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aaronsb

Salesforce MCP Server

by aaronsb

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v0.7.2

  • Disambiguation4/5

    Most tools have distinct purposes (CRUD, SOQL, field search, user info). Opportunity-related tools (analyze_conversation, generate_business_case, get_opportunity_details, opportunity_insights) overlap in domain but differ in function; descriptions clarify each tool's specific role. Only minor potential confusion between analyzing conversation insights and generating a business case.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern using snake_case (e.g., create_record, execute_soql, search_fields). No mixed conventions or vague verbs.

    Tool Count5/5

    11 tools are well-scoped for a Salesforce MCP server, covering CRUD, querying, field search, and opportunity-specific insights. Not too few or too many for the domain.

    Completeness4/5

    The tool surface covers core CRUD (create, update, delete records) and SOQL for reading any object. Opportunity-specific tools add value. Minor gaps: no dedicated 'get_record' for arbitrary objects (though SOQL suffices) and no bulk operations, but overall sufficient for common Salesforce interactions.

  • Average 3.6/5 across 11 of 11 tools scored. Lowest: 2.8/5.

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

    • No community issues in the last 6 months
    • 33 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is failing
  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

  • Add a glama.json file to provide metadata about your server.

  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

    {
      "$schema": "https://glama.ai/mcp/schemas/server.json",
      "maintainers": [
        "your-github-username"
      ]
    }

    Then . Browse examples.

  • Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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

  • Behavior1/5

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

    No annotations exist, so the description must convey behavioral traits. It only states 'generate insights' without mentioning whether the tool is read-only, does it mutate data, require authentication, or has rate limits. Complete lack of transparency.

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

    Conciseness4/5

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

    The description is a single concise sentence that front-loads the key value proposition. It wastes no words, though it could benefit from bullet points or structured sections for clarity given the tool's complexity.

    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?

    With 10 parameters and no output schema, the description provides a broad overview of capabilities but misses details like whether results are returned in real-time or stored, and how to optimally combine parameters. Moderately complete 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 description adds context by grouping parameters into categories (pipeline health, performance metrics, etc.), but does not elaborate on how parameters interact or specific formats. Adequate but not exceptional.

    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?

    Description clearly states the tool generates insights and analytics from opportunity data, listing specific categories like pipeline health and industry trends. However, it does not differentiate from siblings like 'analyze' or 'analyze_conversation', which may cause confusion.

    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 usage guidelines are provided; the description does not indicate when to use this tool versus alternatives such as 'analyze' or 'get_opportunity_details'. The agent receives no context for decision-making.

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

  • Behavior2/5

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

    The description only says 'Delete', implying destructive action, but without annotations it fails to disclose whether deletion is permanent, reversible, or has side effects on related data.

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

    Conciseness3/5

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

    The description is short and front-loaded, but it lacks important details that could be included without being verbose. It is adequately concise but incomplete.

    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 no output schema, the description fails to explain what the tool returns or what constitutes success/failure. It lacks completeness for a destructive operation.

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

    Parameters3/5

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

    Schema description coverage is 100%, so the schema already documents both parameters. The description adds no additional meaning beyond what is in 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 action (Delete) and the resource (a record from Salesforce), which is distinct from sibling tools like create_record or update_record.

    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 or when not to use this tool. It does not mention that deletion is permanent, nor does it suggest alternatives like update_record for soft-deletion.

    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 must disclose behavioral traits. It only states the basic operation and field support, omitting important details like error handling, return value (e.g., record ID), or side effects. This is insufficient 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.

    Conciseness4/5

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

    The description is a single sentence of 12 words, very concise. It front-loads the core purpose, but could be slightly more structured (e.g., separating supported fields). 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?

    Given the tool's complexity (create with nested object, no output schema), the description lacks completeness. It doesn't mention the return value (e.g., record ID), potential errors, or behavior for required fields beyond those in the schema. More context is needed for an agent to use this reliably.

    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 schema already documents both parameters thoroughly. The description adds minimal value by confirming support for custom fields, which is already implied in the schema's custom field example. 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 specifies the action ('create') and the resource ('a new record in Salesforce'), and differentiates from sibling tools like delete_record or update_record. The mention of supporting both standard and custom fields adds specificity.

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

    Usage Guidelines2/5

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

    The description provides no guidance on when to use this tool versus alternatives such as update_record or batch. No explicit when-to-use, prerequisites, or exclusions 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?

    No annotations exist, so the description carries full burden. It only says 'get information', implying a read operation, but does not explicitly state it is non-destructive or describe any other behavioral traits (e.g., no side effects, requires authentication).

    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 is front-loaded and appropriately sized for a parameterless 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 no output schema and simple action, the description is minimal. It does not specify what fields are returned, leaving ambiguity about the tool's output. However, for a straightforward user info tool, it is passable.

    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?

    There are zero parameters, and the schema coverage is 100%. Per guidelines, no-parameter tools get a baseline of 4. The description adds no param-specific info, which is acceptable here.

    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 retrieves information about the current user. It is specific and distinct from sibling tools, but could be improved by hinting at the type of information returned.

    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 vs alternatives, nor any context about prerequisites or typical use cases.

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

  • Behavior2/5

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

    No annotations provided, so the description must fully disclose behavior. It only states the inclusion of standard and custom objects, omitting details like pagination limits, rate limits, or whether the list is exhaustive of all objects in the org.

    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?

    Single sentence, front-loaded with the core purpose. No extraneous information.

    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 no output schema, the description could hint at the return format (e.g., list of object names or metadata). As is, it is minimally viable but lacks completeness for an agent to fully understand the tool's 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 coverage is 100% and both parameters (pageSize, pageNumber) are described in the schema. The description does not add additional meaning beyond what the schema already provides.

    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 all Salesforce objects (standard and custom), with a specific verb ('List') and resource ('available Salesforce objects'). This distinguishes it from sibling tools like 'create_record' or 'execute_soql'.

    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. It does not mention scenarios where it is preferable to use sibling tools like 'describe_object' or 'search_opportunities'.

    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 the description carries full burden. It states 'analyzes' and 'extracts insights' implying read-only behavior but doesn't disclose side effects, permissions, or output format.

    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 with no wasted words; front-loaded with the core purpose and efficiently structured.

    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 a single parameter and no output schema or annotations, the description covers the tool's purpose, data sources, and output type (engagement recommendations). Adequate for the complexity level.

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

    Parameters3/5

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

    Schema description coverage is 100% with a clear description for 'opportunityId'. The description adds no extra semantics beyond the schema, so baseline 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 it analyzes conversation activity and extracts insights from specific sources (Gong calls, emails) for an opportunity, which is distinctive from generic siblings like 'analyze'. However, it does not explicitly differentiate from similar siblings like 'enrich_opportunity'.

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

    Usage Guidelines3/5

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

    The description implies usage when needing engagement insights for an opportunity, but lacks explicit guidance on when not to use it or mention of alternatives like 'enrich_opportunity'.

    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 carries full burden. It discloses that the tool fetches multiple data sources (read operations) to produce a report, but does not mention side effects, authorization needs, or potential performance implications. The behavior is fairly transparent but lacks detail on output handling or error states.

    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: first states the core purpose, second details the data sources. No extraneous information, front-loaded with the key verb and resource.

    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's moderate complexity (2 parameters, no output schema, no annotations), the description covers the essential purpose and inputs. It lacks details on output format, error handling, or prerequisites, but overall is sufficiently complete for a straightforward report generator.

    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 description adds context about overall data fetching but does not enhance parameter meaning beyond what the schema already provides. Per calibration, baseline is 3 when schema does the heavy lifting.

    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 generates a markdown business case report for an opportunity and lists the specific data sources (opportunity details, contacts, conversation insights, similar won deals). This distinguishes it from sibling tools like 'get_opportunity_details' (only details) or 'find_similar_opportunities' (only similar deals).

    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 a complete business case report is needed but does not explicitly state when to use this tool versus alternatives (e.g., 'analyze', 'enrich_opportunity'). No when-not or exclusion criteria are provided.

    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 full burden. It discloses the tool returns fields, related records, and metadata, indicating a safe read operation. No side effects mentioned, but none expected.

    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?

    Single sentence, no redundant information, and directly states the tool's function.

    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 no output schema, the description adequately outlines what is returned (fields, related records, metadata). Lacks specifics on structure but sufficient for understanding.

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

    Parameters3/5

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

    Schema has 100% coverage with clear parameter descriptions. The description adds no extra semantic value 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 retrieves detailed information about a Salesforce opportunity, including fields, related records, and metadata. It distinguishes from sibling tools like search_opportunities (searching) and enrich_opportunity (modifying).

    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 when-to-use or when-not-to-use guidance is provided. The description implies read-only usage but does not address alternatives or prerequisites.

    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, so description carries burden. It confirms mutation ('update') and mentions field support, but lacks disclosure of side effects, permissions, partial update behavior, or error handling.

    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?

    Single sentence, front-loaded with core action and resource. No wasted words; efficient.

    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 no output schema or annotations, the description covers core purpose but omits return values, error conditions, and prerequisites. Sufficient for a simple mutation tool but could be more thorough.

    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%, baseline 3. Description adds value by explaining data as key-value pairs and providing example for custom fields with __c suffix, which aids correct invocation.

    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 updates an existing record in Salesforce and supports standard and custom fields. This distinguishes it from sibling tools like create_record or delete_record.

    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?

    No explicit guidance on when to use this tool versus alternatives; it relies on agent knowledge of sibling tool names. Implicitly clear, but no exclusions or examples of situations.

    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, so description bears full burden. It implies a read-only operation (query execution) but does not explicitly state it is non-destructive or safe. The description is not contradictory but lacks explicit 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 front-loaded with the main action, uses exactly three sentences with no wasted words, and each sentence adds value (purpose, custom field handling, field discovery guidance).

    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?

    The tool has 4 parameters with full schema descriptions and no output schema. The description provides extra context about field discovery and alternatives, making it more complete. However, it does not explicitly state the return format or pagination behavior, a minor gap.

    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 adds context for the 'query' parameter regarding custom fields and field catalog, but does not significantly enhance understanding of other parameters beyond their schema descriptions.

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

    Purpose5/5

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

    The description clearly states 'Execute a SOQL query' and specifies support for standard and custom fields, distinguishing it from sibling tools like search_fields or list_objects 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 Guidelines5/5

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

    Provides explicit guidance: to see populated fields, use the field-catalog resource; for complete schema, use describe_object. This clearly tells the agent when and when not to use this tool.

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

  • Behavior5/5

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

    No annotations provided, so description bears full burden. Fully discloses limitations: lexical match, only discovered objects, and that includeValues is free. No contradictions.

    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?

    Single paragraph but well-organized with main purpose first. Each sentence adds value. Could be slightly more structured with bullet points, but still concise and clear.

    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?

    Covers behavior, limitations, and usage context thoroughly. Does not explicitly describe output format, but given no output schema, it mentions ranking. Slightly lacking in output details.

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

    Parameters5/5

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

    Schema description coverage is 100%, but description adds meaning beyond schema (e.g., default behavior for objectName, cost-free for includeValues, clarification on minPopulationPct).

    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?

    Clearly states the tool's purpose: finding fields by concept when API name unknown. Describes what is searched (every scored field on discovered objects) and ranking. No sibling tool duplicates this function.

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

    Usage Guidelines5/5

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

    Explicitly states when to use: when you know what to query but not API name. Provides exclusions (lexical not semantic, only discovered objects). Includes alternative for browsing via field-catalog resource.

    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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