clearskies MCP Server

Server Quality Checklist

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Latest release: v1.1.2
Disambiguation4/5
Most tools are clearly separated into list/get/generate/explain categories with distinct targets. Minor overlap exists between scaffold_project and scaffold_restful_api, and between generate_model and generate_model_with_relationships, but the descriptions are detailed enough to avoid real confusion.
Naming Consistency5/5
All tool names use snake_case and follow consistent verb-first patterns (list_*, get_*, generate_*, scaffold_*, explain_*, etc.). No mixing of conventions or vague verbs, making the naming highly predictable and readable.
Tool Count2/5
54 tools is excessive for an MCP server, even for a comprehensive framework assistant. The 18 list_available_*/get_*_info pairs alone account for 36 tools, which feels bloated. Per the rubric, 25+ tools is too many, and this server far exceeds that threshold.
Completeness5/5
The tool surface thoroughly covers the clearskies framework: component discovery, detailed reference, code generation, project scaffolding, relationship handling, module management, and v1-to-v2 migration. There are no obvious gaps in functionality for the stated purpose.
Average 3.9/5 across 54 of 54 tools scored. Lowest: 2.6/5.
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
- Last stable release on March 2, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
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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 disclosing behavioral traits. It implies a read-only operation via 'Get', but does not explicitly state safety, error behavior (e.g., what happens if the header_type is invalid), or any side effects. The args section adds no behavioral context. This falls short for a tool with no annotation support.
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 with the main purpose. However, the 'Args:' section essentially duplicates the input schema and does not earn its place. A tighter description would omit or integrate the parameter information. It is not bloated, but contains unnecessary redundancy.
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?
The tool is simple (one parameter) and has an output schema, so return values need not be described. However, the description lacks important context: it does not mention how to get valid header_type values (e.g., via 'list_available_security_headers'), nor error handling. Given the sibling tools available, this is a notable gap that reduces the description's completeness for an AI agent.
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. The description provides 'header_type: The security header type name.' which adds minimal meaning over the schema's property title 'Header Type'. It does not explain possible values, how to discover them, or link to a list tool. This is largely redundant with the schema and provides little semantic enrichment.
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 function: 'Get detailed documentation for a specific clearskies security header handler.' The verb 'get' and resource 'specific security header handler' make the purpose clear. However, it does not explicitly distinguish itself from the sibling tool 'list_available_security_headers' beyond the word 'specific', so it lacks explicit 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 Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus alternatives like 'list_available_security_headers' or other get_*_info tools. The description only states what it does, not when to choose it. There is no mention of prerequisites, exclusions, or how it fits into a workflow.
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 bears full responsibility. It only states the action of getting documentation, but does not disclose whether it is read-only, requires authentication, or what behaviors or errors to expect. It adds no value beyond the obvious getter nature.
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 short and to the point, with no unnecessary verbiage. The Args block is redundant given the input schema, but the overall structure is clean and efficient.
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 simple getter with an output schema, the description is adequate at a base level, but it fails to connect to sibling tools like list_available_clients for discovering valid client_type values. The agent is left without a clear path to invoke the tool correctly.
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 adds 'client_type: The client type name,' which is slightly more specific than the schema's 'Client Type' title, but it does not list valid values, how to discover them, or provide any format details. The compensation is minimal.
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 states a specific action ('Get detailed documentation') on a specific resource ('a specific clearskies client type'), which clearly distinguishes it from the sibling list_available_clients. However, it does not explicitly name the alternative, so it misses the top 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 alternatives, nor does it mention that the client_type must come from a known list (e.g., list_available_clients). Usage is only implied by the action verb, leaving the agent to infer context.
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 for behavioral disclosure. It does not explicitly state that the operation is read-only, nor does it mention errors, permissions, or side effects, leaving the agent with minimal guidance.
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 and includes a structured Args block. While the Args block is somewhat redundant with the schema, it does not waste words and maintains clarity.
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 a simple one-parameter info tool with an output schema, the description is minimally adequate. However, it lacks context on how this tool relates to sibling tools or where to find valid result type names, and the absence of annotations leaves behavioral aspects uncovered.
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?
The description adds little meaning beyond the input schema, simply restating the parameter as 'The query result type name.' It offers no examples, valid values, or link to listing tools, which is insufficient given 0% schema description coverage.
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 function: retrieving detailed documentation for a specific clearskies query result type. It uses a specific verb ('Get') and resource, but does not differentiate it from sibling tools like get_query_info or list_available_query_results.
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 alternatives. The description only includes a parameter listing, with no context about prerequisites, complementing tools, or exclusions.
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, but it only states the check operation without mentioning side effects, error handling, or what 'compatible' means. The agent is left without important context such as whether the tool returns a boolean or raises exceptions.
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 very concise, with a one-sentence purpose and a compact Args list. It is front-loaded and contains no verbose filler. However, it could be slightly more informative while still remaining concise, so it does not earn a perfect 5.
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?
The tool is simple (one parameter) but lacks annotations and an output schema explanation. The description does not cover what compatibility means, what happens if the module is absent, or any environmental factors. Given the rich sibling context, more detail is needed for safe and correct invocation.
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?
The schema has no parameter descriptions (coverage 0%), so the description must compensate. However, the Args section merely restates the parameter name with 'The module name to check', which is tautological and adds no meaningful detail beyond the property name. It does not explain what constitutes a valid module name or how compatibility is determined.
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 checks if a module is installed and compatible, which is a specific action on a specific resource. It distinguishes itself from sibling tools like list_modules and get_module_info, which serve different purposes (listing and retrieving info, respectively).
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, nor does it mention exclusions or prerequisites. The agent must infer usage from the tool name and context, but no explicit direction is given.
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 the full burden of disclosing behavioral traits. It only states that it 'gets' documentation, implying a safe read, but it does not specify that no state is modified, what the response contains, or any potential edge cases. The lack of annotation support leaves behavioral transparency incomplete.
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, with a single sentence stating the purpose followed by a brief Args line. It is front-loaded and contains no redundant information, 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 tool has one parameter, no annotations, and an output schema (which covers return format), the description is still incomplete. It omits practical context such as how to discover valid query_type values, whether the lookup is case-sensitive, or any prerequisite steps. The absence of references to sibling listing tools further reduces completeness.
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?
The schema provides zero description coverage for the only parameter. The description adds only 'The query type name', which is a minimal clarification that largely restates the parameter's name. It does not provide examples, allowed values, or a pointer to where valid names can be found (e.g., list_available_query), so it insufficiently compensates for the schema gap.
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 action ('Get detailed documentation') and its specific resource ('a specific clearskies query builder type'). This distinguishes it from sibling tools like list_available_query which lists all types, making the purpose unambiguous.
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 provide any guidance on when to use this tool versus alternatives. It does not mention that users should refer to list_available_query to find available query types, nor does it exclude any scenarios. There is no explicit context or exclusion.
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 carries full burden. It doesn't disclose whether the tool is read-only, how it handles invalid component types, or what form the suggestions take. The bare statement 'Suggest modules' offers minimal behavioral insight.
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, containing a one-line purpose statement and a single parameter explanation. Every word earns its place, and the 'Args:' structure is clear and scannable.
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 a tool with one parameter and an output schema, the description is minimally viable but leaves context gaps. It doesn't explain what 'modules' refers to, what criteria are used for suggestion, or what the output represents beyond what the output schema might cover. It's adequate but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema only defines component_type as a string, but the description enriches it by explaining it as 'The component category' with concrete examples ('backends', 'contexts', 'models'). This is crucial given 0% schema description coverage and helps the agent use the parameter correctly.
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 function with a specific verb ('Suggest') and a resource ('modules that provide a specific component type'). It distinguishes itself from sibling tools like list_available_* by focusing on module suggestion rather than listing, though it doesn't explicitly differentiate.
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 list_modules or get_module_info. It lacks any contextual hints about use cases, prerequisites, or exclusions.
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 only says the tool returns 'detailed documentation,' leaving the agent uninformed about potential errors, read-only nature, response format, or any side effects. The name implies read-only, but that is not explicit, and no behavioral details are added beyond the minimal statement.
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 brief and front-loaded with the primary purpose. The Args section adds a small semantic but overlaps with the schema; still, it remains concise without unnecessary fluff. It earns a good score but loses a point for the redundant re-listing of the parameter.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one parameter and an output schema exists, so return values needn't be explained. However, the description lacks contextual completeness by not referencing list_available_configs for valid config_type values or explaining what a 'configuration type' is. This leaves a clear gap in the discovery workflow.
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. The Args section adds 'config_type: The config type name,' which is a minimal semantic but does not clarify where to find valid values or any format requirements. This is insufficient compensation for having no schema-level descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get detailed documentation for a specific clearskies configuration type.' This uses a specific verb ('get') and resource ('configuration type'), and the name distinguishes it from sibling tools like list_available_configs, which lists configs, and other get_*_info tools for different resource types.
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 is provided on when to use this tool versus alternatives. The description implicitly suggests it is for fetching details about a config type, but it does not mention prerequisites (e.g., using list_available_configs to see valid names) or exclusions. This is a clear but unstated usage context.
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 only says 'get detailed documentation,' implying a read-only operation, but it doesn't disclose error behavior, output format, or any side effects. For a simple info retrieval tool, some transparency is expected but not provided beyond the basic operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, with one sentence stating the purpose and a brief Args section. Every sentence provides useful information, and the structure is front-loaded and easy to scan. No unnecessary words or repetition.
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 simplicity (one parameter, output schema present), the description covers the core purpose and parameter. It doesn't explain return values, but the output schema handles that. It could mention error cases or prerequisites, but for a basic info getter, it is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description includes an 'Args' section explaining that secret_type is 'The secret type name,' adding meaning beyond the schema's plain string type. Schema coverage is 0%, so this explanation is valuable. It could be more specific (e.g., listing valid values or referencing list_available_secrets), but it adequately compensates for the lack of schema 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 gets detailed documentation for a specific clearskies secrets handler, using a specific verb and resource. It distinguishes from list_available_secrets by focusing on a specific handler rather than listing available ones, though it doesn't explicitly contrast with other get_*_info tools.
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. It does not mention that this should be used when a specific secret type is known, nor does it suggest list_available_secrets for discovery. The usage context is only implied by the 'get' vs 'list' pattern in sibling tool names.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden for behavioral disclosure. It only says 'generate' without explaining whether the tool returns a configuration object, writes to a file, mutates state, or requires authentication. No side effects or prerequisites are mentioned.
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 opens with a one-sentence purpose statement followed by a terse, well-organized Args list. Every line adds value, with no fluff or redundancy. The structure is front-loaded and efficient for an agent to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The parameter list is comprehensive, and an output schema exists so return values are covered. However, the overall behavior of 'generate' remains ambiguous, and there is no discussion of prerequisites, workflow context, or how the generated configuration is consumed. The description 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.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description is the only source of parameter meaning. It explains all 10 parameters with practical examples (e.g., endpoint_type examples, authentication format) and clarifies the role of each column list. This fully compensates for the lack of 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 'Generate a clearskies endpoint configuration' with a specific verb and resource. It distinguishes from sibling tools like generate_model, generate_context, and generate_endpoint_group by focusing on endpoint configuration.
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 alternatives such as generate_endpoint_group or scaffold_restful_api. The description only lists parameters and gives no contextual or exclusionary instructions.
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, so the description bears full responsibility for disclosing side effects. It only states the tool generates models with relationships, but does not mention whether files are overwritten, whether existing code is modified, or any potential unintended consequences. The phrase 'properly configured' lacks detail about validation or error behavior.
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 front-loaded with the primary purpose and usage, followed by a structured Args block. It is reasonably concise and avoids fluff, though the Args section could be tightened.
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 an output schema, the description lacks essential detail on how relationships are declared in the model definitions. It mentions relation types but does not explain how BelongsTo/HasMany/ManyToMany are represented in the dicts, which is critical for correctly using this tool. The completeness for a complex generation task is insufficient.
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 0% description coverage for the 'models' parameter, so the description compensates by listing expected keys (name, columns, backend_type, id_column_name). This provides meaningful structure beyond the schema, but the 'columns' sub-structure is not detailed, leaving ambiguity about column schemas.
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 'Generate multiple related clearskies Model classes with their relationships properly configured.' This specifies a concrete verb (generate) and resource (Model classes), and explicitly distinguishes from the sibling 'generate_model' by emphasizing multiple models and relationships.
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?
Provides a clear usage context: 'Use this when you need to create models with BelongsTo, HasMany, or ManyToMany relationships.' This tells the agent when to pick this tool over alternatives like 'generate_model', though it does not explicitly mention 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. It only states the action and parameter, omitting any details about return format, error behavior on unknown io_type, or side effects. This is a read-like operation, but that is not explicitly stated.
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, front-loaded with the action, and contains no redundant wording. The Args section is necessary because the schema lacks descriptions, so it 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?
The tool is simple and has an output schema, so return values are already covered. However, the description lacks guidance on how to discover valid io_type values and does not reference the sibling list_available_input_outputs tool, making discovery workflows less complete.
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 0% description coverage, but the description's Args section explains io_type as 'The input/output type name', providing basic meaning beyond the bare schema. However, it does not specify acceptable values or where to find them, so it only partially compensates for the schema gap.
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 the specific verb 'Get' and identifies the resource as 'detailed documentation for a specific clearskies input/output handler'. This clearly distinguishes it from sibling listing tools like list_available_input_outputs, which enumerate all available types.
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 requiring an io_type, but it does not explicitly state when to use this tool versus alternatives, nor does it mention that list_available_input_outputs can be used to discover valid type names. Guidance is minimal and relies on 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?
No annotations are provided, so the description carries full burden. It simply states the action without disclosing behavioral traits like read-only safety, required permissions, or return format. The description adds no context beyond what the tool name already suggests.
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 two-sentence purpose plus a compact Args block. It is front-loaded with the primary purpose and includes only necessary parameter information, with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple: one required parameter with examples in the description, and an output schema exists to document returns. It is adequate for correct invocation, though mentioning that valid inject_type names can be listed via list_available_di_inject 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 0%, so the description must compensate. It provides examples ('ByClass', 'Utcnow') for inject_type, adding concrete meaning beyond the bare schema. However, it does not explain how to discover valid values or provide further 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?
The description states it 'Get detailed documentation for a specific clearskies DI inject helper,' which clearly identifies the tool's action (get detailed documentation), the resource (DI inject helper), and scope (specific). This distinguishes it from sibling list tools like list_available_di_inject.
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 for a specific inject type via 'specific' but does not explicitly mention alternatives or exclusionary conditions. It lacks direct guidance like 'use list_available_di_inject to see all types' or 'use only when you already know the inject type 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?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It only says 'List' which implies read-only, but does not explicitly state safety, authorization requirements, rate limits, or any side effects. The lack of such detail makes behavioral transparency inadequate.
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, concise sentence that leads with the verb and clearly states the action and scope. Every word earns its place, with no waste or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple, parameterless listing tool with an output schema, the description is largely complete. It explains what is listed and that descriptions are included. However, it doesn't mention whether the list is sorted or how to interpret 'context types', but given the low complexity and existence of an output schema, this is acceptable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so schema coverage is trivially 100%. Per the rubric, a 0-parameter tool receives a baseline of 4, and no additional parameter semantics are needed. The description doesn't need to compensate for any missing parameter info.
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 available clearskies context types with a short description. The verb 'List' and specific resource 'clearskies context types' distinguish it from sibling list_available_* tools like list_available_backends or list_available_endpoints.
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 get_context_info for details on a specific context. There are no exclusions or references to sibling tools, leaving the user to infer usage from the 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 does not state whether the tool writes to disk, returns code as a string, or has side effects like overwriting files. It also lacks details on authentication handling or backend options beyond passing them through. This is a significant gap for a scaffold tool that presumably creates files.
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 starts with the core purpose, then enumerates parameters in a clean Args list. Each line serves a purpose, and the structure is scannable. It is slightly longer due to the parameter documentation, but that is necessary given the schema coverage gap.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description provides good parameter-level detail and specifies the generated artifacts (model, endpoint, context). However, it omits usage guidance, behavioral side effects, and any prerequisites or dependencies. With an output schema present, return values need not be explained, but the missing operational context keeps it from being fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description fully compensates by documenting all seven parameters in the Args block. It details the nested structure of 'columns' (name, type, options), explains the auto-generation of 'url', and lists defaults for backend_type and context_type. This adds substantial meaning beyond the bare 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 opens with 'Generate a complete, runnable clearskies REST API application for a single model,' which is a specific verb+resource+scope. It clearly distinguishes itself from sibling tools like generate_model, generate_endpoint, and generate_context by emphasizing it produces all three components in one file.
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 via 'This is a convenience tool that generates a model, a RestfulApi endpoint, and a context in a single file ready to run.' It establishes the aggregate nature but does not explicitly state when to prefer this over individual generators or mention exclusions. The sibling list makes the contrast obvious, but the description itself leaves the guidance implicit.
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 disclose behavioral traits. It only says 'Generate' without clarifying whether this returns code, writes files, or requires side effects. There is no mention of safety or expected output behavior beyond the configuration.
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 opens with a clear one-sentence purpose followed by a structured Args list. It is appropriately sized for 5 parameters and contains no filler.
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 description covers all 5 parameters and provides examples for key ones. Given the output schema exists, return value details are not needed. However, it lacks context on prerequisites (e.g., needing an endpoint first) and how to discover available context types, making it slightly incomplete.
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?
The description includes an Args section that explains every parameter: context_type with examples, endpoint_code referencing generate_endpoint output, classes/modules for DI registration, and bindings as name→value dictionary. This fully compensates for the 0% schema description coverage.
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 'Generate a clearskies context configuration that wraps an endpoint', specifying a verb and resource. This distinguishes it from sibling generation tools like generate_endpoint and generate_model by focusing on context configuration.
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 generate_endpoint_group or scaffold_project. It does not mention prerequisites or exclusion conditions.
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 carry the full burden of behavioral disclosure. It does not mention whether the tool writes files, returns code, requires an existing project, or has side effects. The description only states the generation intent without explaining observable behavior, which is a significant gap for a code generation 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 well-structured with a clear purpose sentence followed by a detailed Args list. Every sentence adds value, and the length is proportional to the tool's 6 parameters and the nested column structure. It is front-loaded and efficiently organized.
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 complexity and the presence of an output schema, the description covers input parameters thoroughly and states the purpose clearly. However, it lacks behavioral context such as output format or constraints on column types, and it does not reference related sibling tools like get_column_info for additional details. Still, for the provided information, it is reasonably complete.
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?
The schema has 0% description coverage, so the description fully compensates by providing rich details for each parameter. It explains the PascalCase requirement for name, the structure of columns with name/type/options, defaults for backend_type and id_column_name, and examples for hooks. This adds significant meaning beyond the schema's bare type definitions.
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 generates a clearskies Model class definition with a specific verb and resource. However, it does not explicitly distinguish itself from sibling tools like generate_model_with_relationships, which also generates a model. The name is specific enough, but the description lacks explicit differentiation.
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 through its detailed parameter list, but there is no explicit guidance on when to use this tool versus alternatives like generate_model_with_relationships or scaffold_project. No exclusions or alternative recommendations are provided, so guidance is only implied.
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 the full burden. It states only that it 'gets' documentation, without disclosing whether this is read-only, requires permissions, or what happens on invalid input. It also doesn't mention the output structure, though an output schema 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 one sentence plus an Args block, front-loading the main purpose. It is concise and structured, with no unnecessary words, making it easy to parse.
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 a simple one-parameter tool, the description adequately covers the purpose and parameter but lacks usage guidance and behavioral details. The existence of an output schema means return format doesn't need to be described, but the description could mention how to discover valid endpoint types (e.g., via list_available_endpoints).
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 provides only a title 'Endpoint Type' with no description. The description's Args section compensates by explaining the parameter is the name of an endpoint type and gives examples ('RestfulApi', 'Create', 'List'), adding meaningful semantics 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 uses the specific verb 'Get' and identifies the resource as 'detailed documentation and configuration options for a specific clearskies endpoint type.' It clearly distinguishes from siblings like 'list_available_endpoints' by focusing on a single endpoint type rather than enumerating them.
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 you need details about a known endpoint type ('for a specific...'), but it does not explicitly state when to use this tool versus alternatives like 'list_available_endpoints' or other 'get_*_info' siblings. It provides no exclusions or alternative tool references, so the guidance is implied rather than explicit.
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. However, it only restates the purpose ('Get detailed documentation') and does not mention what the documentation contains, whether the tool returns structured data, how it behaves for unknown function names, or any error conditions. This leaves the agent without critical behavioral context for a non-trivial lookup operation.
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: one main sentence followed by an args section. Every word earns its place, and the main purpose is front-loaded. There is no wasted wording or redundancy with the input schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has one required parameter and an output schema, so the description doesn't need to explain return values. However, it lacks guidance on how to obtain a valid func_name (e.g., via list_available_functional) and what constitutes a 'functional utility' in this context. Given the tool's simplicity, this is a minor gap but prevents a higher score.
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%, and the description provides a minimal explanation for the only parameter: 'func_name: The functional utility name.' This adds some meaning beyond the schema (which only has the title 'Func Name'), but it does not clarify where to find valid values, expected format, or relationship to sibling list_available_functional. It is barely more than a synonym.
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: 'Get detailed documentation for a specific clearskies functional utility.' This uses a specific verb ('Get') and a clear resource ('detailed documentation for a specific clearskies functional utility'), and it distinguishes itself from sibling tools like list_available_functional (which enumerates utilities) by focusing on a specific named function.
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 implies the tool is used when you know the exact name of a functional utility and want its documentation. It does not explicitly mention alternatives (e.g., 'use list_available_functional to see available names'), but the context of sibling tools and the singular 'specific' makes the use case clear. No exclusions are provided, so it falls short of a 5.
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 carry the behavioral burden. It discloses that the tool returns discovered models, handlers, errors, warnings, and a complexity assessment, suggesting it surfaces parsing issues rather than failing outright. However, it does not state whether the tool is read-only or what happens if the project path is invalid.
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 compact and well-structured with Args and Returns sections. It lists all output keys without redundancy, making every sentence useful.
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?
For a one-parameter analysis tool, the description fully covers inputs and outputs, including the structure of the returned report. It does not mention relationships to migration steps, but that is not essential for invoking this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema gives no description for 'project_path', but the description says 'Path to the v1 project directory', adding the needed meaning. It also enumerates the return dictionary keys, which clarifies what the parameter is used for.
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 function: 'Analyze a ClearSkies v1 project and generate migration report.' The verb 'analyze' and resource 'v1 project' distinguish it from sibling tools that list available components or map v1 to v2.
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 generate_v2_migration or get_migration_checklist. It simply states what it does without offering context, prerequisites, or exclusions.
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, and the description does not disclose any behavioral details beyond the basic action of retrieving documentation. It does not mention error handling, required permissions, or side effects, leaving the agent without information on failure modes.
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-loading the purpose and then detailing the parameter. No unnecessary information.
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?
This is a simple one-parameter tool with an output schema, so the description covers the essential purpose and parameter. However, it does not direct the agent to list_available_contexts for valid values, which would improve completeness.
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 no description for context_type (0% coverage). The description compensates by explaining the attribute and providing examples ('Cli', 'WsgiRef', 'Wsgi'), which adds meaningful context on what value to supply.
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 detailed documentation for a specific clearskies context type', which uses a specific verb and resource. It distinguishes itself from sibling tools like list_available_contexts by focusing on a specific context type.
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 via the word 'specific', contrasting with list_available_contexts, but it does not explicitly mention when to use this tool over alternatives. No exclusions or alternative tool references are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It implies a read-only operation but does not disclose error behavior, authentication requirements, or what 'detailed documentation' includes. It is not misleading, but it adds minimal behavioral context beyond the obvious action.
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, with a front-loaded purpose statement and a single argument explanation. Every sentence serves a purpose, and there is no unnecessary detail.
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?
For a simple one-parameter info-retrieval tool with an output schema, the description is mostly complete. It could enhance completeness by mentioning that the cursor_type should be one of the available cursors from list_available_cursors, but given the simplicity, it is sufficient.
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 has zero description coverage, so the description's 'Args: cursor_type: The cursor type name' adds some plain-language meaning. However, it largely repeats the schema's title and does not provide concrete examples, valid values, or a pointer to list_available_cursors.
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 detailed documentation for a specific clearskies cursor type,' which specifies a distinct action and resource. It differentiates from sibling 'list_available_cursors' by targeting a single cursor type rather than listing all.
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 usage context is implied: you use this tool when you need details for a specific cursor type. However, it does not explicitly mention when not to use it or point to alternatives like list_available_cursors for discovering available types.
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?
There are no annotations, so the description carries the full burden of behavioral disclosure. It only states 'Get detailed documentation,' which implies a read-only operation, but it does not describe error handling for invalid exception types, return format, or any other behavioral traits. The description is too minimal to adequately inform the agent about side effects or failure modes.
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 compact and front-loaded, with a clear one-sentence purpose followed by a standard Args section. Every element is useful and there is no redundant or filler text.
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 is simple: one required parameter and an output schema exists, so the description efficiently covers the core purpose and parameter. However, it lacks explicit guidance on when to use this tool relative to siblings and does not mention error behavior. Given the simplicity and availability of an output schema, the description is mostly complete but leaves minor gaps.
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 no description for 'exception_type' (0% coverage), but the description's Args section provides clear meaning: 'The exception type name (e.g. "InputError", "AuthenticationError").' This adds substantial value beyond the schema by explaining the exact content and providing examples.
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 function: 'Get detailed documentation for a specific clearskies exception type.' It uses a specific verb and resource, and the inclusion of example exception type names clarifies the exact target. This distinguishes it from the sibling tool list_available_exceptions, which lists exception types.
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 usage is implied: the agent should call this when it knows a specific exception type name. However, the description does not explicitly mention when to use this versus alternatives, nor does it reference list_available_exceptions for discovering available types. No direct usage guidance or exclusions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of disclosing behavior. It explicitly states the output (a list with short descriptions), which implies a read-only operation, but it does not explicitly confirm no side effects, auth requirements, or other behavioral nuances. For a simple listing tool, this is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, front-loaded with the primary action, and includes a brief clarifying sentence about the role of configuration types. Every sentence earns its place with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no parameters, clear purpose) and the presence of an output schema, the description is nearly complete. It explains what the tool returns and gives context about configuration types. It could benefit from a note about how it relates to get_config_info, but that is more of a usage guideline gap.
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 no parameters, and the schema confirms this with 100% coverage. The description does not need to explain parameters, and the baseline for zero-parameter tools is 4. It adds no parameter-related detail, which 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 lists all available clearskies configuration types and provides a short description for each. It uses a specific verb ('List') and resource ('configuration types'), distinguishing it from sibling tools like list_available_backends or list_available_columns.
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 gives no guidance on when to use this tool versus alternatives such as get_config_info or other list_available_* tools. It does not mention that this is a discovery tool for exploring available configuration types before using a specific config.
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 disclosing behavior. It documents the input parameters in detail but does not mention side effects, whether it modifies the filesystem, requirements, or error behavior. It lacks transparency about what happens beyond returning a configuration object.
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 well-structured docstring with a clear first sentence followed by an Args block. Every bullet point adds necessary information about the endpoint configuration structure. It is lengthy but justifiable given the complexity of the `endpoints` parameter.
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 description covers all three parameters and their semantics in depth, and an output schema exists for return values. However, it does not mention that `url` and `authentication` have empty-string defaults or that `endpoints` is optional (schema shows default null). This small gap prevents a perfect score.
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?
The input schema provides only types and titles (0% coverage), so the description must compensate. It does so thoroughly: for `endpoints` it enumerates all sub-fields with types and optionality, and for `authentication` it gives a concrete example. This adds substantial meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description begins with a specific verb and resource: 'Generate a clearskies EndpointGroup configuration.' This clearly distinguishes it from sibling tools like generate_endpoint (single endpoint) and scaffold_restful_api, which have broader scope.
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 a group of endpoints with a shared URL prefix and authentication, but it does not explicitly state when to use this tool versus generate_endpoint or other alternatives. No exclusions or conditions are mentioned, so the guidance is implied rather than explicit.
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 the burden of behavioral disclosure. The word 'Get' implies a read-only operation, but the description does not mention error conditions, prerequisites, or any side effects. It is minimally adequate for a simple documentation lookup but lacks depth.
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: a single purpose sentence plus the parameter explanation. Every sentence earns its place, and the parameter documentation is clear and front-loaded.
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 simplicity (one parameter) and the presence of an output schema, the description provides the essential information for selection and invocation. It lacks usage alternatives, but that is captured under usage_guidelines, and the core purpose and parameter are well covered.
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?
The schema has 0% description coverage, but the description fully compensates by explaining the single parameter 'auth_type' with examples ('SecretBearer', 'JWKS', 'SecretBasic'). This adds meaning well beyond the schema's bare title 'Auth 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 action ('Get detailed documentation') and the specific resource ('a specific clearskies authentication type'). It distinguishes from sibling tools by focusing on authentication types, unlike the broader get_*_info family targeting other resources.
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 explicit guidance on when to use this tool versus alternatives such as list_available_authentication. It only states what it does without any context about selecting it over sibling tools or when a list is more appropriate.
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 the burden. It describes the getter behavior as returning documentation, but does not disclose any details about invalid inputs, error behavior, or what the documentation includes. This is a simple read operation, so the lack of richer transparency is acceptable but leaves gaps.
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 compact and front-loaded with the core purpose. The 'Args' block repeats parameter info from the schema, which is slightly redundant, but overall it earns its place with examples.
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?
For a one-parameter getter with an output schema, the description is largely complete. It could benefit from mentioning that valid backend types are listed by list_available_backends, but given the simple nature and existing output schema, no major gaps exist.
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 schema provides no description for backend_type, but the tool description explains it with examples ('MemoryBackend', 'CursorBackend', 'ApiBackend'), adding meaningful semantics beyond the schema. It does not, however, list all valid values or point to a complete source.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'detailed documentation for a specific clearskies backend type', which is specific and differentiates from sibling tools like list_available_backends. The examples of backend types further clarify the scope.
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 you have a specific backend_type to fetch documentation, but it does not explicitly state when to prefer this over list_available_backends or other get_*_info tools. No when-not/alternatives 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It reveals that output includes descriptions and constructor parameters, but it does not explicitly state that the operation is read-only, nor does it mention behavior on missing modules or other side-effect-free guarantees. The absence of safety context for a 'get' tool 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured. It opens with a clear purpose sentence, elaborates with one sentence on behavior, then uses an Args section with examples. No wasted words; every sentence contributes to understanding the tool's purpose and parameters.
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?
For a relatively simple read-only tool with two parameters and an output schema, the description is largely complete. It covers the main functionality and gives parameter examples. A minor omission is that it does not mention whether module_name must be a previously installed module or how errors are handled, but given the output schema exists, the return values are already documented.
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?
The input schema has 0% description coverage, leaving all parameter semantics to the description. The description compensates exceptionally well: it explains module_name with a concrete example ("clearskies-aws") and category with examples ("backends", "contexts", "models"), while also clarifying that category is optional. This adds meaning well beyond the bare schema properties.
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 opens with a specific verb and resource: "Get detailed component information for a module." It clearly states that the tool lists components with descriptions and constructor parameters, and optional category filtering. This distinguishes it from sibling list_* and get_*_info tools, which are either global or focused on a single category.
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 module-scoped component listing, with module_name and optional category examples. However, it does not explicitly state when to prefer this over the sibling list_available_* tools or other get_*_info tools, nor does it mention exclusions or negative use cases.
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 must convey behavior. 'List' implies a read-only operation, and it clarifies that the output is a brief description of each handler. However, it does not mention potential output size, security implications, or whether actual secret values are exposed, which could be relevant for a secrets-related 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 compact at two sentences. The first sentence clearly states the purpose, while the second provides helpful context about secrets handlers. No redundant information is present, though the second sentence is explanatory rather than directly about tool behavior.
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?
For a zero-parameter list tool with an output schema, the description is reasonably complete. It explains what is returned (handlers with short descriptions). It might have added a note about the return format or pagination, but the output schema likely covers that. Overall, it provides sufficient context for the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the baseline is 4. The description adds no parameter-specific meaning, which is fine since there are no parameters to define. The schema coverage is 100% by virtue of having no properties.
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 'List' and a clear resource 'all available clearskies secrets handlers', and specifies that each has a short description. This distinguishes it from sibling list tools like list_available_backends or list_available_columns by focusing on secrets handlers.
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 cases (enumerating secrets handlers) but does not explicitly state when to use this tool versus alternatives such as get_secret_info for details on a specific handler. No exclusions 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral disclosure burden. It correctly implies this is a read-only documentation lookup, but it does not disclose error behavior, required permissions, or what happens if an invalid validator type is provided. For a simple information retrieval tool, this is adequate but leaves some 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 two concise sentences plus a brief argument explanation. It is front-loaded with the main purpose, contains no fluff, and every sentence contributes useful information.
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 this is a simple single-parameter tool with an output schema, the description is mostly complete. However, it could be enhanced by referencing the sibling list_available_validators as a source for valid validator_type values, but this is not essential for basic usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, but the tool description compensates by explaining that validator_type is 'the validator type name' and provides concrete examples ('Required', 'Unique', 'Email'). This adds meaning beyond the schema's bare type definition, though it could further specify case sensitivity or valid formats.
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 action ('Get detailed documentation') and resource ('a specific clearskies validator type'). It distinguishes from sibling tools like list_available_validators by emphasizing 'specific' and providing example validator names, making the scope unambiguous.
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 this tool is used when you need documentation for a specific known validator type, but it does not explicitly state when to use it versus alternatives, nor does it mention exclusions or prerequisites. No sibling tool or 'when not to use' guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavioral expectations. It clarifies that functional utilities are helper functions and decorators and indicates the tool returns a list with short descriptions. However, it does not disclose details such as sort order, result size, or network/backend access. For a read-only list operation, this is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences: the first clearly states the action and outcome, the second provides helpful background on what functional utilities are. There is no wasted text, and all information earns its place.
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?
This is a simple zero-parameter listing tool with an output schema. The description covers the tool's purpose and gives enough context about the domain. It does not need to explain return values due to the output schema, nor parameters. It is complete for its complexity, though it might have benefited from a pointer to get_functional_info for more detail.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the description does not need to explain parameter meanings. The schema is empty, and the description adds context about what is being listed, which is sufficient. The 0-parameter baseline of 4 applies.
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 ('List') and resource ('all available clearskies functional utilities') with a defined scope ('with a short description of each'). It distinguishes from siblings like get_functional_info and other list_available_* tools by focusing specifically on functional utilities.
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 states what the tool does but provides no explicit guidance on when to use this list versus alternatives (e.g., get_functional_info for detailed info about a specific utility). Usage is implied—users wanting an overview of functional utilities would use this—but no exclusions or alternative recommendations are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavior. It states that the tool returns a list with short descriptions, implying a read-only operation, but it does not explicitly affirm non-mutating behavior or address any side effects. The domain explanation adds some context, but safety expectations are not stated.
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 core action in the first sentence, and the following two sentences provide necessary domain context about handlers. Every sentence earns its place, with no redundant or filler content.
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?
For a simple listing tool with no parameters and an output schema, the description sufficiently covers purpose and domain context. It does not rely on annotations (which are absent) and adequately prepares the agent for what the tool does, though it could clarify what 'available' means (e.g., registered handlers), a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema is empty, so the baseline is 4. The description adds value by explaining what input/output handlers are, giving the agent context to interpret the returned list, even though there are no parameters to document.
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 ('List all available...'), the specific resource ('input/output handlers'), and the scope ('all available... with a short description of each'). This distinguishes it from sibling tools like get_input_output_info, which would provide detailed info on a single handler.
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 provides context about what input/output handlers are, implying this tool is for discovering available handlers. However, it does not explicitly say when to use this tool versus alternatives like get_input_output_info, nor does it mention any exclusions or specific scenarios.
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 the full burden of behavioral disclosure. It states the action 'list' which implies read-only, but it does not explicitly mention side effects, authentication requirements, or rate limits. For a listing tool, the behavior is minimally transparent but lacks explicit safety guarantees.
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 long, with the main action front-loaded. The second sentence explains the purpose of query builders, adding value without unnecessary fluff. Every sentence earns its place.
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 is simple (0 params, output schema exists), and the description sufficiently explains what it does and the context of query builders. It does not need to detail return values because an output schema is present. However, the description could briefly mention that it is a safe read-only operation.
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 since there are no parameters to document, the description does not need to add parameter semantics. The baseline for 0 params is 4, and the description does not need to compensate for any missing parameter info.
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 'List all available clearskies query builder types' with a specific verb ('list') and resource ('query builder types'), and it provides a short description of each. This distinguishes it from sibling list tools like list_available_backends or list_available_columns.
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 gives clear context about what query builders are ('used to construct database queries programmatically'), which implies when to use this tool. It does not explicitly mention alternatives or exclusions, but the extra sentence provides enough usage context for an AI agent.
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 the full burden of behavioral disclosure. It states the tool 'gets' examples and guidance, implying a read-only operation, but does not explicitly state whether it has side effects, requires authentication, or how it behaves. For a simple explain tool, this is a modest gap, but without annotations, the description should be more explicit about expected behavior and safe use.
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: one sentence for purpose and a short 'Args' block with parameter details. It is front-loaded with the main action and provides necessary parameter examples without unnecessary prose. Every sentence earns its place.
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?
For a tool with a single parameter and an output schema, the description covers the essential purpose and parameter semantics. The output schema handles return-value details, so the description is sufficient. It could add a bit more context about when to use this vs alternatives, but that is already addressed in the usage_guidelines dimension. Overall, the description is complete enough for a simple explain tool.
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?
The schema does not include a description for module_name, so the tool description fully compensates by listing the parameter and providing concrete examples ('clearskies-aws', 'clearskies-graphql', etc.). This adds meaning beyond the schema's bare type and title, making the parameter usage clear.
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 starts with a specific verb+resource: 'Get usage examples and integration guidance for a specific clearskies extension module.' This clearly identifies the tool's function and distinguishes it from siblings like get_module_info (which likely returns metadata) and list_modules (which enumerates modules). The focus on usage and integration guidance is unique among the listed sibling tools.
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 implies usage when you need usage examples and integration guidance for a clearskies module. It gives no exclusions or explicit alternatives, but the context is clear enough that an agent would know when to select it. However, it does not distinguish itself from get_module_info or suggest_modules, so it falls short of explicit when/when-not guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the return type ('Detailed explanation of the changes') but does not explicitly state side-effect-free behavior, prerequisites, or whether it analyzes a project. The verb 'explain' implies a non-mutating read operation, but this is not made explicit.
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 well-structured: a one-sentence purpose, a clear 'Args' section with bullet-like options, and a 'Returns' section. Every sentence contributes vital information, and the format is immediately scannable.
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?
For a tool with one parameter and an output schema (not detailed here), the description adequately covers purpose, parameter semantics, and return value. It does not mention when to use it relative to sibling migration tools, which is a minor gap but not critical given the simplicity and clear scope.
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?
The input schema only defines 'concept' as a string with no description or enum. The tool description compensates fully by listing all allowed values and explaining what each represents (e.g., 'model: Model definition changes'). This adds substantial meaning beyond the schema, meeting the 0% schema coverage gap.
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: 'Explain how a specific concept changed between v1 and v2.' It uses a specific verb ('explain'), identifies the resource (concept differences between versions), and distinguishes itself from siblings by focusing on version comparisons. The enumerated concept options further clarify the scope.
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 (understanding version changes) but does not explicitly state when to use this tool over alternatives like 'explain_concept' or other migration tools. There are no explicit 'when not to use' or alternative tool references, leaving the agent to infer based on the tool name and sibling list.
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 carries the burden. It states that it lists all available types with short descriptions, implying a read-only operation, but doesn't explicitly disclose safety or prerequisites. The example adds domain context but not additional behavioral 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 first sentence is a clear front-loaded purpose statement. The following context and example are relevant but slightly expand the length. Overall, it is efficient and every sentence serves a purpose.
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?
For a zero-parameter list tool with an output schema, the description adequately covers the purpose and provides usage context. The example enriches understanding. Return values are not described, but the output schema covers that.
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 zero parameters, so the description correctly omits parameter details. It instead explains the purpose and usage of authentication types, which provides useful context. Baseline for 0 params is 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'List' and the resource 'authentication types' with a short description of each. This distinguishes it from sibling tools like list_available_backends and get_authentication_info.
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 relevant context: authentication types secure endpoints and are attached via the authentication parameter, with a concrete example. It doesn't explicitly name alternatives (e.g., get_authentication_info) but the listing vs. specific info distinction is implied.
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 the burden of disclosure. 'Explain in detail' suggests a free-form informational response, but it does not explicitly state whether the operation is read-only, what output format to expect, or any other behavioral traits. However, the purpose is clear and non-destructive.
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, focused sentence followed by a clean list of valid concepts. It is front-loaded and wastes no words, making it easy to parse and understand.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one parameter, an output schema exists, and the description provides the complete set of valid inputs. There is no missing information about return values or side effects that is necessary for competent use.
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?
The schema provides zero description coverage, but the tool description fully enumerates all valid values for the 'concept' parameter. This compensates entirely for the missing schema documentation and gives complete semantic meaning.
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 ('Explain') and names the resource ('clearskies framework concept'), clearly distinguishing it from sibling tools that provide info about specific components or differences. The list of valid concepts further clarifies the 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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for conceptual explanations, but it does not explicitly state when to choose this tool over alternatives like explain_module or get_* tools. No exclusions or alternative guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of disclosing behavior. It indicates the tool lists all column types and includes short descriptions, which is useful. However, it does not explicitly state that the operation is read-only, non-destructive, or whether any authentication is required. For a simple listing tool, the behavior is largely implied but not fully disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that leads with the action and resource, followed by the valuable detail about short descriptions. No unnecessary words or repetition.
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?
For a simple listing tool with no parameters and an output schema present, the description is nearly complete. It covers what is listed and the nature of the output (short descriptions). It could be slightly more explicit about the purpose (e.g., for use in model creation), but it is sufficient for an agent to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the baseline is 4. The description does not need to explain parameter semantics. It correctly focuses on the tool's purpose and output quality (short descriptions).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'List all available clearskies column types with a short description of each.' It uses a specific verb ('list'), identifies the resource ('clearskies column types'), and differentiates itself from sibling list_available_* tools by specifying 'column types'.
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 implies the tool is used to discover available column types, but it does not explicitly state when to use it versus alternatives or mention any exclusions. The context is clear, however, and the sibling tool names reinforce the intended use case for column types.
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 carries the full burden. The word 'List' implies a non-mutating operation, and the second sentence explains the domain (security header handlers), but it does not explicitly state that no modifications occur, nor does it disclose any potential side effects, authentication requirements, or rate limits. This is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core action and resource, and the second sentence earns its place by explaining the domain. There is no wasted text or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (no parameters) and has an output schema, so the description does not need to explain return values. It provides sufficient context about what security header handlers are. A brief mention of the related get_security_header_info tool for detailed information would have improved completeness, but it is not necessary for a basic list operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the baseline is 4. The description adds context about what the listed items are, which is helpful, but there is no parameter detail to add 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 uses a specific verb ('List') plus a clear resource ('all available clearskies security header handlers'), and it states that each entry includes a short description. This clearly distinguishes it from sibling tools like get_security_header_info and other list_available_* tools.
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 implies this tool is for enumerating all security header handlers and provides context about what these handlers do. It does not explicitly mention when to prefer this over get_security_header_info or other list_available_* tools, but the 'list all' phrasing makes the primary use case clear.
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 carries the full burden. It discloses the transformation action and the exact return dictionary (v2_code, breaking_changes, notes), but does not discuss failure modes, handling of unsupported v1 syntax, or any external 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 well-structured with Description, Args, and Returns sections, and it is reasonably compact. The sentence 'Useful for understanding how specific v1 patterns translate to v2' is slightly redundant with the first sentence, but the overall layout is clear and front-loaded.
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 is simple (2 parameters, 1 required) and the description covers purpose, both parameters, and return values. An example or error-handling note would improve it, but it is sufficiently complete for an agent to select and invoke the tool correctly.
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 0%, making the Args section essential. It defines v1_code_snippet as 'The v1 code to convert' and context as "Context hint ('model', 'handler', 'di', 'general')", adding enum-like value options not present in the JSON 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 opening sentence 'Map a v1 code snippet to its v2 equivalent' clearly states a specific verb (map), resource (v1 code snippet), and result (v2 equivalent). The focus on 'code snippet' distinguishes it from project-level siblings like analyze_v1_project and generate_v2_migration.
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 offers a clear use case: 'Useful for understanding how specific v1 patterns translate to v2.' It implies when to use the tool but does not explicitly name alternative sibling tools or state when not to use it, so it misses the 'when-not' aspect of a 5.
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 carries the full burden. It discloses that the tool 'forces re-discovery of all modules', implying a cache invalidation. Yet it lacks details about side effects, safety during active operations, or error conditions, leaving notable 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 two sentences, front-loaded with the action and followed by a brief rationale. Every word earns its place, achieving excellent conciseness and structure.
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 simplicity of the tool (no parameters, output schema exists), the description adequately covers what it does and when to use it. It could mention potential side effects more explicitly, but this is not critical for such a straightforward operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so there is nothing for the description to explain beyond the schema. Per the rubric, a baseline of 4 applies, and the description does not need to add parameter details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Refresh the module discovery cache' with a specific verb and resource, and further explains 'Forces re-discovery of all modules'. This distinguishes it from sibling list/get/explain tools by indicating an action that mutates the cache state.
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 phrase 'useful after installing new modules' provides a clear context for when to use this tool. However, it does not explicitly mention alternatives or when not to use it, so it falls short of a 5.
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 the burden. It conveys that the tool retrieves documentation and constructor parameters, implying a non-mutating read operation. However, it does not disclose error behavior (e.g., invalid column_type) or any additional details, but for a simple getter this is adequate.
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 long, front-loaded with the main purpose, and uses a clear Args block for parameter details. There is no redundant text while still providing essential examples.
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?
For a single-parameter info-retrieval tool with an output schema, the description gives sufficient context about what the tool does and what input to provide. It doesn't explain return values, but the output schema handles that. Minor gaps exist around error handling, but given the tool's simplicity, it is reasonably complete.
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?
Although schema description coverage is 0%, the description compensates with a dedicated Args section that explains column_type as 'the name of the column type' and provides concrete examples ('String', 'Integer', 'BelongsToId'). This fully clarifies the parameter's meaning and expected format.
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 a specific action ('Get detailed documentation and constructor parameters') and resource ('a specific clearskies column type'), distinguishing it from sibling list tools like list_available_columns. The verb and resource are explicit, leaving no ambiguity about what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: use when you need documentation or constructor parameters for a named column type. It does not explicitly mention alternatives or exclusions, but the focus on 'specific' versus the listing siblings makes the usage context obvious.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It discloses the return type (dictionary of phases and tasks) but does not explicitly state whether the tool is read-only or has any side effects, though 'Get' implies a safe operation. It adds some behavioral context beyond the schema.
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 convey the purpose and return format with no wasted words, front-loading the verb and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with an output schema, the description sufficiently covers the tool's function and return structure. No additional context is necessary for this simple retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema is empty. Per baseline for 0 params, the description's lack of parameter info is acceptable. No parameter semantics are needed.
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 a comprehensive checklist for v1 to v2 migration, using a specific verb ('Get') and resource, which distinguishes it from sibling tools that analyze, map, or generate migration artifacts.
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 its use for obtaining a migration checklist but provides no explicit guidance on when to use it versus alternatives like generate_v2_migration or map_v1_to_v2. No exclusions or alternative recommendations are given.
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?
Without annotations, the description carries the burden of behavioral disclosure. It transparently reports what information the tool returns (installation status, version, discovered components). It also implies a read-only nature by describing documentation retrieval, though it does not mention error cases or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with the main purpose, followed by a brief summary of output content and the parameter explanation. Every sentence earns its place with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema and a single parameter, the description is mostly complete. It explains what the output will contain and the parameter format. It could be more complete by positioning itself against sibling tools, but that gap is minor for a simple info retrieval tool.
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?
The schema only defines module_name as a string with no description. The description adds significant meaning by explaining what the parameter is and providing concrete examples ('clearskies-aws', 'clearskies-graphql', 'clearskies-snyk'), making it easy for an agent to format the argument correctly.
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 ('Get detailed documentation') and the resource ('specific clearskies extension module'). It specifies what will be shown (installation status, version, components with descriptions and parameters), distinguishing it from sibling tools like list_modules or get_module_components.
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 it is for a specific module rather than listing all modules, but it does not explicitly state when to use this tool over alternatives like explain_module or get_module_components. No exclusions or alternative tool names are provided, leaving usage somewhat inferred.
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 provided, the description carries the burden of indicating safety and behavior. The verb 'List' clearly implies a read-only operation with no side effects. It also discloses that each backend will have a short description, but does not elaborate on output format beyond that.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence that conveys exactly what the tool does without any redundant or vague language. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with an output schema and zero parameters, the description is sufficient. It tells the agent what the tool returns (backend types with short descriptions) and requires no additional context for typical usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema is empty, so the description does not need to explain parameters. The baseline for 0-param tools is 4, and the description adequately clarifies the output scope ('all available...backend types').
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 the specific verb 'List' with the resource 'clearskies backend types', making the tool's purpose unambiguous. It clearly distinguishes from sibling tools like get_backend_info, which focus on single backend details rather than enumeration.
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 discovering available backends, but it does not explicitly state when to use this tool over alternatives. There is no mention of when not to use it or reference to get_backend_info for detailed information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It states that the tool lists all available client types and provides a short description of each, which conveys the read-only nature and output format. It does not mention any side effects or additional behaviors, but for a simple list operation this is adequate.
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 main purpose. The second sentence adds valuable context about what client types are for, earning its place. No redundant words or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter list tool with an output schema, the description is complete. It explains what the tool returns (all client types with short descriptions) and why they matter (HTTP/API requests). No additional context is required for the agent to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema coverage is 100% (empty schema). The baseline for 0 parameters is 4. The description adds no parameter-specific details, but none are needed.
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 verb ('List'), resource ('all available clearskies client types'), and output ('with a short description of each'). It also clarifies what client types are used for, which distinguishes it from sibling tools like get_client_info.
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 provides context about client types (used for HTTP/API requests), implying when this tool might be relevant, but it does not explicitly state when to use it versus alternatives like get_client_info or other list_available_* tools. No exclusions or explicit 'use when' guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It explains the role of cursors and states that the tool lists them, which implies a read-only operation. Yet it does not explicitly disclose safety, side effects, or any required permissions. The 'list' verb is a strong signal, but additional explicit disclosure would have improved transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long and front-loaded with the primary action ('List all available...'). The second sentence adds useful context without redundancy. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is complete for a tool with zero parameters and an output schema (which covers return values). It explains what cursors are and why they matter, providing sufficient context for selection. No gaps are evident.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the empty input schema is already fully descriptive. The baseline is 4 for no parameters, and the description does not need to add parameter details. It correctly focuses on purpose and context.
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 'List all available clearskies cursor types with a short description of each.' This is a specific verb+resource combination that distinguishes it from sibling tools like get_cursor_info, which focuses on a single cursor. The scope ('all available') is explicit.
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 on when to use this tool: 'Understanding these is useful for advanced backend customization.' This implies the intended audience and use case. However, it does not explicitly name alternatives or exclusions, so it falls short of a 5.
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?
No annotations are provided, so the description carries the full burden. The verb 'List' conveys a read-only operation, and the phrase 'with a short description of each' gives a clue about the return content. However, it does not explicitly state safety guarantees (e.g., no side effects) or any limitations, but for a list tool this is largely sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the action and resource. Every word adds value, with no redundant or irrelevant text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that the tool has no parameters and an output schema is present, the description adequately defines the tool's purpose and expected output. It is complete for a simple, side-effect-free listing utility.
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 takes zero parameters, so the description does not need to explain parameter meaning. The baseline for zero parameters is 4, and the description adds no unnecessary parameter-related content.
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 the specific verb 'List' and identifies the exact resource ('clearskies endpoint types'). This clearly distinguishes it from sibling tools like list_available_backends or list_available_columns, which target different resources.
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 the tool is used when one needs to enumerate available endpoint types, but it does not explicitly state alternatives or exclusions. There is no mention of when to choose this over list_available_backends or get_endpoint_info, leaving the usage context somewhat implicit.
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?
No annotations are provided, so the description carries the transparency burden. It clearly describes the output format (a list with short descriptions) and adds context about what query result types are. It doesn't disclose potential caveats like ordering or pagination, but for a simple listing operation this is sufficient.
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 main action, and includes a useful explanatory second sentence. Every word earns its place with no filler or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a simple zero-parameter tool with an output schema. The description fully explains what the tool does, what its return value contains, and provides background context on query result types. There is nothing missing for an agent to confidently invoke this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema is empty (0 parameters), so there is no parameter information to add. The baseline for zero-parameter tools is 4, and the description doesn't claim any parameters, which is consistent and complete.
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 ('List all available') and resource ('clearskies query result types') and clearly states what is returned (short description of each). It distinguishes itself from sibling tools by naming a distinct resource type, so the agent can immediately know its scope.
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: if you need to discover available query result types, this is the tool to call. However, it does not explicitly state when to use this versus sibling tools like list_available_query or get_query_result_info, and it doesn't mention any exclusions or prerequisites.
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 provided, the description carries the full burden of disclosing behavior. It does well by explaining that the tool analyzes the codebase, can write files (implied by dry_run description), defaults to not writing files, and returns a dictionary with specific keys (files, breaking_changes, warnings, manual_steps). It does not detail side effects like file overwriting or permissions, but for a code-generation tool this is solid transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear opening sentence, a usage tip, and labeled Args and Returns sections. Every sentence serves a purpose, and the information is front-loaded. It is concise enough for a tool with three parameters and a non-trivial return value.
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 description covers the essential aspects: purpose, main behavior, dry-run mode, and the full return structure. It could potentially mention prerequisites or edge cases (e.g., handling of non-v1 projects), but for the given complexity it is quite complete. The presence of an output schema reduces the need to describe return values, though the text already does.
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 coverage is 0%, but the description explicitly explains all three parameters: project_path is the v1 project directory, output_path is where v2 code should be generated, and dry_run controls whether files are written (defaulting to True). This adds meaningful context beyond the bare schema and fully compensates for the lack of 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 the tool's purpose with a specific verb and resource: 'Generate v2 code from a v1 project.' It further elaborates by saying it 'analyzes a v1 codebase and generates v2-compatible code.' This distinguishes it from sibling tools like analyze_v1_project or map_v1_to_v2, which analyze or map rather than generate code.
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 the tool (when you have a v1 project and want v2 code) and includes a practical usage tip: 'Use dry_run=True to preview changes without writing files.' However, it does not explicitly mention when not to use it or reference alternative tools, so it stops short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden, but 'List all available' clearly indicates a read-only, side-effect-free operation. It also explains the domain concept, though it doesn't explicitly mention any prerequisites or environment 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 front-loaded with the core purpose in the first sentence, followed by a concise explanation and a helpful example. Every section adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple zero-parameter tool with an output schema present, the description provides enough context: what the tool returns, what DI inject helpers are, and a usage example. It is complete without over-explaining.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and 100% schema coverage (empty schema), so the baseline is 4. The description adds no parameter details, but none are needed.
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 ('List') and a clear resource ('all available clearskies DI inject helpers') with a defined scope ('with a short description of each'). It clearly distinguishes from sibling tools like list_available_backends by naming the exact helper category.
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 by explaining what DI inject helpers are and gives an example, so you know when you'd need this listing. It does not explicitly name alternative tools like get_di_inject_info, but the listing-vs-detail distinction is implied.
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?
No annotations are provided, so the description carries the full burden. It transparently states the tool lists exceptions with descriptions, which is suitable for a read-only operation. It adds context about the purpose (error handling) without needing to describe return structure since an output schema 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 concise and front-loaded: the first sentence delivers the action, and the second adds relevant context. There is no wasted language.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple parameterless list operation with an output schema, the description fully covers purpose and use case. The output schema handles return structure details, so no further context is necessary.
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 takes zero parameters, so the baseline is 4. The description adds no parameter details, but none are needed since the input schema is empty.
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 'List all available clearskies exception types with a short description of each', using a specific verb and resource. It distinguishes from sibling list_* tools by focusing specifically on exceptions, making it unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains these are exceptions clearskies may raise and helps with error handling, giving a clear use case. It implies when to use this tool, though it does not explicitly mention alternatives like get_exception_info for specific exception details.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It accurately indicates a read-only listing operation and provides useful context about validator usage through the example. It does not explicitly mention non-mutating behavior, but the verb 'list' makes it obvious.
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 front-loaded with the primary purpose, followed by brief context and a relevant example. Every sentence earns its place, and the example illustrates validator usage without bloat.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple listing tool with no parameters and an output schema, the description provides sufficient context: what the tool returns, what validators are, and an example of their use. It is complete for its complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the schema provides complete coverage. The description adds useful context by explaining what validators are and showing an example, which compensates for the lack of parameter information.
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 available clearskies validator types with a short description, using the specific verb 'list' and resource 'validator types'. This distinguishes it from sibling tools that list other entities or provide detailed info.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains that validators are used to validate model data before saving and can be attached to columns, providing clear context for when to use this tool. It does not explicitly exclude alternatives like get_validator_info, but the usage context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It clearly indicates this is a read-only listing operation and specifies the kinds of data returned (installation status, version, component counts). It does not disclose potential side effects, but none are implied for a list operation.
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 purpose, and adds concise detail about the output. Every word contributes value, with no fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with zero parameters and an output schema, the description is complete. It states what is listed and the specific categories of information shown, which is sufficient given the low complexity and available output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the input schema is empty, so there is no parameter semantics to clarify. The baseline of 4 applies; the description adds no parameter information but also requires none.
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 available clearskies extension modules and summarizes what each provides. It specifies additional outputs (installation status, version, component counts), distinguishing it from sibling tools like get_module_info or explain_module that target individual modules.
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 implies the tool is for obtaining an overview of all modules, but it does not explicitly state when to use it over alternatives or mention exclusions. However, the clear listing intent and contrast with sibling get_* tools provide adequate context.
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 provided, the description carries the full burden of behavioral disclosure. It states that the tool 'Returns the full file content for a working clearskies application,' which clarifies that it returns generated content rather than performing side effects like writing files. This is a useful behavioral trait beyond the schema. However, it does not mention input validation, error cases, or any other runtime behaviors, so it is not fully comprehensive.
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 well-structured: a one-sentence purpose, a brief note on return value, and then a detailed Args section. Every sentence provides necessary information, and the detailed model structure is essential for correct usage. It is appropriately sized for the complexity of the tool and avoids fluff.
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 is complex with 4 parameters (one deeply nested), and the description covers all of them with defaults and sub-fields. It also references 'same format as generate_model' for column definitions, which helps link to sibling tools. However, it does not explicitly state which fields within the models dict are required (e.g., name and columns appear necessary but are not marked as required), which could lead to incomplete model definitions. With an output schema present, return value explanation is justifiably minimal.
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?
The schema provides only parameter names and types with no descriptions (0% coverage). The description compensates fully by explaining each parameter, including defaults for context_type and endpoint_type, and an extensive breakdown of the models parameter structure with fields like name, columns, backend_type, id_column_name, url, and various column name lists. This adds enormous meaning beyond the sparse 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's purpose: 'Generate a complete clearskies project with models and endpoints.' It uses a specific verb ('Generate') and resource ('clearskies project'), and explicitly distinguishes itself from sibling tools like generate_model and generate_endpoint by focusing on the complete project rather than individual components.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: use this to generate a complete project with models and endpoints. It does not explicitly name alternatives or exclusion scenarios, but the phrase 'complete clearskies project' implies the intended use case. Since the schema and sibling names offer context, this is clear but not exhaustive.
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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