Server Quality Checklist

Tool Scores

• select_endpoint_bundleC
  2.8/5.0
  Behavior2/5

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

  With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the tool 'Returns selected endpoints with required and dependency annotations and a summary', which gives some output information. However, it doesn't describe what 'resolve' entails operationally, whether this is a read-only or mutating operation, what happens to the stored bundles_result, or any error conditions 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.

  Conciseness4/5

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

  The description is appropriately concise at 4 sentences. It's front-loaded with the core purpose ('Step 4 of 6. Resolve the user's selection...'), followed by prerequisites, parameter hints, and return information. There's minimal wasted language, though the workflow step numbering could be more integrated with the purpose statement.

  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 (6 parameters, workflow tool, no annotations, no output schema), the description is incomplete. It provides workflow context and some parameter hints but lacks crucial information about what the tool actually does operationally, the meaning of the color choices, how customizations affect the result, and the format of the returned data. For a tool with this many parameters and no structured documentation elsewhere, more detail is needed.

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

  Parameters2/5

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

  With 0% schema description coverage and 6 parameters (only 1 required), the description must compensate but provides limited help. It mentions 'choice' parameter values ('green | yellow | red') and that 'customizations' can 'add/remove of endpoints', and references 'bundles_result' usage. However, it doesn't explain 'spec', 'openapi_input', or 'input_type' parameters at all, leaving most parameters undocumented.

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

  Purpose3/5

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

  The description states the tool 'Resolve the user's selection (green | yellow | red) and optional add/remove of endpoints' and 'Returns selected endpoints with required and dependency annotations and a summary', which provides a basic purpose. However, it's somewhat vague about what 'resolve' means operationally and doesn't clearly distinguish this from sibling tools like 'propose_endpoint_bundles' beyond being 'Step 4 of 6'.

  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 about workflow sequencing: 'Requires step 3 (propose_endpoint_bundles)' and 'Completes workflow step 4'. It mentions using 'stored bundles_result from step 3 if not provided', which gives guidance on parameter usage. However, it doesn't explicitly state when NOT to use this tool or name specific alternatives among siblings.

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

• propose_endpoint_bundlesB
  3.3/5.0
  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. It discloses that this is part of a workflow (step 3/6), has dependencies on prior steps, and describes the return structure ('bundles with endpoint_count and endpoints_sample; dependency_endpoints; total_operations'). However, it doesn't mention error conditions, performance characteristics, or authentication needs that would be helpful for a tool with 7 parameters.

  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 reasonably concise but includes workflow boilerplate ('Step 3 of 6', 'Completes workflow step 3') that could be streamlined. The information is front-loaded with the core purpose, but the parameter explanation is buried and incomplete. Some sentences like 'Next: run select_endpoint_bundle(choice) (step 4)' feel redundant.

  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 complexity (7 parameters, workflow tool, no output schema, no annotations), the description is incomplete. It covers the basic purpose, workflow position, and return structure, but fails to adequately explain the numerous parameters or provide behavioral context needed for proper tool selection and invocation. The lack of output schema means the description should ideally explain return values more thoroughly.

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

  Parameters2/5

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

  Schema description coverage is 0%, so the description must compensate. It mentions that the tool 'Uses stored spec and inferred_segment from prior steps if not provided' and lists some parameters ('spec or openapi_input; optional agent_creator_role, agent_task_workflow, inferred_segment'), but doesn't explain what these parameters mean, their formats, or how they affect the proposal. With 7 undocumented parameters, this is insufficient.

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

  Purpose4/5

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

  The description clearly states the tool's purpose: 'Propose three endpoint bundles (Green / Yellow / Red) based on the API and optional user context.' It specifies the verb ('propose'), resource ('endpoint bundles'), and scope ('three bundles with color coding'). However, it doesn't explicitly differentiate from sibling tools like 'select_endpoint_bundle' beyond mentioning it as the next step.

  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 for when to use this tool: 'Step 3 of 6' and 'Requires step 2 (prompt_mcp_developer_context).' It mentions dependencies on prior steps and optional parameters. However, it doesn't explicitly state when NOT to use it or compare it to alternatives among siblings.

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

• prompt_mcp_developer_contextA
  3.5/5.0
  Behavior3/5

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

  No annotations are provided, so the description carries the full burden. It discloses that this tool 'Uses stored analysis from step 1' if inputs aren't provided, which adds useful behavioral context about state management. However, it doesn't cover other traits like error handling, performance, or side effects, leaving gaps for a tool in a multi-step workflow.

  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 appropriately sized and front-loaded with the step context, but includes some redundancy (e.g., repeating 'step 1' and 'step 2') and could be more streamlined. Sentences like 'Completes workflow step 2.' don't add significant value, reducing efficiency.

  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 complexity of a multi-step workflow tool with 3 parameters, 0% schema coverage, no annotations, and no output schema, the description is incomplete. It covers usage sequencing and return values at a high level, but lacks details on parameter usage, error cases, and full behavioral context, making it only minimally adequate.

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

  Parameters2/5

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

  Schema description coverage is 0%, so the description must compensate for all three parameters. It mentions 'analysis' and 'openapi_input' as options to provide, but doesn't explain their formats, purposes, or the 'input_type' parameter at all. This adds minimal meaning beyond the schema, failing to adequately document the parameters.

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

  Purpose4/5

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

  The description clearly states this is 'Step 2 of 6' in a workflow and that it 'get[s] Trimble Agentic Ecosystem context and prompts,' which specifies the verb (get) and resource (context and prompts). However, it doesn't explicitly distinguish this from sibling tools like 'propose_endpoint_bundles' or 'validate_openapi' beyond mentioning their step numbers, so it lacks full sibling differentiation.

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

  Usage Guidelines5/5

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

  The description provides explicit guidance on when to use this tool: 'Use after validate_openapi' and 'Requires step 1 (validate_openapi).' It also mentions alternatives for input ('provide analysis or openapi_input') and specifies the next step ('Next: run propose_endpoint_bundles (step 3)'), making usage context very clear.

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

• generate_mcp_serverA
  3.8/5.0
  Behavior4/5

  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 effectively describes key behaviors: it's part of a multi-step workflow, automatically proceeds to step 6 (GitHub repo creation) on success, always creates a new public repo, and returns specific outputs (output_dir, files_created, etc.). It also mentions the tool's scope and consequences, though it could elaborate more on error handling 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.

  Conciseness4/5

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

  The description is appropriately sized and front-loaded, starting with the core purpose. Sentences are efficient, covering prerequisites, parameters, behavior, and outputs without redundancy. Minor improvements could include bullet points for outputs or clearer separation of steps, but overall it's well-structured and concise.

  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 complexity of a multi-step workflow tool with 2 parameters, 0% schema coverage, no annotations, and no output schema, the description is moderately complete. It covers purpose, prerequisites, parameters, and outputs, but lacks details on error cases, side effects, or how it integrates with siblings like 'upload_to_github'. For a tool that automatically creates public repos, more cautionary notes would enhance 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 0%, so the description must compensate. It explains both parameters: 'output_dir' as an optional path for the project and 'repo_name' as an optional suggested name for step 6, with derivation from API title if omitted. This adds meaningful context beyond the schema's basic titles. However, it doesn't detail format constraints or examples for paths, leaving some ambiguity.

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

  Purpose4/5

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

  The description clearly states the tool's purpose: 'Generate a complete MCP server directory from the selected endpoints.' It specifies the verb (generate) and resource (MCP server directory), and mentions it's part of a workflow (step 5 of 6). However, it doesn't explicitly differentiate from sibling tools like 'upload_to_github' or 'select_endpoint_bundle', which handle related but distinct steps.

  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 for when to use this tool: 'Requires step 4 (select_endpoint_bundle). Uses stored validated_spec and selected_endpoints.' It specifies prerequisites and workflow dependencies. However, it doesn't explicitly state when NOT to use it or mention alternatives among siblings, such as using 'upload_to_github' separately.

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

• reset_workflowA
  3.8/5.0
  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 describes the action ('Clear workflow state and start over'), which implies a destructive reset, but does not specify if this is reversible, what data is lost, or any permissions required. It adds some context about post-reset steps, but lacks details on error handling or side effects, making it adequate but with gaps.

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

  Conciseness5/5

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

  The description is concise and well-structured, consisting of two sentences that efficiently convey the tool's purpose and usage guidelines. Every sentence adds value, with no wasted words, and it is front-loaded with the main action.

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

  Completeness3/5

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

  Given the tool's complexity (a destructive reset with no parameters) and the lack of annotations and output schema, the description is minimally complete. It explains what the tool does and the next steps, but does not cover potential risks, confirmation prompts, or error scenarios. For a tool that clears state, more behavioral context would be beneficial, but it meets basic requirements.

  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 0 parameters, and the schema description coverage is 100%, so there is no need for parameter details in the description. The description appropriately focuses on the tool's purpose and usage without redundant parameter information, meeting the baseline for zero parameters.

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

  Purpose4/5

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

  The description clearly states the tool's purpose with a specific verb ('Clear') and resource ('workflow state'), and indicates the outcome ('start over'). It distinguishes from siblings by mentioning a specific use case ('when the user wants to use new API docs'), though it doesn't explicitly name alternatives. The purpose is not tautological and is adequately specific.

  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 for when to use this tool ('when the user wants to use new API docs') and outlines the next steps ('ask the user to provide new API docs and run validate_openapi'). It implies usage by linking to a sibling tool (validate_openapi) but does not explicitly state when not to use it or name all alternatives, keeping it from a perfect score.

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

• get_workflow_statusA
  4/5.0
  Behavior3/5

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

  No annotations are provided, so the description carries the full burden. It discloses that the tool returns information ('Return the current workflow step...'), implying it's a read-only operation, but doesn't specify behavioral traits like error handling, response format, or whether it updates any state. It adds some context about tracking progress but lacks details on how the 'current step' is determined or if it's dynamic.

  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 highly concise and well-structured: two sentences that directly state the purpose and usage, followed by a bullet-like list of the tool order. Every sentence earns its place by providing essential information without waste, making it easy to scan and understand.

  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 complexity (a workflow status tool with no parameters but no output schema), the description is somewhat complete but has gaps. It explains what the tool does and when to use it, but without annotations or an output schema, it doesn't detail the return format (e.g., what 'current workflow step' looks like) or potential errors. This is adequate but could be more informative for an agent.

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

  Parameters4/5

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

  The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't mention parameters, which is appropriate. A baseline of 4 is applied since it avoids redundancy and focuses on the tool's purpose and usage.

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

  Purpose4/5

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

  The description clearly states the tool's purpose: 'Return the current workflow step and the required order of tools.' This specifies the verb ('Return') and resource ('current workflow step and required order of tools'), making it understandable. However, it doesn't explicitly differentiate from sibling tools like 'reset_workflow' which might also relate to workflow state.

  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?

  The description provides explicit usage guidance: 'Use this to keep the user/agent on track.' It also lists the specific order of tools (1-6), which implicitly defines when to use this tool—to check progress against that sequence—and distinguishes it from alternatives like individual step tools. This is comprehensive guidance for context.

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

• upload_to_githubA
  4.1/5.0
  Behavior3/5

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

  No annotations are provided, so the description carries the full burden. It discloses some behavioral traits: it's a write operation (creates repo, uploads directory), has dependencies on previous steps, and returns specific outputs (repo_url, message, next_step_guidance). However, it lacks details on authentication needs, error handling, rate limits, or what happens if the repo already exists.

  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 appropriately sized and front-loaded: the first sentence states the core purpose, followed by prerequisites, parameter details, and return values. Every sentence adds value with zero waste, using bullet-like formatting for parameters without being verbose.

  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 annotations and no output schema, the description does a good job covering the tool's context: purpose, workflow step, prerequisites, parameters, and return values. It's complete enough for a tool with 3 optional parameters in a known workflow, though it could benefit from more behavioral details like error cases or side effects.

  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?

  With 0% schema description coverage, the description must compensate. It adds meaningful semantics for all 3 parameters: 'repo_name: optional repo name; default unique name (base + timestamp) to avoid repeats.', 'visibility: "public" or "private". Default: "public".', and 'source_dir: optional path to generated directory; default: get_stored("output_dir").' This provides clear context beyond the bare schema, though it doesn't explain parameter interactions or constraints.

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

  Purpose4/5

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

  The description clearly states the tool's purpose: 'Create a new GitHub repo and upload the generated MCP server directory.' It specifies the verb (create and upload), resource (GitHub repo with MCP server directory), and scope (step 6 of a workflow). However, it doesn't explicitly differentiate from sibling tools like 'send_repo_email_to_user' which might also involve GitHub repos.

  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?

  The description provides explicit usage guidelines: 'Requires step 5 (generate_mcp_server).' It also specifies dependencies ('Uses stored output_dir if source_dir not provided') and context ('Completes workflow step 6'). This clearly indicates when to use this tool and its prerequisites within the workflow.

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

• validate_openapiA
  4.3/5.0
  Behavior4/5

  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 effectively describes key behaviors: it fetches and reads response bodies from URLs (including specific examples like raw.githubusercontent.com), handles both read and download-style URLs, returns validation results with analysis and scaffolding, and outlines success/failure outcomes. However, it lacks details on rate limits, authentication needs, or error handling beyond validation failures.

  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 well-structured and front-loaded with the core purpose, followed by usage details and outcomes. Most sentences add value, but it includes some redundancy (e.g., repeating URL examples) and could be slightly more concise without losing clarity.

  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 complexity of a validation tool with 2 parameters, no annotations, and no output schema, the description is reasonably complete. It covers input types, behavioral aspects, and success/failure outcomes, though it could benefit from more details on error scenarios beyond validation failures and the optional parameter's role.

  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 0%, so the description must compensate for undocumented parameters. It explains the semantics of 'openapi_input' by detailing acceptable values (file path, URL, or inline JSON/YAML) and URL examples, but does not clarify the purpose or usage of the optional 'input_type' parameter. This partial compensation results in a baseline score.

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

  Purpose5/5

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

  The description clearly states the tool's purpose with specific verbs ('validates OpenAPI 2/3 specs') and resources (file path, URL, or inline JSON/YAML). It distinguishes itself from siblings by being explicitly labeled as 'Step 1 of 6' in a workflow, making its role unique among tools like generate_mcp_server or upload_to_github.

  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?

  The description provides explicit usage guidance: it specifies when to use this tool ('Step 1 of 6'), what types of inputs are accepted (file path, URL, or inline JSON/YAML), and includes a clear directive for next steps ('You must present results to the user and get confirmation before calling step 2'). This gives strong context for when to use it versus alternatives.

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

• send_repo_email_to_userA
  4.5/5.0
  Behavior4/5

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

  With no annotations provided, the description carries the full burden. It discloses key behavioral traits: it requires email validation before sending, uses environment variables (SENDER_EMAIL, GOOGLE_APP_PASSWORD), and returns success or error messages. However, it doesn't mention rate limits, authentication needs beyond env vars, or detailed 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.

  Conciseness4/5

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

  The description is appropriately sized and front-loaded, starting with the core purpose. Each sentence adds value: prerequisites, parameter details, and implementation notes. It could be slightly more concise by combining some details, but there's minimal waste.

  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 annotations and no output schema, the description is fairly complete for a 3-parameter tool. It covers purpose, usage context, parameter semantics, and behavioral aspects like env vars and returns. However, it lacks details on output format (e.g., structure of success/error messages) and doesn't fully address all potential edge cases.

  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 description coverage is 0%, so the description must compensate. It adds meaning for all parameters: email must be validated, repo_url is optional and defaults to last upload if omitted, and description is optional for the email body. This covers semantics beyond the basic schema, though it could specify format constraints like email validation rules.

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

  Purpose5/5

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

  The description clearly states the tool's purpose: 'send the repo URL to the user's email via Gmail' after a GitHub upload. It specifies the verb ('send'), resource ('repo URL'), target ('user's email'), and method ('via Gmail'), distinguishing it from sibling tools like upload_to_github or get_workflow_status.

  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?

  The description provides explicit usage guidelines: 'Call this only after the user has confirmed their email is correct' and 'after a successful GitHub upload.' It also implies an alternative by noting that repo_url is optional and can be retrieved from 'get_stored' if omitted, though it doesn't name specific sibling alternatives.

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