriate usage.
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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