coderide

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a distinct purpose: getting, listing, updating, or starting projects/tasks. No two tools overlap in functionality, making it easy for an agent to select the right one.
Naming Consistency4/5
Tools mostly follow a verb_noun pattern (get_project, list_tasks, update_task), but 'next_task' deviates by using a noun phrase instead of a verb. This minor inconsistency is still clear.
Tool Count5/5
With 9 tools, the set is well-scoped for a project/task management server. Each tool serves a clear purpose without being excessive or too sparse.
Completeness2/5
The domain appears to be project and task management, but there is no way to create or delete projects or tasks. Only update and list/get operations are provided, which is a significant gap for a complete workflow.
Average 3.7/5 across 9 of 9 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- Last stable release on December 21, 2025
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under Inno Setup License.
This repository includes a README.md file.
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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?
Annotations are absent, so the description must carry the full burden. It only says 'retrieves' but does not state if it is read-only, safe, or if it requires any permissions. There is no mention of side effects or idempotency, which is a notable gap for a retrieval 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?
Two concise sentences with no wasted words. The first sentence defines the tool's primary purpose, and the second provides typical usage context. Information is front-loaded and well-structured.
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 has only one parameter and no output schema, the description is fairly complete. It explains what the tool does, the input format, and typical usage. However, it could hint at the return value format.
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 for the parameter, but the description clarifies that the parameter is a unique task number (e.g., 'CRD-1') and matches the pattern. This adds some semantic value beyond the schema pattern, but does not fully describe the parameter's purpose or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states it retrieves specific instructions/prompt for a task, using a unique task number. It clearly identifies the resource and action, and the example number format helps. However, it does not explicitly differentiate from sibling tools like get_task, which might retrieve task details.
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 says 'typically used to understand the detailed requirements' which gives some context. But it does not provide when to use vs. alternatives (e.g., get_task) or when not to use it. No exclusion criteria are mentioned.
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 disclose behavior. It only says 'retrieves', implying read-only, but does not explicitly state there are no destructive actions or side effects, nor does it mention authorization or edge cases.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the action, and contains no unnecessary words. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema and annotations, the description adequately covers the tool's purpose and usage. It could be improved by describing the return format, but it is sufficient for a simple retrieval 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?
The schema has 0% description coverage for the slug parameter. The description adds context by giving an example ('CRD') and explaining it's a unique slug, but does not go beyond what the pattern already conveys.
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 retrieves project details and the prompt for the first task using a slug. It uses specific verb and resource, but does not explicitly differentiate from siblings like get_project or get_prompt.
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 it is useful for initiating work or understanding a project's starting point, providing clear context. However, it lacks explicit guidance on when not to use it or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It does not disclose behavior when no next task exists, how the sequence is determined, or whether the operation is read-only. For a tool 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?
The description is two sentences, front-loaded with the verb and resource, and includes a concrete example. Every sentence adds value with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter retrieval tool without an output schema, the description is mostly complete. It explains the purpose and usage example, but could mention the expected return format or edge cases like a missing next task.
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 parameter 'number' has a regex pattern in the schema, and the description adds meaning by explaining its format (e.g., CDB-23) and how it is used to find the next task. However, it does not specify what happens on invalid input or describe the return value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves the next task in sequence based on a current task number (e.g., CDB-23 → CDB-24), and explains its utility in project workflows. This distinguishes it from siblings like get_task and list_tasks.
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 that it is useful for finding the next task to be done, but does not explicitly state when not to use it or compare it to alternative tools like get_task or list_tasks.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for behavioral disclosure. It fails to mention side effects, error handling (e.g., when task not found), permissions needed, or whether the update is reversible. This is a significant gap 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?
The description is highly concise with only two sentences, no fluff, and front-loads the key action and constraints. Every sentence adds value.
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 the basic purpose and parameters but omits return values or success/failure indications. For an update operation with no output schema, the lack of any mention of what the tool returns or how to confirm success is a gap, making it only 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?
Schema description coverage is 0%, but the description clarifies that 'number' is a unique identifier with an example format, and that 'description' and 'status' are optional but at least one must be provided. It does not add additional meaning beyond the schema for the status enum or description type, but the usage constraint is helpful.
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 specifies the action (updates), resource (task), and the specific fields that can be updated (description and/or status), distinguishing it from sibling tools like get_task or list_tasks.
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 states that at least one of 'description' or 'status' must be provided, giving a clear constraint. However, it does not explicitly mention when not to use or provide alternatives, which would have earned a 5.
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 behavioral disclosure. Only states 'retrieves detailed information' without covering error conditions, data freshness, or whether operation is read-only (assumed but not stated). 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, concise, front-loads purpose and identifier format. No redundant 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 one-parameter read tool with no output schema, description covers purpose and parameter format adequately. Missing details like return structure or error cases, but acceptable given simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% coverage, but description explains slug meaning: unique identifier, three uppercase letters with example. Adds context beyond pattern regex, clarifying it's a project-specific identifier.
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 verb 'retrieves', resource 'project', and identifier 'slug' with format details. Distinguishes from siblings like list_projects (which lists) and get_prompt (different resource).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies use when slug is known, but no explicit guidance on when to use versus list_projects or other project tools. No exclusion criteria mentioned.
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 describes listing all projects but does not disclose output format, pagination, limits, or any behavioral nuances beyond the basic operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no superfluous information. It efficiently covers purpose and a notable usage detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a parameterless list tool with no output schema, the description is mostly complete. It explains the scope and authentication context. Lacking output format details, but acceptable for a simple list.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With zero parameters, baseline is 4. The description adds value by explaining why no parameters are needed (workspace determined from API key), which clarifies the intended use 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 lists all projects in the user workspace, with a specific verb and scope. It distinguishes from siblings like get_project and start_project by implying this is the broad list operation.
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 does not explicitly state when to use this tool versus alternatives. However, by naming the resource and noting it lists all projects, an agent can infer it is the right choice for getting an overview, while get_project is for details.
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 states it lists tasks and returns them organized by status columns, but does not disclose if it's read-only, safe, or any side effects. With no annotations, the description carries full burden 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?
Single sentence that efficiently front-loads the action ('Lists all tasks') and adds output structure details, with no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with one parameter and no output schema, the description provides adequate context about the return format (organized by status columns). Could mention pagination or limits.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaning to the slug parameter by explaining it's a project slug and providing an example ('CDB'), which supplements the schema's pattern constraint (0% 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 lists all tasks within a project given a project slug, and distinguishes itself from siblings like list_projects (which lists projects) and get_task (which retrieves a single task).
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 get_task or next_task. The description does not mention prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must carry full burden. Only states 'retrieves' implying read, but omits any details on side effects, permissions, rate limits, or what 'detailed information' entails.
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 with no unnecessary words, front-loaded with action and resource.
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 a simple tool with one parameter, but lacks description of return value details (since no output schema) and potential errors. Not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Adds meaning by explaining the 'number' parameter as a task number with example 'CRD-1', clarifying pattern. Schema coverage is 0%, so description compensates well.
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 verb 'Retrieves' and resource 'detailed information for a specific task', with an example (CRD-1) that distinguishes it from siblings like list_tasks or get_project.
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?
Implies usage when needing detailed info for a specific task by number. Does not explicitly exclude alternatives or state when not to use, but context from sibling names provides some 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 updates can be partial (only knowledge or diagram or both) and that slug is the identifier. However, it does not specify whether updates are additive or overwrite existing data, what happens on failure (e.g., invalid slug or diagram format), or any authentication/authorization requirements. For a mutation tool, this is adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, directly states the purpose and required conditions, and contains no redundant or irrelevant information. Every word earns its place, making it 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?
Given the tool has three parameters (one a nested object) and no output schema, the description covers the core action and constraints (slug requirement, at least one update field). However, it omits important context such as the return value/response format, error handling (e.g., if slug does not exist or diagram is invalid), and whether updates are incremental or replacement. This leaves gaps for an AI agent to infer.
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 three parameters with 0% description coverage, so the description adds meaning: it explains that slug identifies the project, project_knowledge is graph data, and project_diagram is in Mermaid.js format. It also clarifies that at least one of the two optional parameters must be provided. However, it does not specify the internal structure of the project_knowledge object or the expected formatting of the diagram string, which would improve clarity.
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 updates a project's knowledge graph data and/or its structure diagram in Mermaid.js format. This specific verb and resource, along with the explicit mention of two updatable components, distinguishes it from sibling tools like get_project (read-only) and list_projects (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 context: the project is identified by a unique slug, and at least one of the two optional fields must be provided for the update to occur. However, it does not explicitly compare this tool to alternatives (e.g., when to use update_project vs update_task), nor does it 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.

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