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Amit-Lakhani

Postman MCP Generator

by Amit-Lakhani
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JavaScript
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Server Quality Checklist

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  • Latest release: v1.0.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose targeting different attributes of an activity in Adobe Target: priority, schedule, and state. There is no overlap or ambiguity between them, making it easy for an agent to select the correct tool based on the specific update needed.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern with 'update_activity_' as a prefix followed by the specific attribute (priority, schedule, state). This uniformity enhances readability and predictability across the tool set.

    Tool Count2/5

    With only 3 tools, the set feels thin for a server named 'Postman MCP Generator', which might imply broader functionality. While the tools cover specific update operations for Adobe Target activities, the scope seems limited, lacking create, get, delete, or other essential CRUD operations for a complete activity management surface.

    Completeness2/5

    The tool set is severely incomplete for managing activities in Adobe Target. It only provides update operations for priority, schedule, and state, missing create, read, delete, and other lifecycle operations. This will likely cause agent failures when trying to perform full activity workflows, as there are significant gaps in coverage.

  • Average 2.9/5 across 3 of 3 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 0 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available

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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 provided, the description carries the full burden of behavioral disclosure. It states this is an update operation, implying mutation, but doesn't address critical behavioral aspects like required permissions, whether changes are reversible, rate limits, or what happens to the activity during the update. This is a significant gap for a mutation tool.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is a single, efficient sentence that states the tool's purpose without any wasted words. It's appropriately sized and front-loaded, 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.

    Completeness2/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    For a mutation tool with no annotations and no output schema, the description is incomplete. It lacks behavioral context (e.g., permissions, effects), usage guidance relative to siblings, and details on the update operation's outcome. Given the complexity of updating a priority in a system like Adobe Target, more information is needed.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters3/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The schema description coverage is 100%, with both parameters (tenant and priority) documented in the schema. The description adds no additional parameter semantics beyond what's in the schema, such as format examples or constraints. Baseline 3 is appropriate when the schema does the heavy lifting.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose4/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the action ('Update') and target resource ('priority of an activity in Adobe Target'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its siblings (update_activity_schedule and update_activity_state), which also update activity properties, so it doesn't reach the highest score.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines2/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description provides no guidance on when to use this tool versus its siblings or alternatives. It doesn't mention prerequisites, exclusions, or specific contexts for updating priority versus schedule or state, leaving the agent with no usage direction beyond the tool name.

    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 'Update' which implies a mutation, but doesn't clarify if this requires specific permissions, is destructive, has side effects, or what the response might be. This leaves significant gaps for a tool that modifies data.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is a single, direct sentence with zero wasted words. It is appropriately sized and front-loaded, efficiently conveying the core 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 complexity of a mutation tool with no annotations and no output schema, the description is incomplete. It lacks information on behavioral traits, error handling, or what the update entails, which is insufficient for safe and effective use by an AI agent.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters3/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The input schema has 100% description coverage, with clear documentation for all three parameters (tenant, startsAt, endsAt). The description adds no additional parameter details beyond what the schema provides, so it meets the baseline of 3 without compensating for any 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 action ('Update') and the resource ('activity schedule in Adobe Target'), making the purpose immediately understandable. It distinguishes from sibling tools like 'update_activity_priority' and 'update_activity_state' by specifying the schedule aspect, though it doesn't explicitly contrast them.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines2/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description provides no guidance on when to use this tool versus alternatives like the sibling tools. It lacks context about prerequisites, such as needing an existing activity to update, or any exclusions, leaving the agent to infer usage from the tool name alone.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior2/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    With no annotations provided, the description carries the full burden of behavioral disclosure. It states this is an update operation, implying mutation, but doesn't cover critical aspects like required permissions, whether changes are reversible, rate limits, or error handling. This is a significant gap for a mutation tool.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is a single, efficient sentence with zero waste. It's front-loaded with the core action and target, making it easy to parse quickly.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness2/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given the complexity of a mutation tool with no annotations and no output schema, the description is incomplete. It lacks behavioral context, usage guidance, and details about the update operation's effects or return values, leaving the agent with insufficient information for reliable use.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters3/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The schema description coverage is 100%, with clear descriptions for both parameters (tenant and state). The description doesn't add any meaning beyond what the schema provides, such as explaining valid state values or tenant context. Baseline 3 is appropriate when the schema does the heavy lifting.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose4/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the action ('Update') and the target ('state of an activity in Adobe Target'), making the purpose understandable. However, it doesn't differentiate this tool from its siblings (update_activity_priority and update_activity_schedule), which also update activity attributes but different ones.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines2/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description provides no guidance on when to use this tool versus its siblings or alternatives. It lacks context about prerequisites, typical use cases, or exclusions, leaving the agent to infer usage from the tool name alone.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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