@testneo/mcp-server

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v0.1.3
Disambiguation3/5
The tool set covers diverse areas, but several tools have overlapping purposes (e.g., multiple execution and batch-run tools). Descriptions help differentiate them, but an agent could still be confused when choosing between similar-sounding tools like testneo_execute_generated_test_case and testneo_run_generated_test_pipeline.
Naming Consistency3/5
All tools share the 'testneo_' prefix, but the naming pattern is inconsistent: some use verb_noun (testneo_create_web_project), others use noun_verb combinations (testneo_api_project_openapi_impact) or longer phrases (testneo_figma_to_tests_workflow). While readable, the lack of a strict convention reduces predictability.
Tool Count2/5
With 48 tools, the server is excessively large for typical use. Although the domain is broad, this count is likely overwhelming and indicates a lack of focus, potentially leading to agent confusion and performance issues.
Completeness2/5
The tool set covers creation, reading, and some updating across multiple entities, but critical delete operations are missing for projects, test cases, contexts, and environments. This gap means agents may need fallback strategies or fail when attempting to clean up resources.
Average 3.3/5 across 48 of 48 tools scored. Lowest: 2.3/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 10 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under GPL 3.0.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

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

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

How is the quality score calculated?

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

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

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

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

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description should disclose safety, auth, and side effects. It mentions polling and return values but omits whether the tool is destructive, requires authentication, or has rate limits.
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 dense sentence that covers many aspects but lacks structure. It is front-loaded but could benefit from bullet points or clearer segmentation.
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?
Without output schema and with conflicting parameter info, the description is incomplete. The tool as defined cannot be used correctly because the schema denies the described parameters, leaving the agent without a valid invocation path.
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 input schema has 0 parameters, yet the description references multiple parameters (test_case_id, project_id, name_query, etc.). This is a critical mismatch that misleads the agent into expecting inputs that don't exist.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool executes a generated test end-to-end, but the input schema has zero parameters, contradicting the described inputs like test_case_id and project_id. This inconsistency undermines clarity.
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 mentions using test_case_id OR (project_id + name_query) and optional wait_for_agent_seconds, and references a sibling tool, but it lacks explicit guidance on when to choose this tool over 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?
No annotations provided, and the description does not disclose side effects, duration, or whether the workflow modifies data. The term 'agentic' hints at AI-driven decisions but lacks specifics.
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 sentence, front-loaded with the workflow types. But it is too brief and omits critical details, making it efficient but insufficient.
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 no output schema, no annotations, 5 undocumented parameters, and multiple sibling tools, the description fails to provide enough context for an AI agent to use the tool correctly.
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?
Schema description coverage is 0%, and the description adds no information about any of the 5 parameters (e.g., workflow_type, project_id, range). The agent cannot infer parameter meaning from the tool description.
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 runs a multi-step QA workflow and lists the three workflow types, distinguishing it from single-step run tools like testneo_run_api_test_chain. However, it could be more explicit about the composite nature.
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 vs alternatives. With many sibling run tools (e.g., testneo_run_batch_by_tags, testneo_run_generated_test_pipeline), the absence of usage context is a significant gap.
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; the description does not disclose whether this is a read operation, potential side effects, or output format. The word 'summarize' implies aggregation but lacks clarity on behavior.
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?
Single sentence, concise but lacks structure. No breakdown of key information; it is adequate in length but missing essential details.
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 3 parameters, no output schema, and no annotations, the description is severely incomplete. Does not cover what the trend output looks like, pagination, or error conditions.
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?
Schema description coverage is 0%; the description does not explain any parameter. Only 'date range' hints at the range parameter, but project_id and limit are entirely unexplained.
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 'Summarize' and the resource 'pass/fail trend', specifying scope 'for a project over a date range'. It is specific and distinguishes from sibling tools like 'testneo_get_execution_summary' which summarizes a single execution.
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 such as 'testneo_search_failures' or 'testneo_get_execution_logs'. No context on prerequisites or limitations.
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. Description only states 'List recent executions' without disclosing behavior such as ordering, read-only nature, pagination details, or what fields are returned. With no annotations, the description carries the full burden and falls short.
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?
Single sentence is concise but sacrifices necessary detail. It could be restructured to front-load the core action while adding brief notes on pagination and return format.
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 6 parameters, no output schema, and no annotations, the description is incomplete. It does not explain return value format, pagination behavior, or how results are ordered. Missing critical context for effective use.
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 6 parameters with 0% description coverage. Description only lists filter fields (project/status/release/build) but does not explain their semantics, valid values, or constraints. For example, status_filter is ambiguous. Parameters like limit and offset exist but are not mentioned in description.
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 'List recent executions' with optional filters. However, it does not differentiate from sibling tools like get_execution_logs, get_execution_status, or get_execution_summary, which could also list executions with specific 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?
No guidance on when to use this tool versus alternatives like testneo_get_execution_logs or testneo_get_execution_status. The description implies it is for recent executions but does not specify exclusion criteria.
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 must carry the burden. It mentions extraction and execution via Playwright SDK, but does not disclose side effects, safety, rate limits, or whether it is read-only or destructive. The behavior is only superficially described.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words. However, it could be structured to front-load the core action and add details without losing conciseness. It earns points for being short but loses some for not being optimally informative.
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 no output schema and 0% parameter coverage, the description is incomplete. It explains the high-level process but fails to provide enough context about inputs, outputs, and how it fits into the workflow. The tool complexity (6 params, execution endpoint) demands more detail.
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?
Schema description coverage is 0%, and the description does not explain any parameter (project_id, test_name, playwright_spec_ts, mode, confirm, idempotency_key). The agent must infer from names alone, which is insufficient for correct usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (run a preview) and the resource (Playwright SDK spec). It distinguishes from siblings like testneo_export_playwright_spec (export) and testneo_trigger_playwright_execution (trigger different execution). However, 'preview' is not explicitly defined, leaving some ambiguity.
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. The description does not mention prerequisites, when-not-to-use, or context for choosing this tool over similar siblings like testneo_run_batch_by_tags or testneo_trigger_playwright_execution.
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?
Without annotations, the description must reveal behavioral traits. It implies a read operation ('fetch') but lacks details on side effects, auth requirements, rate limits, or error cases. This is minimal for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with 11 words, highly efficient. However, it could be slightly more descriptive without being verbose; current conciseness sacrifices some informational value.
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 lack of output schema, annotations, and schema descriptions, the description is insufficient. It does not indicate return values, response structure, or how the tool handles errors. The agent would need to look elsewhere for basic usage understanding.
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 'execution ID' but does not describe the 'include_steps' parameter (boolean, default true). The agent cannot infer what 'include_steps' controls from the description alone.
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 verb 'fetch' and the resource 'primary execution status, steps and summary metadata' for an execution ID. It is specific about what data is retrieved, but does not explicitly differentiate from sibling tools like get_execution_summary or get_execution_logs.
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 does not mention prerequisites, exclusions, or context in which this tool is preferred.
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 fully inform about behavioral traits. It lists pipeline stages but omits side effects, authorization needs, idempotency, or resource cleanup. For a mutation-heavy workflow, this lack of disclosure 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.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence listing the workflow steps, which is concise but not wasteful. However, it lacks structure such as bullet points or grouping, and could be more informative without becoming verbose.
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 (8 parameters, no output schema, many siblings), the description is insufficient. It does not explain the flow between steps, input/output relationships, or what the preview entails. The high-level summary leaves major gaps for an AI agent.
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?
Schema description coverage is 0%, meaning the input schema provides no property descriptions. The tool description adds no explanation of parameters beyond their names and constraints (e.g., project_id, figma_token), leaving the agent without needed semantic 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 it is an end-to-end workflow with specific steps: ingest Figma, create unified context, generate tests, and preview NLP + Playwright drafts. This distinguishes it from sibling tools that perform individual steps or a variant (testneo_figma_image_to_tests_workflow).
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 implicitly suggests using this tool when an integrated workflow is desired, but it does not explicitly state when to use this tool versus its siblings. No prerequisites or exclusions are mentioned, relying on the schema for required parameters.
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 must disclose behavior. It only states the basic operation without mentioning side effects, authentication needs, rate limits, or response format. The agent lacks crucial behavioral cues.
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 one short sentence with no redundancy. It is front-loaded and gets to the point, but it could benefit from additional context without being verbose.
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 no annotations, no output schema, and 0% schema coverage, the description is incomplete. It does not describe pagination behavior, log format, error handling, or how logs relate to other execution data. A log retrieval tool requires more context for correct usage.
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 implicitly explains 'execution_id' by mentioning 'for an execution ID', but 'limit' and 'offset' are not explained. Their names are self-explanatory, but the description adds no value beyond the schema structure.
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 resource (execution logs) with a specific identifier (execution ID). It distinguishes from sibling tools like testneo_get_execution_status and testneo_get_execution_summary by focusing on logs.
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 sibling tools (e.g., status, summary, failure bundle). The agent must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It does not disclose any behavioral traits such as what happens if the route map does not exist, authorization needs, 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.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence, but it is too brief and lacks structure. It could be more informative without losing conciseness.
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 simple parameter set and no output schema, the description is minimally complete. It does not explain the return format, behavior on missing data, or how it relates to sibling tools.
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%. The description adds no meaning to the single parameter (project_id) beyond what the schema already provides. It fails to explain acceptable values or usage 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 action ('Get') and resource ('project-level MCP route-hardening map/profile'), and the sibling tool testneo_set_project_route_map provides a clear distinction as a setter counterpart.
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 testneo_set_project_route_map or testneo_apply_route_hardening. There is no mention of prerequisites or context for use.
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. It lists outputs but fails to disclose side effects, authorization needs, error behavior, or other behavioral traits. For a tool that likely modifies state (PR validation planning), this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, front-loading the purpose effectively. However, it could benefit from a structured format with sections for usage and outputs.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (8 parameters, nested objects, no output schema or annotations), the description is incomplete. It does not explain how to construct the input, what the output will look like, or any prerequisites, leaving significant gaps.
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%, yet the description does not explain any of the 8 parameters beyond hinting at 'diff or git refs'. It adds no meaning beyond the schema's basic structure, leaving the agent to infer parameter usage.
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 runs 'TestNeo PR validation planning' from 'diff or git refs' and returns specific outputs like impacted tests and verification stages. It uses a specific verb ('Run') and resource, making the purpose distinct from 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 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, nor does it mention prerequisites or when not to use it. Sibling tools exist (e.g., testneo_run_agent_workflow), but no differentiation 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, so description carries full burden. States guardrails and endpoint, but does not explain idempotency, overwrite behavior, return values, or errors. Limited beyond basic write indication.
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 stating purpose, guarding, and endpoint. No redundant information; every sentence adds value.
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 6 parameters, no output schema, and no annotations, the description severely lacks context. Does not explain parameter roles, expected response, or edge cases, making it incomplete for reliable use.
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?
Schema coverage 0% with 6 parameters. Description mentions none of the parameters, leaving agent to infer from names only. Fails to add meaning beyond 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?
Description explicitly states 'Persist a named API test chain', clearly defining its role. Differentiates from siblings like delete_saved_api_test_chain and run_api_test_chain by focusing on creation/persist.
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?
Mentions guarded write and confirmation requirement, but does not compare with alternatives or specify when to use (e.g., for new chains vs updates). Implies usage context but lacks explicit 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 that it persists modified spec bytes and requires confirmation (confirm=true) for the write operation. However, it does not detail other behavioral aspects such as idempotency, reversibility, or what happens when confirm is false.
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 front-loaded with the main purpose. It covers the action, outcome, persistence, guard, and backend endpoint in a few sentences. Minor improvement could be adding structure like bullet points or parameter mentions.
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 5 parameters, no output schema, and no annotations, the description is incomplete. It does not explain what the tool returns (e.g., list of impacted tests), nor does it provide parameter semantics. The agent lacks essential context to use the tool effectively.
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 schema description coverage is 0%, meaning no parameter descriptions are provided in the schema. The tool description does not explain any of the five parameters (project_id, swagger_file_base64, swagger_filename, confirm, idempotency_key), leaving the agent without crucial contextual meaning for correct invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Compare', the resource 'uploaded Swagger revision against the last snapshot', and the outcomes 'diff endpoints' and 'list impacted swagger-sourced NLP tests'. It distinguishes itself from siblings by specifying the analysis focus and persistence behavior.
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 like testneo_swagger_impact_actions or testneo_swagger_preview. It mentions a guard condition but 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.
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 behavioral traits such as read-only nature, pagination behavior, or response format. The description only states 'lists projects,' leaving the agent to infer safety and 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?
A single, clear sentence with no unnecessary words. It is appropriately front-loaded 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?
Given the lack of output schema and annotations, the description should provide more context about pagination and response structure. It is insufficient for a tool with two undocumented parameters.
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?
Schema coverage is 0%, with no descriptions for the 'limit' and 'offset' parameters. The description adds no meaning or guidance for these parameters, leaving the agent to guess their usage based only on JSON schema types and 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 clearly states it lists projects and specifies the scope ('available to the current API key user'), distinguishing it from sibling list tools like testneo_list_recent_executions or testneo_list_tests_by_tags.
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 retrieving projects, but provides no explicit guidance on when to use this tool versus alternatives like testneo_list_unified_contexts. No exclusions are mentioned.
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 exist, so the description carries the transparency burden. It discloses that the tool may flag tests, requires confirmation (confirm=true), and specifies the backend endpoint. However, it does not detail side effects (e.g., whether the spec is saved, how existing tests are affected, or what 'impact analysis' entails operationally).
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 (three sentences) and front-loaded with the core purpose. Each sentence adds essential information: the action, the parameter usage, and the guarding requirement. No redundant or extraneous content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (6 parameters, no output schema, no annotations), the description is insufficient. It lacks explanation of the output, the meaning of business_rules and auto_flag, and the overall workflow. The high number of parameters and the potential for internal state changes are not addressed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must explain parameters but only elaborates on openapi_spec. It omits explanations for project_id, auto_flag, business_rules, confirm, and idempotency_key, leaving their semantics unclear despite the schema providing names and types.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: running OpenAPI impact analysis for API (non-web) test cases against a new or stored spec. It differentiates from web-focused siblings by specifying 'API (non-web)', but does not explicitly compare with other impact analysis tools like testneo_swagger_impact_analysis.
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 explains when to pass openapi_spec (to diff an inline revision) versus omit (use stored spec), and mentions the 'confirm=true' requirement for guarded operations. However, it does not provide guidance on when not to use this tool, nor does it reference alternatives among sibling tools.
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 fully disclose behavior. It mentions write operation and confirmation requirement, but omits important traits like exact effects of confirm flag, idempotency key behavior, and potential 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, 33 words, no filler. Could integrate more parameter info without becoming verbose.
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?
No output schema and no return value description. For a creation tool, missing info on what is returned (e.g., environment ID). Does not fully cover all 7 parameters' roles.
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?
Only the 'variables' parameter is contextualized with the NLP example. The other 5 parameters (project_id, name, is_default, is_active, confirm, idempotency_key) lack description. With 0% schema coverage, description should compensate more.
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?
Clear verb 'Create' and resource 'web project environment', with specific mention of optional variables for NLP base_url. Distinct from sibling tools which focus on tests, queries, etc.
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?
Provides context that it is a guarded write requiring confirmation, but does not explicitly state when to use vs. alternatives or when not to use. No sibling differentiation.
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 fully convey behavior. It only says 'Export', implying a read-only operation, but doesn't specify side effects, required permissions, rate limits, or response format, leaving the agent with ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no unnecessary words, front-loaded with key action and output format.
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 no output schema, the description is minimal but could be improved by noting the return type or that the spec text is returned directly. Still adequate for a straightforward export function.
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%, and the description does not add any meaning to the 'test_case_id' parameter beyond its type. No context is given about what constitutes a valid ID or how to obtain it.
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?
Description clearly states the verb 'Export' and the resource 'test case' with the output format 'Playwright SDK TypeScript spec text', distinguishing it from siblings like run_playwright_spec_preview or trigger_playwright_execution.
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. Doesn't mention when not to use it or provide context about prerequisites or typical workflow integration.
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 carries the burden. It discloses that the tool retrieves analytics summary with specified fields, but does not mention other behavioral traits such as read-only nature, idempotency, or potential rate limits. Adequate but could add more context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence that is front-loaded with the core action and includes supporting details in parentheses. No wasted words, highly efficient.
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 retrieval tool with one parameter and no output schema, the description hints at the return content but does not specify the response format or error conditions. Adequate but incomplete; an output schema would help.
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?
Schema description coverage is 0% and the description does not explain the execution_id parameter beyond the schema's minLength. It adds no value in clarifying the parameter's purpose or format, leaving the agent to guess.
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 an analytics summary for an execution, listing specific components (status, pass/fail, duration, video metadata), which distinguishes it from sibling tools like testneo_get_execution_status (just status) and testneo_get_execution_logs (logs).
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 siblings. The description implies it's for a broad summary but does not explicitly state when to choose it over the status or logs tools, leaving the agent to infer.
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 burden. Only mentions 'calls list internally' but does not disclose read-only nature, error behavior, 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 purpose. Minor informality in 'calls list internally' but overall 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?
Given 5 parameters, no output schema, and no annotations, the description lacks explanation of return values, error cases, and parameter details.
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% coverage; description only refers to 'natural-language name' and does not explain parameters like match_mode, prefer_context_id, include_detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it resolves unified context_id from a natural-language name, specifying the action and resource. Distinguishes from sibling list_unified_contexts by hinting at internal lookup.
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?
Says 'Great for onboarding and demos' but does not explicitly state when not to use it or provide alternatives like list_unified_contexts.
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 bears full responsibility for behavioral transparency. It mentions ETL ingestion and optional waiting, but omits details about destructive potential, authentication requirements, error handling, or the linked context creation process.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that efficiently conveys the tool's purpose and key steps. However, a slightly more structured format (e.g., listing parameters or steps) could improve clarity without sacrificing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (8 parameters, no output schema, no annotations), the description is insufficient. It fails to explain required vs. optional parameters, the ETL process, or the outcome of creating 'linked unified context', leaving significant gaps 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?
The input schema has 8 parameters with 0% description coverage, yet the description provides no parameter-specific information. It fails to clarify what each parameter means or how they interact, such as the role of figma_token, figma_file_id, or wait_for_ingest.
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 ingests Figma metadata via ETL, optionally waits for completion, and creates a linked unified context for test generation. It distinguishes from siblings like testneo_figma_to_tests_workflow by focusing on metadata ingestion and context creation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when needing to create a unified context from Figma metadata, but provides no explicit when-to-use or when-not-to-use guidance, nor does it mention alternatives among the many Figma-related sibling tools.
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 labels the action as 'guarded write', hinting at potential guardrails (e.g., the confirm parameter). However, with no annotations, it fails to disclose details like idempotency, rate limits, or side effects on test results, leaving significant behavioral 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?
A single sentence with a clear verb and resource, front-loaded and free of unnecessary words. Could potentially be split into two sentences for better readability, but overall effectively concise.
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 no output schema and five parameters with no descriptions, the description fails to explain expected return values or the rerun outcome (e.g., execution IDs, success status). It is incomplete for an agent to correctly invoke and interpret results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage and no mention of parameters in the description (except indirectly implying project_id via 'for a project'), the description adds minimal value. Parameters like limit, confirm, range, and idempotency_key remain unexplained, forcing the agent to rely solely on schema 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 clearly states the tool reruns failed tests for a project, specifying the verb 'rerun' and resource 'failed tests for a project'. It also notes the underlying endpoint and that it's a 'guarded write action', which distinguishes it from read-only or non-write 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 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 tool versus other execution-related siblings (e.g., testneo_run_generated_test_pipeline). The description does not mention prerequisites, exclusions, or alternative tools, leaving the agent to infer usage from 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?
No annotations exist, so description must bear the burden. It only states what the tool does but not behavioral aspects like whether results are paginated, what happens on empty results, or any 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?
Single sentence, no unnecessary words. Front-loads core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and 0% schema coverage, the description provides minimal context. It omits output format, pagination, and error conditions, but captures essential search capability.
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 description must compensate. It explains 'query' can be a test name or execution ID, but project_id and limit receive no explanation.
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 searches for failed executions within a project using either test name or execution ID. It distinguishes from siblings like testneo_find_test_cases which targets test cases, and testneo_get_execution_summary which is summary-focused.
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 vs alternatives. It does not mention when not to use it or describe prerequisites (e.g., having a project ID).
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. The phrase 'guarded write action' hints at protection but lacks details on authentication, rate limits, or side effects. No mention of response behavior or error conditions.
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 efficiently communicates the core action. It front-loads the primary purpose without extraneous words.
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 tool's complexity (7 parameters, nested objects, enums, no output schema), the description is severely incomplete. It fails to explain parameter semantics, return values, or usage details, leaving agents with insufficient information for 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?
Schema coverage is 0%, yet the description adds no parameter explanations. Only 'profile' and 'enabled' are vaguely referenced; critical parameters like 'extra_map', 'merge_mode', 'confirm', and 'idempotency_key' remain unexplained, leaving the agent to guess their 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 clearly states the verb 'Persist' and the resource 'project-level route-hardening map/profile', with a specific target location. It differentiates from siblings like 'testneo_get_project_route_map' and 'testneo_apply_route_hardening' by emphasizing the write action and guarded nature.
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 a write action but does not explicitly state when to use or not use this tool versus alternatives. No exclusions or context for when to prefer read or apply siblings 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?
With no annotations, the description alone must disclose behavioral traits. It states the tool is a write operation and requires confirm + allow-write, providing basic safety info. However, it omits details on side effects, rate limits, or error handling, limiting 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 a single concise sentence of 12 words that is front-loaded and contains no filler. Every word is necessary and informative.
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 6 parameters, 3 required, no output schema, and no annotations, the description is too brief. It fails to provide usage examples, parameter guidance, or sufficient detail to ensure correct invocation, making it incomplete for an 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 should compensate. It only mentions 'confirm' implicitly but does not explain any parameter meanings beyond the schema. This adds minimal value for understanding parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool triggers NLP execution via Playwright SDK and identifies as a write tool requiring confirm and allow-write. It distinguishes from siblings by specifying 'Playwright SDK' and 'NLP execution', though could be more explicit about 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 indicates when to use (for write operations requiring confirmation) but does not explicitly state when not to use or provide alternatives among sibling tools. The context is clear but lacks exclusions.
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 indicates the tool polls and stops at terminal status or timeout window, but lacks details on what terminal status means, what happens on timeout, rate limiting, or return value characteristics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence. It is concise, though it could benefit from slightly more detail to improve completeness without becoming verbose.
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 5 parameters and no output schema or annotations, the description is insufficient. It omits critical details about polling behavior, termination conditions, timeout handling, and return format, which are essential for proper use.
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?
With 0% schema description coverage, the description should add meaning to the 5 parameters, but it does not. It only mentions 'execution summary' broadly, leaving max_polls, poll_interval_ms, include_event_sample, and event_sample_limit completely unexplained.
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 (poll) and resource (execution summary) with a specific goal (until terminal status or timeout). This distinguishes it from sibling tools like get_execution_status which are one-shot retrievals.
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 the tool is used when you need to wait for an execution to finish, but it does not explicitly compare to alternatives like get_execution_status or get_execution_summary, nor does it provide conditions for 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. It only states that the tool lists contexts with id and names, but omits details on output format, pagination, error handling, or any side effects. For a list tool, this is insufficient.
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, each serving a distinct purpose: stating the action and providing usage context. No unnecessary words.
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 three parameters and no output schema, the description is very brief. It does not cover what the tool returns, how parameters affect output, or any constraints. The overall context is incomplete for effective tool selection and use.
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 explain any of the three parameters (project_id, compact, max_compact_lines). With 0% schema description coverage, the description fails to add meaning beyond the schema, leaving agents without guidance on optional 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 tool lists unified contexts for a project with IDs and human-readable names, and explicitly mentions its use as a precursor to testneo_generate_tests_from_context. This differentiates it from sibling tools like testneo_get_unified_context_by_name.
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 explicitly advises using this tool before testneo_generate_tests_from_context and explains the benefit (avoid scraping context_id from UI). It provides clear context of use, though it does not mention when not to use or alternative tools.
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?
Description reveals guarded nature (require write and confirmation) and snapshot promotion, but fails to mention return format, failure modes, or side effects of actions. With no annotations, more detail is needed.
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-load purpose and key information. No wasted words.
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?
Omits response format, error conditions, prerequisites (e.g., existing project), and detailed behavior of each action. With 4 parameters and no output schema, the description is too sparse.
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?
Only actions and confirm are hinted at in description; critical parameters project_id and idempotency_key are not described. Given 0% schema coverage, this is insufficient.
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 applies impact triage on web test cases with specific actions (mark_stale, archive, keep) and promotes a modified spec snapshot. It distinguishes itself from sibling testneo_swagger_impact_analysis by being an action-oriented tool.
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 tool versus alternatives. Mentions 'guarded: allow-write + confirm=true' as a safety feature but does not explain when it's appropriate to use or when to choose another tool.
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 fails to mention what the tool produces (e.g., returns test cases? saves them? side effects?). It discusses auth and route maps but omits the outcome of the generation process.
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 front-loads the core purpose, but the second half dives into low-level configuration details that could be placed in the schema. It is somewhat verbose for a description, with three paragraphs covering many edge cases.
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 has 16 parameters, nested objects, and no output schema. The description does not explain the return value or the overall effect (e.g., do tests get saved or just returned?). It lacks completeness for an AI agent to reliably invoke it.
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?
With only 6% schema description coverage, the description must compensate. It explains auth_preamble and context resolution well, but ignores most of the 16 parameters (e.g., test_types, max_tests, focus_areas). Thus it adds value on a few key parameters but leaves many others undocumented.
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 that the tool generates NLP test cases from an existing unified context, which distinguishes it from context-creation tools like testneo_ingest_figma_context. However, it does not explicitly differentiate from other test-generation tools like testneo_figma_to_tests_workflow, so the distinction is slightly opaque.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool (after resolving context via list or get), when not to use it (public/no-login apps omit auth_preamble), and suggests alternative tools for custom route mapping (testneo_set_project_route_map). This is comprehensive.
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 provided; description covers write requirement, polling for agent, environment variable behaviors (TESTNEO_MCP_*), and underlying API calls. Lacks details on success/failure but is fairly transparent.
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?
Description is front-loaded with purpose and contains necessary operational details without excessive verbiage. Could be slightly shorter but remains focused.
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 complexity (12 params, no output schema, no annotations), the description covers core behavior but leaves many parameters unexplained. Sufficient for basic use but gaps exist.
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%; description only adds meaning to tags, confirm, and wait_for_agent_seconds. Most parameters (project_id, tag_match, idempotency_key, etc.) are not explained, leaving the agent to infer from schema alone.
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 creates and executes multi-test runs for tags, with specific verb and resource. It mentions resolving tags like testneo_list_tests_by_tags, but does not explicitly differentiate from other run-related siblings (e.g., testneo_run_api_test_chain).
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?
Provides clear context: write permission needed, confirm=true required, and local agent handling. Does not explicitly state when not to use or name alternatives beyond referencing testneo_list_tests_by_tags.
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 mentions returning a 'verification snapshot' and optionally rewriting commands, but does not disclose whether the update is destructive, whether idempotency is enforced (though an idempotency_key parameter exists), or any side effects. The description adds some behavioral context but is incomplete.
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 succinctly convey the core action and an optional feature. The description is front-loaded with the main purpose. However, the structure could be improved by listing parameters or providing a clearer separation of required vs optional behavior.
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 5 parameters, no output schema, and no annotations, the description should provide more context about return values, default behavior when route_hardening is omitted, the role of idempotency_key, and whether the update is incremental or overwriting. The current description leaves significant gaps for an agent to use 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%, and the description does not explain individual parameters beyond implying test_case_id and nlp_commands are used. The complex nested route_hardening object is not described, and the purpose of idempotency_key is omitted. The description adds minimal value over the schema's raw structure.
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 ('Update NLP commands'), the specific resource ('for a specific test case ID'), and the return value ('return verification snapshot'). It also mentions an optional feature ('optionally rewrites Navigate-to lines using route hardening'), which distinguishes it from sibling tools like testneo_apply_route_hardening that handle route hardening separately.
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 mentions that route hardening is 'same env / route_hardening as generate', implying consistency with another tool, but does not explicitly state when to use this tool versus alternatives like testneo_apply_route_hardening or testneo_generate_tests_from_context. No when-not-to-use or prerequisites 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?
With no annotations provided, the description must disclose behavioral traits. It mentions validation, creation, optional environment, and returns a trace plus recommended tools. However, it lacks details on mutation aspects, required permissions, idempotency, or rollback. 'Guarded like other writes' is vague.
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 convey the core purpose, key constraint, and output. It is front-loaded with 'One-shot onboarding' and contains no unnecessary words.
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 10 parameters, no output schema, and no annotations, the description is insufficient. It does not explain the full workflow, validation details, or the meaning of required fields like name and website_url. The return value is only vaguely described.
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 'add_base_url_variable' and 'base_url + credentials' but does not clarify other parameters like confirm, idempotency_key, environment_username, etc. The description adds minimal value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: one-shot onboarding that validates and creates a web project with an optional default environment. It uses specific verbs and distinguishes from siblings like testneo_create_web_project and testneo_create_web_project_environment by combining both steps.
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 hints at when to use the environment part ('when add_base_url_variable=true') and says 'Guarded like other writes' but does not explicitly advise when to choose this tool over the separate create tools. Usage context is implied but not clearly delineated.
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 disclose behavioral traits. It outlines the main steps (upload, wait, create context, generate, preview) and mentions the backend endpoint and method (POST multipart). It also notes the guard requiring write permission and confirmation. However, it does not describe error handling, latency expectations, idempotency behavior, or what happens to existing contexts. The description adds value but leaves significant gaps in transparency.
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 moderately concise at three sentences. It front-loads the core purpose and flow, but includes extraneous details like the specific backend endpoint and multipart field, which may not be necessary for the agent. It could be more streamlined by omitting implementation details and focusing on user-facing guidance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (15 parameters, no output schema, no annotations), the description is incomplete. It does not explain return values, error conditions, prerequisites (e.g., valid image format, required fields), or how the preview step works. The agent would lack critical information to assess whether results are successful or handle failures, making the description insufficient for contextual understanding.
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 15 parameters with 0% description coverage, meaning the JSON schema provides no explanations. The tool description fails to compensate: it does not explain individual parameters like project_id, image_file_base64, context_name, figma_json_id, enrich_context_id, or idempotency_key. Only a high-level flow is provided, leaving the agent to infer parameter meanings from names alone. This is insufficient for correct invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: upload an exported UI image (PNG/JPEG/GIF/WebP) and run a workflow that includes vision ETL, creating unified context, generating tests, and previewing. It distinguishes itself from sibling tools by explicitly saying 'No Figma token', indicating this is for cases where a Figma access token is not available, unlike testneo_figma_to_tests_workflow which likely uses a token.
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 context by stating 'No Figma token', guiding users to choose this tool when they don't have a Figma token. However, it does not explicitly list alternatives (e.g., testneo_figma_to_tests_workflow) or provide when-not-to-use guidance. The mention of 'Guarded: TESTNEO_MCP_ALLOW_WRITE + confirm=true' hints at required precautions but lacks formal exclusion conditions.
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?
Discloses read-only status and search matches name/description per API rules. Lacks details on pagination, sorting, rate limits, error conditions, or return format beyond id and name.
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 efficiently convey purpose, usage guidance, and behavioral note. No redundant or extraneous content.
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?
Covers basic purpose, API endpoint, and how to chain with sibling tools. Missing details about return structure (beyond id, name), potential errors, and empty results. Adequate for a simple list tool but not exhaustive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description only implies project_id and search parameters but provides no explanation for limit and skip. It adds value by hinting at output fields (id, name), but parameter semantics are incomplete.
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 lists web test cases via text search, specifying the API endpoint. It distinguishes from sibling tools like testneo_list_tests_by_tags by indicating it uses '?search=' rather than tags, but does not explicitly name alternatives.
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?
It provides explicit guidance on using the returned id and name with testneo_run_generated_test_pipeline or passing project_id and name_query to run by name. However, it does not compare against alternatives like testneo_list_tests_by_tags for when to use each.
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 states 'Read-only' and shows the HTTP method, indicating no mutation. However, it does not mention error handling, pagination, or what happens if the project_id is invalid. Additional transparency about the return format would improve this.
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 sentence with the endpoint appended. No unnecessary words or repetition. It is appropriately concise and front-loaded with the core action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool is a simple list with one parameter and no output schema, the description covers the basic purpose and parameter. However, it does not describe the structure of the returned test chains, pagination, or sorting. The agent might need additional context to use the output effectively, but the description is minimally 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 schema has 0% coverage for parameter descriptions. The description adds minimal context for project_id by saying 'for a web project', which clarifies the parameter's role. While this is helpful, it does not explain how to obtain the project_id or the parameter's format beyond the schema 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 clearly states the action ('list'), resource ('user-saved API test chain suites'), and scope ('for a web project'). It also mentions the output includes 'ordered test_case_ids'. This distinctively differentiates from sibling tools like testneo_save_api_test_chain and testneo_list_tests_by_tags.
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. It does not mention when not to use it or specify prerequisites. The read-only note and endpoint provide some context but not enough for an agent to decide between this and other list tools.
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?
Without annotations, the description discloses the backend endpoint and tag query behavior. It does not mention side effects, rate limits, or response details (e.g., pagination, empty results). Adequate but 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 two sentences, front-loaded with purpose, and contains no redundant information. Every word is necessary and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations or output schema, the description covers the main purpose and behavior. However, it lacks details on return structure, error conditions, and how it differs from similar tools, leaving some gaps for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage. The description adds meaning for tags (leading @, querying mechanism) and tag_match (union/intersection) but does not explain project_id or the exact return format. Partial compensation.
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 lists web test case IDs by tags and explains the backend behavior. However, it does not explicitly distinguish from similar sibling tools like testneo_find_test_cases, which may cause confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides context on how tag matching works (union vs intersection) but gives no guidance on when to use this tool compared to alternatives or any prerequisites/exclusions.
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?
Discloses read-only nature and no DB writes, and gives backend endpoint. With no annotations, this is helpful but lacks detail on return format, error handling, or size limits.
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?
Three concise sentences, front-loaded with the main purpose. No redundancy, efficient use of 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?
Given no output schema and two parameters, description provides backend endpoint and return content types. But lacks details on validation, error messages, or expected usage context.
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% and description does not explain the two required parameters (swagger_file_base64 and swagger_filename). Only implies base64 but no details on filename or format 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 clearly states it parses Swagger/OpenAPI from base64 and returns spec format, tags, and endpoint counts. It distinguishes from siblings like testneo_swagger_impact_analysis (impact analysis) and testneo_api_project_upload_openapi (upload).
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 usage via 'Read-only; no DB writes' and mentions backend endpoint, but does not explicitly state when to prefer this over siblings like testneo_swagger_upload_and_generate. No exclusion criteria.
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 full responsibility for behavioral disclosure. It reveals it is a write operation (stores spec) and that confirmation is needed ('confirm=true'). However, it does not describe idempotency behavior, error handling, or what happens if a spec already exists. The backend endpoint is mentioned but rate limits or auth requirements are not.
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 at three sentences with no verbosity. It front-loads the main purpose. However, it could be better structured by explicitly listing parameters or behavior.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description should cover return values or side effects, but it does not. It also omits error scenarios, idempotency, and parameter details. For a tool with 5 parameters and no schema descriptions, the description is insufficient for an agent to fully understand how to invoke it 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%, leaving the description to explain parameters, but it does not. It mentions 'multipart field: file' but does not map to the actual parameters (openapi_file_base64, openapi_filename). The confirm parameter is hinted at via 'confirm=true' but not explained. project_id and idempotency_key are entirely undocumented. The description adds minimal value beyond parameter names.
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 ('Upload OpenAPI JSON/YAML to a classic API project') and the resource affected ('stores spec on Project.openapi_spec'). It distinguishes from the sibling tool by explicitly saying 'Use before testneo_api_project_openapi_impact.'
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 explicit usage context: it should be used before testneo_api_project_openapi_impact. It also notes the guarded nature ('allow-write + confirm=true'), which informs the agent that confirmation is required. However, it does not explicitly state when not to use this tool or mention alternatives beyond the sibling.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses write operation, confirmation requirement, and timeout handling, but does not mention idempotency, overwrite behavior, or error handling. More detail on side effects would improve transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loading the main purpose and including key guardrails. It is concise but could be structured with bullet points or clearer separation of usage notes.
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 11 parameters and no output schema, the description lacks detail on return values, error conditions, and parameter interactions. It does not explain the output format beyond 'unified context indexing + NLP web test cases', making it insufficient for an agent to fully understand tool behavior.
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%, but description only implicitly references swagger and business rules parameters. It does not explain project_id, folder_id, max_test_cases, focus_tags, confirm, or idempotency_key, leaving the agent with minimal guidance beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (upload Swagger + optional business rules) and the outcome (unified context indexing + NLP web test cases). It distinguishes from sibling tools like testneo_swagger_preview (preview only) and testneo_api_project_upload_openapi (upload without generation).
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 usage context: requires TESTNEO_MCP_ALLOW_WRITE and confirm=true, respects preconditions, and suggests timeout for large payloads. However, it does not explicitly contrast with sibling tools or specify when not to use.
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 details the output components and the conditional inclusion of an NLP patch, which is useful. However, it does not disclose that this is a read-only operation or any potential side effects, which is a gap for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently conveys the tool's purpose and output components. It is front-loaded with the core action and includes important conditional behavior. The length is appropriate for the complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description lists the bundle components (summary, logs, theme, etc.), which provides useful context. However, it lacks details on the output format, error handling, or pagination behavior for logs/events. The condition for the NLP patch is clearly stated, but overall completeness is moderate.
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%, and the description fails to explain any of the four parameters beyond the implied execution_id. Parameters like logs_limit, event_limit, and include_nlp_patch_suggestion have defaults but no rationale in the description, leaving the agent to rely solely on schema types and 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 clearly states it retrieves a failure triage bundle containing specific components like summary, logs, and an NLP patch. The verb 'Get' and the resource 'failure triage bundle' are specific, and the tool distinguishes itself from siblings like testneo_get_execution_summary or testneo_search_failures by offering a comprehensive, actionable bundle.
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 use when investigating a failure with an execution ID, as it returns a triage bundle. It mentions conditions for the NLP patch, providing context. However, it does not explicitly state when to avoid this tool in favor of alternatives like testneo_get_execution_logs or testneo_search_failures.
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?
Mentions applying route hardening conditionally, but doesn't clarify if preview is read-only or has side effects; no annotations to compensate.
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 clear, front-loaded sentences with no redundancy.
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?
Adequate for main purpose but missing details on input format for generated_test_cases and output behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Adds some meaning to route_hardening parameter via description, but neglects generated_test_cases and max_items (0% schema 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 it previews generated tests in NLP and Playwright SDK spec.ts format for human-in-loop approval, distinguishing it from sibling tools like export or execute.
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?
Implied usage after test generation for approval, but no explicit when-not-to-use or comparison to alternatives like export or update.
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 write nature (create and execute), the ordered chain behavior, and the guard conditions. However, it does not detail potential side effects, rate limits, or failure modes. The reference to sibling routing helps but is not fully self-contained. Scores 3 as it covers key behaviors 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: three sentences, each carrying essential information. The first sentence defines purpose and options, the second relates to a sibling, and the third states guard conditions. No filler, well-structured, and 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?
Despite high complexity (12 parameters, no output schema), the description leaves many details uncovered. It does not explain return values, error handling, or the behavior of numerous parameters. Given the tool's sophistication and the lack of annotations or output schema, the description is insufficient for an agent to use the tool correctly without external documentation.
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 explicitly explains only three parameters (test_case_ids, saved_chain_id, confirm) out of 12. Critical parameters like run_name, notes, parallel, max_workers, environment_variables, etc., are left without any explanation. This significantly impairs the agent's ability to use them 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 tool creates and executes a multi-test run using an ordered API chain, specifying two distinct input modes (test_case_ids or saved_chain_id) and explicitly preserving order. It also references a sibling tool (testneo_run_batch_by_tags) for routing similarity, distinguishing itself effectively.
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 usage guidance: choose either explicit test_case_ids (ordered) or saved_chain_id from a specific sibling tool. It also mentions the guard conditions (TESTNEO_MCP_ALLOW_WRITE + confirm=true) and references similar routing to another tool, giving adequate context for when to use. Scores 4 because it lacks explicit 'when not to use' but is otherwise strong.
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 exist, so the description carries the burden. It discloses human-in-loop gating, conditional use_agent flag, and preflight polling with environment variables, adding behavioral context beyond basic execution.
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 dense but each sentence adds value. It is front-loaded with the core action. Minor redundancy in environment variable details could be tightened.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description covers execution logic, routing, and polling. It references sibling tools for status, but missing details on response format and error handling.
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 input schema declares zero properties, but the description implies parameters (test_case_id, project_id, name_query) exist. This contradiction will confuse the agent; the description does not align with the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: execute a generated test case by numeric ID or by project+name query. It distinguishes from sibling tools like testneo_find_test_cases and testneo_get_execution_status.
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 advises using testneo_find_test_cases to browse matches before executing, and mentions human-in-loop gating. It lacks explicit when-not-to-use conditions but provides sufficient context.
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 mentions validation and fetching context but does not explicitly state that it is read-only, has no side effects, or what 'basic account context' includes.
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?
A single, straightforward sentence with no filler. Every word is meaningful 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?
For a simple tool with no parameters and no output schema, the description covers the main action and return type. However, it could elaborate on what 'basic account context' entails for better 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?
There are zero parameters, so schema coverage is 100%. The description doesn't need to add parameter info; baseline 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 it validates a token and fetches basic account context, aligning with the tool name. This distinguishes it from sibling tools like testneo_get_local_agent_status or testneo_list_projects.
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. For example, it doesn't suggest using it before other operations to verify token validity, nor does it 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.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite no annotations, the description explicitly declares the tool as read-only and non-API-calling, which are key behavioral traits. It does not detail specific side effects, but the read-only claim reduces ambiguity.
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 conveys purpose, environment context, and key constraints. It is well-structured and front-loaded.
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 description lacks details about return values, output format, error handling, or the structure of overrides. Given the absence of an output schema and low parameter coverage, this is a significant gap for agent understanding.
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%, and the description does not explain individual parameters. The term 'optional per-call overrides' vaguely references route_hardening, but nlp_commands is entirely undescribed, leaving the agent to infer its purpose.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it rewrites vague Navigate-to NLP lines into URLs using server environment variables and optional overrides. It distinguishes itself from sibling tools by specifying its unique function of route hardening.
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 context by stating it is read-only and does not call the TestNeo API, which helps the agent decide when to use it. However, it lacks explicit guidance on when not to use it compared to alternatives like testneo_update_test_case_nlp.
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, description discloses it uses Web AI chat quota, mirrors UI behavior, and accepts optional recommend_context / rag_context for document-aware answers. Does not cover output format or error behavior, but provides reasonable 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?
Three sentences with front-loaded purpose, followed by usage and optional features. No wasted words.
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?
No output schema, but description lacks return value information. Only covers about half of the 9 parameters, leaving nested objects (recommend_context, rag_context) unexplained. Incomplete given complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has no descriptions (0% coverage). Description adds meaning to context_id, context_name_query, recommend_context, rag_context, and the scoping rule. But omits context_match_mode, response_style, prefer_context_id, and doesn't detail nested objects. Partial 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 it is a natural-language Q&A tool over a project, same as the product UI, and optionally scoped to unified context. It uniquely identifies its purpose among siblings, which lack a similar Q&A tool.
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?
Explicit guidance on when to pass context_id or context_name_query (scoped questions) versus omitting both (project-wide questions). Mentions quota usage. No explicit when-not-to-use or alternatives, but the context scoping is well covered.
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?
The description explicitly states that the tool deletes a resource (destructive), and highlights the guard requiring write permission and confirmation. This adds behavioral context beyond the schema, though it does not mention possible side effects like cascading deletion.
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: one for purpose, one for guard and endpoint. No redundant information. Efficient and front-loaded.
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 covers purpose, guard, and endpoint. However, without annotations or output schema, it lacks parameter descriptions and return value information. This is a notable gap for a 4-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?
With 0% schema description coverage, the description should explain parameters. It only references 'confirm' in the guard but does not describe project_id, chain_id, or idempotency_key. This is a significant 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 action ('Delete a saved API test chain by id') and the specific resource. It is distinct from sibling tools like save, list, and run, so the purpose is 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 mentions the guard ('TESTNEO_MCP_ALLOW_WRITE + confirm=true') and the backend endpoint, which implies that write permission and confirmation are required. However, it does not explicitly state when not to use this tool or provide alternatives for deletion.
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 fully bears the burden. It discloses write guard, default environment creation, and Lighthouse performance audits, providing good behavioral context for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Four sentences packed with essential information: purpose, API mapping, guard, default behavior, and audit setting. No redundancy, well front-loaded.
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?
No output schema is provided, and the description does not mention return values. While key behavioral aspects are covered, details about parameters like environment, status, and idempotency_key are missing, leaving some gaps for a complex 12-parameter 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?
Schema coverage is low (17%), but the description provides meaning for key parameters (base_url, credentials, create_default_environment, project_settings) beyond the schema. Not all 12 parameters are covered, but enough value is added.
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 'Create a new web automation project' and mentions it mirrors POST /api/web/v1/projects, providing a specific verb and resource. It differentiates from siblings like testneo_create_web_project_environment.
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 mentions guarded conditions (TESTNEO_MCP_ALLOW_WRITE=true, confirm=true) and explains default vs. project-only creation via create_default_environment. However, it does not explicitly state when to use this tool over alternatives.
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?
States 'Read-only' and provides the HTTP method (GET), disclosing safety. No annotations are provided, so the description partially covers behavioral needs, but it could mention return format or potential side effects (though none expected).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two succinct sentences: first gives purpose, second adds behavioral and usage context. Every sentence is essential, front-loaded with key 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 the tool's simplicity (one parameter, no output schema), the description is mostly complete. It explains the core functionality and usage context, but lacks detail on the returned data structure (chains, summaries) and potential errors.
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%, yet the description does not elaborate on the `project_id` parameter beyond implying it identifies a project. It adds minimal value over the schema's type and constraints. Parameter meaning is left implicit.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it scans Swagger/NLP-derived tests and returns suggested business-flow chains. It uses specific verbs ('Scan', 'return') and resource ('API-style web tests for a project'), and distinguishes itself from sibling tools by mentioning it is read-only and should be used before save/run operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use before recommending which suite to run or before testneo_save_api_test_chain / testneo_run_api_test_chain', providing clear when-to-use guidance and naming specific alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description fully discloses read-only nature and what is returned (registration status, heartbeat, setup_url). No behavioral traits are hidden.
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, no filler. First sentence immediately states purpose, second adds output details. 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, parameterless, no-output-schema tool with no annotations, the description is fully complete. It explains what the tool does, what it returns, and its read-only nature.
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?
Tool has zero parameters, so schema coverage is 100%. The description adds no parameter info, which is acceptable. Baseline 4 for 0 params.
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?
Description clearly states it 'Returns whether a TestNeo self-hosted agent is registered and recently heartbeating (local runner)', specifying verb and resource. It also mentions 'includes setup_url...', making the purpose distinct from siblings which focus on tests, projects, and executions.
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 vs alternatives. The description implies it's for checking agent status, but lacks 'when' or 'when not' statements typical of good usage guidelines.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![testneo-mcp MCP server](https://glama.ai/mcp/servers/gururajhm-neo/testneo-mcp/badges/card.svg)](https://glama.ai/mcp/servers/gururajhm-neo/testneo-mcp)

Score Badge

Copy to your README.md:

[![testneo-mcp MCP server](https://glama.ai/mcp/servers/gururajhm-neo/testneo-mcp/badges/score.svg)](https://glama.ai/mcp/servers/gururajhm-neo/testneo-mcp)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/gururajhm-neo/testneo-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server