Testing Platform — MCP server

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool targets a distinct action: issue CRUD, comments, attachments, project lookup. No two tools have overlapping purposes.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern in snake_case (e.g., create_issue, list_comments, update_issue). No deviations.
Tool Count5/5
9 tools cover the essential operations of a testing platform without redundancy or bloat. Well-scoped for the domain.
Completeness4/5
Core issue lifecycle (create, read, update, comment, attach) is covered. Minor gaps like project creation or issue deletion are out of expected scope, keeping the set focused.
Average 3.9/5 across 9 of 9 tools scored. Lowest: 2.7/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 1 commit 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
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How is the quality score calculated?

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

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

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

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

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must carry the full burden. It only discloses ordering ('oldest-first') but omits details like whether results are paginated, read-only status, or side effects. The behavioral profile 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.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise, but it lacks necessary detail. It is not overly verbose, but it earns its place only partially due to under-specification.
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 simplicity of the tool (1 param, no output schema), the description is too sparse. It fails to describe the output format, whether all comments are returned, or any limits. Context is insufficient for confident selection.
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 1 parameter (card_id) with 0% description coverage. The description does not explain card_id (e.g., that it is the issue ID) or add any meaning beyond the schema. This is a critical gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action: 'List comments on an issue, oldest-first.' It specifies the resource (comments on an issue) and ordering, distinguishing it from sibling tools like add_comment or get_issue.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not mention when to use this tool versus alternatives, nor does it include prerequisites or exclusions. Context is only implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided. The description mentions 'Real-time' and visibility, but does not disclose side effects, permissions, or error behavior. It adds moderate behavioral context beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is lengthy with detailed writing style guidelines. While valuable, it could be more concise. The first sentence effectively states the purpose, but the rest adds bulk.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with two parameters and no output schema. The description covers purpose and usage style well, but omits error handling, success response, and prerequisites. Adequate but not 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?
Schema coverage is 50% (body is described, card_id is not). The description elaborates on body content (plain English, audience) but offers no additional meaning for card_id. It partially compensates for the coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Post a comment on an issue' and adds 'Real-time, visible to anyone watching the board.' This distinguishes it from sibling tools like list_comments and create_issue.
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 audience guidelines (testers and project owners) and writing style tips, but does not explicitly state when to use this tool versus alternatives or when not to use it. No alternative tools are named.
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 term 'Read' indicates idempotency, and the description lists what information is returned. However, it omits details on error handling, authentication requirements, or rate limits, which a fully transparent description would include.
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 purpose with no filler. It is well-structured and to the point, though slightly more detail could be added without harming conciseness.
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 read tool with one parameter and no output schema, the description partially explains the return value but does not specify the format or whether it returns the full issue object. It also does not address possible errors or permissions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already covers the single parameter 'id' with 100% coverage. The description adds no additional meaning for the parameter, only stating it reads full details for that issue. Baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool reads a single issue's full detail, listing key attributes. It distinguishes itself from siblings like 'list_issues' (which lists summaries) and 'get_attachment' (which retrieves attachments specifically).
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 reading details of one issue, but provides no explicit when-to-use or when-not-to-use guidance, nor does it mention 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavior. It reveals that issues land in the 'New column by default', but does not mention authentication, rate limits, or other side effects. The detailed writing guidance is helpful but not behavioral.
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 somewhat long but well-structured with two paragraphs. The first sentence states the main purpose, and the second paragraph adds valuable guidance. Every sentence earns its place, though it could be slightly more concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 6 parameters (3 required) and no output schema, the description covers the main action, default column, audience, and examples. It does not explain return values, but that's acceptable without an output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by explaining the audience and writing style for title and description, but does not enumerate or clarify each parameter beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Create a new issue') and the resource ('in a project'), and distinguishes from siblings like update_issue and list_issues. It also provides example use cases.
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 tells when to use the tool ('file bugs you've found, follow-ups from a conversation'), and provides extensive audience guidance. However, it does not explicitly exclude alternatives or state 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It communicates the basic function but omits important details such as behavior on no matches or multiple matches, and whether it returns a single id or could return multiple. These gaps reduce 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 concise with two sentences, each serving a distinct purpose: stating the action and providing usage guidance. There is no extraneous 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?
For a simple tool with one parameter and no output schema, the description covers the core functionality and usage context adequately. However, it lacks detail on edge cases (e.g., no match, multiple matches) and the return format, which would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds minimal value beyond the schema: it provides an example and context ('free-text'), but the schema already describes the parameter as 'Case-insensitive project name or fragment.' Thus, the description does not significantly enhance parameter understanding.
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: 'Resolve a free-text project name to its id.' It provides a concrete example ('panda eats') and specifies the output (id), making the function immediately understandable. It is distinct from sibling tools, which focus on other operations like adding comments or creating issues.
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 explicitly tells when to use the tool ('Use before any other tool that takes a project') and when not to ('unless you already have the numeric id'). This provides clear decision guidance, which is crucial for an AI agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses that the free-text filter is applied client-side, pagination is only honored in archive mode, and limit has a cap of 100. This adds significant value beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no filler, front-loaded with main action. Every word adds information, making it highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Lacks output schema, so return shape is not described. However, pagination and defaults are covered. Given 9 parameters and client-side behavior, the description is mostly complete for a list tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 67% with basic descriptions. The description adds value for include_archived/status relationship and client-side filter, but does not elaborate on parameters like type, priority, or reporter 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?
The description explicitly states 'List issues (cards) in a project, optionally filtered' with a specific verb and resource, and clearly differentiates from sibling tools like create_issue or get_issue by focusing on listing.
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 when-to-use context, including default behavior (ACTIVE issues only) and how to retrieve archived issues via include_archived or status. It does not explicitly name alternatives but implies the scope clearly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It describes the behavior as listing all visible projects. It does not explicitly state that it is a read-only operation, but the intent is clear. More detail on what 'visible to the configured user' means could be added.
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 superfluous words. The description is front-loaded with the action and resource, followed by usage guidance. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description is sufficient for a simple list operation. It covers what is listed and when to use. Could optionally mention the return format, but not required given the tool's straightforward 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?
The input schema has no parameters, so schema coverage is 100%. With 0 parameters, baseline is 4. The description does not need to add parameter-level details, but it correctly implies no input is needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it lists all projects visible to the user, with a specific verb ('List') and resource ('testing-platform projects'). It explicitly distinguishes from sibling tool 'find_project' by noting use cases for when project id is unknown or disambiguation is needed.
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 guidance on when to use: when the project id is unknown or to disambiguate names. It does not explicitly mention when not to use, but the sibling tools list implies alternatives like 'find_project' for direct lookup.
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, so description bears full burden. Discloses that moving to done/wont_fix is blocked unless reporter signed off. Also mentions behavior for service-account reporters. Lacks details on authorization or rate limits, but status change behavior is well covered.
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 multi-paragraph but front-loaded with main purpose. Uses clear section headings for status changes and audience. Every sentence serves a purpose, though could be slightly more concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers status transition behavior and title/description guidelines thoroughly, with 7 parameters and no output schema. Missing error conditions and full parameter details, but sufficient for common use cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. Description adds meaning for status (explains transition rules) and title/description (plain-language rules), but does not detail id, url, type, or priority. Some parameters like priority are left undocumented.
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 starts with 'Patch fields on an existing issue.' and lists specific examples like status change, reprioritize, retitle. Clearly different from sibling tools like create_issue (create new) and get_issue (read).
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?
Explicit when to move card silently (in_progress, in_review, stalled->new) and when not to (terminal states blocked server-side). Also provides audience guidelines for title/description edits. Differentiates from add_comment for confirmation scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description discloses that the attachment is returned inline for visual inspection and that external URLs are refused. It could be improved by mentioning error handling or what happens with non-image attachments, but it adequately covers key behavioral traits.
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 two short paragraphs, front-loaded with purpose, and efficiently conveys usage guidance. It is clear and well-structured, though slightly informal in one phrase, but overall concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no output schema), the description is fully complete. It explains when to use, the exact parameter usage, and constraints, leaving no ambiguity for an AI agent to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by instructing to pass the URL exactly as received from get_issue's attachments array, reinforcing the schema's requirement and providing practical context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool fetches a screenshot or image attachment and returns it inline, with a specific verb and resource. It distinguishes itself from sibling tools, as no other tool deals with fetching attachments.
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 explicitly says when to use this tool: after get_issue when the reporter mentions a screenshot, the description references a visual problem, or to confirm a UI bug visually. It also specifies constraints (only platform-served URLs allowed), providing clear guidance on when and how to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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