API Tester MCP

by kirti676

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Server Quality Checklist

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Latest release: v1.5.3
Disambiguation4/5
Most tools have distinct purposes, but debug_file_system and get_workspace_info both provide workspace information, which could cause minor confusion. The descriptions help differentiate them.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern in snake_case (e.g., generate_scenarios, run_api_tests). No mixed conventions or ambiguous verbs.
Tool Count5/5
11 tools is appropriate for an API testing server. Each tool serves a clear purpose in the workflow without being excessive or insufficient.
Completeness4/5
The tool set covers the core API testing workflow: ingestion, setup, scenario/test generation, execution, and diagnostics. Minor gaps include inability to view generated content directly or delete resources, but these are not critical.
Average 3.3/5 across 11 of 11 tools scored. Lowest: 2.4/5.
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 April 7, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is failing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description should fully disclose behavioral traits. It does not mention side effects, return format, auth needs, or whether results are stored or streamed. The output schema exists but is unaddressed.
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 extremely concise (one sentence), but at the cost of omitting crucial details. It is not front-loaded with key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema and multiple sibling tools, the description does not provide enough context. The agent does not know what 'results' look like or how this tool relates to 'run_load_tests'.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 0% property description coverage, and the description adds no meaning to 'test_case_ids' or 'max_concurrent'. The agent cannot infer what these parameters do beyond the schema types and defaults.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it executes API tests and generates results. However, it does not explicitly distinguish from the sibling 'run_load_tests', relying on the word 'API' vs 'load' which is subtle.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'run_load_tests'. No prerequisites, context, or when-not-to-use information is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It only states 'execute load tests', omitting side effects, output, permissions, or any constraints. The existence of an output schema is not mentioned.
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 a single short sentence, which is concise but lacks critical detail. It earns its place but does not leverage the format to provide structured, front-loaded information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the nested input schema, lack of annotations, and an output schema (unreferenced), the description is severely incomplete. It fails to explain parameter roles, expected behavior, or return value, making it inadequate for correct tool invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not elaborate on any of the four parameters (test_case_ids, duration, users, ramp_up). Schema coverage is 0%, so the agent gets no additional meaning beyond the raw schema, which includes defaults but no explanations.
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 'Execute load tests with specified parameters' clearly states the verb (execute) and resource (load tests), but does not differentiate from sibling tools like 'run_api_tests' or 'debug_file_system'. It is specific enough to understand the general action.
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, or any prerequisites or exclusions. The agent must 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?
No annotations exist, and the description fails to disclose behavioral traits such as whether files are overwritten, permissions needed, or side effects of reusing session data.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently written in two sentences with no redundancy, clearly stating the action and a notable behavior.
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?
While the output schema covers return values, the description omits preconditions (e.g., need for a valid ingest_spec) and does not address potential destructive actions, making it adequate but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no explanation for the two parameters (project_name, include_examples) beyond the input schema. With 0% schema description coverage, this is a critical 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 generates complete project files based on ingest_spec, distinguishing it from sibling tools like generate_scenarios and generate_test_cases.
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 an ingest_spec is present and session data is available, but does not explicitly state when to avoid using it or provide alternatives among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must carry full burden. Mentions analyzing API spec but omits critical behavioral details like persistence, override behavior, security implications, or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the main verb. Efficient, though the second sentence could be more specific.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (nested object, many parameters, no annotations), the description is too brief. Missing output schema details and fails to explain how parameters interact or what the tool actually does beyond setting variables.
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 has 0% description coverage for parameters. Description only mentions 'authentication and configuration' at a high level, failing to clarify the role of each parameter (variables, baseUrl, auth_*).
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?
Cleary states it sets environment variables for authentication and configuration, with a specific verb and resource. Distinguishes from sibling tools which are about debugging, testing, and file management.
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?
Implies use for setting up environment variables with API spec context, but lacks explicit when-to-use/when-not-to-use guidance or alternatives.
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 full burden of disclosing behavioral traits. It only mentions return format (dictionary with progress details) but does not indicate safety (read vs write), idempotency, 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?
Two sentences with no extraneous words. First sentence states the core purpose, second specifies return format. Every sentence is needed and efficiently worded.
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 (no parameters, output schema exists), the description is sufficient to convey what the tool does and returns. However, it could mention any prerequisites or side effects for 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 tool has zero parameters, and the input schema is fully covered (empty). The description adds no parameter information but correctly implies no inputs are needed. For zero-parameter tools, baseline is 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves 'current session status' with 'progress details', using the verb 'Get' and a specific resource. It distinguishes from siblings like get_workspace_info by focusing on session context, though the term 'session' could be more defined.
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, nor are any conditions for use or non-use stated. The description only states what it does, 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, the description carries full burden for behavioral disclosure. It only states the return type (dictionary) and content, but does not mention side effects, required permissions, rate limits, or whether the tool is read-only. However, the simple retrieval nature suggests low risk.
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 very concise: two sentences with no extraneous information. The first sentence front-loads the purpose, and the second specifies the return format. Every word 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?
Given the tool's low complexity (no parameters, output schema present), the description is nearly complete. It specifies the return type and content. However, it could mention that the list is for test generation purposes, but this is minor.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters (0 params, 100% schema coverage), so baseline is 4. The description adds no parameter info, which is acceptable as no parameters exist. It does not detract from the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a list of supported programming languages and testing frameworks. It is specific and distinguishes from sibling tools like run_api_tests or generate_test_cases, which involve execution rather than listing.
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. For instance, it does not mention that this tool should be called before generating test cases to check language support. The description lacks explicit when-to-use or when-not-to-use instructions.
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?
The description discloses the automatic saving behavior to output directory and workspace, which is useful. However, it does not mention any potential side effects, required permissions, or whether the operation is destructive. With no annotations, this level of transparency is adequate but not 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 exceptionally concise with two sentences. The first sentence clearly states the primary action, and the second adds a critical behavioral note. No unnecessary words or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (nested params, boolean options) and the presence of an output schema (not shown), the description is adequate but incomplete. It lacks parameter details and does not describe the output format. For a tool with siblings like 'generate_test_cases', more context would be beneficial.
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 input schema has 0% description coverage, and the description does not explain the two boolean parameters ('include_negative_tests', 'include_edge_cases') or their defaults. While the parameter names are somewhat self-explanatory, the description should clarify their effect on scenario generation.
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: generating test scenarios from an ingested API specification. It effectively distinguishes from sibling tools like 'generate_test_cases' and 'generate_project_files' by specifying the input (API spec) and output (scenarios).
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 like 'generate_test_cases'. The description lacks any 'when to use' or 'when not to use' information, leaving the AI agent to infer context from sibling tool names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description is the sole source of behavioral info. It mentions automatic analysis and suggestion of env variables, which is useful. However, it does not disclose potential failures (e.g., invalid file format), side effects, or whether the spec is stored permanently. The description is adequate but not thorough.
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 concise sentences: the first states the main action and resource, the second adds a key behavior. No unnecessary words, front-loads the core purpose. Ideal length for a tool description.
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 omits important context such as file path requirements, supported formats beyond the name drop, and the relationship to other tools (e.g., ingesting before running tests). For a complex operation like file ingestion, more context is needed to avoid misuse.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It mentions 'OpenAPI/Swagger or Postman collection' which relates to spec_type, but does not clarify the other three parameters (file_path, preferred_language, preferred_framework) or their defaults. The description adds some context but insufficiently maps to the schema, especially for a tool with 4 hidden parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Ingest' and the resource 'API specification (OpenAPI/Swagger or Postman collection)'. It also specifies the source 'from a file' and an additional behavior 'automatically analyzes and suggests required environment variables'. This distinguishes it from siblings like run_api_tests or set_env_vars, which serve different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. The description implies it is for ingesting API specs, but does not specify prerequisites (e.g., file existence) or order of operations relative to sibling tools like run_api_tests or set_env_vars. The context is clear but incomplete 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description discloses the important side effect of auto-saving to both output directory and current workspace. However, it does not mention behavior when scenario_ids is null, whether files are overwritten, or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, front-loaded with the primary purpose, followed by a critical behavioral note. No unnecessary words.
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?
An output schema exists, so return values need not be explained. But the description omits parameter details and does not address the context of how scenario_ids relate to scenarios from generate_scenarios, leaving gaps for a single-parameter tool.
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 coverage is 0%, so the description must explain parameters. It mentions 'from scenarios' but does not clarify the meaning of scenario_ids, its format, or that it is optional. The agent lacks sufficient parameter guidance.
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 'generate', the resource 'executable test cases from scenarios', and the dependency on 'ingest_spec' for language and framework. This distinguishes it from sibling tools like generate_scenarios, which produce scenarios rather than tests.
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 that ingest_spec should be called first to set language/framework, but does not explicitly state prerequisites or alternatives like generate_scenarios for creating scenarios. No guidance on when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It reveals non-destructive behavior ('without creating directories') and indicates it's a read-only diagnostic. However, lacks details on response structure or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two efficient sentences, front-loaded with key purpose. Slightly vague on return details but overall concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters and output schema present, the description covers the main purpose and behavior. Could add more on diagnostics scope but sufficient.
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?
Zero parameters, schema coverage 100%. Description adds meaning by explaining the tool shows save locations without creating directories, going beyond the empty 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 gets comprehensive workspace info and file system diagnostics, including showing where files will be saved without creating directories. This distinguishes it from siblings like get_workspace_info.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this vs. alternatives. The description implies debugging file system behavior but doesn't mention when not to use it or refer to siblings.
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 explains the return format (dictionary with current directory and ingest flag) but does not disclose any other behavioral traits such as side effects, permissions, or state dependencies. The description adds basic context but lacks depth for full 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 extremely concise: two sentences that front-load the purpose and then detail the return format. Every sentence is necessary and there is zero waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters and an output schema, the description is fairly complete. It covers the key return fields. However, it omits any potential error conditions or prerequisites. Despite this, for a simple info-retrieval tool, it provides sufficient context.
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?
With zero parameters, the baseline is 4. The description adds significant value by explaining the return structure beyond the trivial input schema. It specifies that the output includes the current directory and whether it was set from an ingested API specification file, which is meaningful for the agent.
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 ('Get information') and resource ('current workspace directory and file generation locations'). It directly addresses what the tool does and distinguishes it from siblings like 'debug_file_system' or 'generate_*' which have different scopes.
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 exclusion criteria, prerequisites, or context where other tools might be more appropriate. Given the lack of usage recommendations, the score is low.
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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