codex-skills-mcp

Server Quality Checklist

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Latest release: v1.0.6
Disambiguation4/5
search_skills and plan_workflow both return skill recommendations, which could cause slight confusion, but the descriptions clarify that search_skills is for finding a single skill while plan_workflow is for combining multiple skills. The other tools (list_categories, read_skill, load_skill_file, list_skill_files) have clearly distinct purposes.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern with lowercase and underscores (search_skills, list_categories, read_skill, load_skill_file, list_skill_files, plan_workflow). No mixing of styles or irregular naming.
Tool Count5/5
Six tools is well-scoped for a skill library server, covering discovery, browsing, reading, and planning without excess or deficiency.
Completeness5/5
The tool set fully covers the lifecycle of using a skill library: discovering skills (search_skills), exploring categories (list_categories), reading skill instructions (read_skill), accessing files (list_skill_files, load_skill_file), and planning multi-skill workflows (plan_workflow). No obvious gaps for a read-only skill consumption server.
Average 4.2/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 20 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 MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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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

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the behavioral disclosure burden. It clarifies that the tool returns a file tree (not file contents), supports subdirectories, and is intended for structural exploration. However, it does not mention output format, pagination, or any side effects. As a read-only listing tool, this is acceptable but not deeply transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the action and includes a usage hint. No unnecessary words or repetition of schema details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple listing tool with fully documented parameters and a clear purpose, the description is adequate. It does not explain the response format, but no output schema exists and the tool's behavior is straightforward. The usage guidance adds contextual value.
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 fully documents all three parameters with descriptions and defaults (path, max_depth, skill_name). The description adds no extra parameter semantics beyond the schema, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List the file tree of a skill or a subdirectory within it') and identifies the specific resource (skill file tree). It also distinguishes this tool from siblings by positioning it as a pre-loading exploration step, contrasting with read/load tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit usage advice: 'Use this to understand a large skill's structure before deciding which files to load.' This implies when to use (before loading) and differentiates from load/read siblings. However, it does not name alternatives explicitly or state when not to use, so it stops short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 discloses that results are 'matching skills ranked by relevance' and implies a read-only search, but does not cover edge cases, result structure, or error behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the verb and resource, and no wasted words. Each sentence carries meaningful 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 low-complexity search tool with a complete input schema, the description provides adequate return semantics ('ranked by relevance') and usage context. It lacks output structure details since no output schema exists, but this is not critical for selection or invocation.
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?
All three parameters are fully described in the schema with defaults and examples, so the description adds no additional parameter-level detail. The baseline of 3 is appropriate given 100% 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 uses a specific verb ('Search') and resource ('codex-skills library') with clear scope ('by natural language query'). It differentiates from siblings like list_categories and read_skill by focusing on discovery.
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?
Explicitly states when to use it: 'Use this as the primary entry point to discover skills for a task.' It provides clear context but doesn't name alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that the tool reads instructions, file structure, and dependency info, and notes that instructions contain role and execution rules. This is a read operation with no side effects implied, and the description gives meaningful context beyond a bare 'reads skill'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core action, and every sentence adds value. The first sentence specifies what the tool does, the second gives usage guidance and context about the content. No filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (single parameter, no output schema, no annotations), the description is adequately complete. It explains what is read and when to use it. It does not describe the return format, but for a simple read operation this is a minor gap, not a major deficiency.
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 single parameter 'name' is fully described in the schema (100% coverage), including the requirement for an exact name from search results. The description adds no additional parameter semantics beyond reinforcing the workflow context, so the 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 skill's full instructions (SKILL.md), file structure, and dependency info. It uses a specific verb (read) and resource (skill), and distinguishes from siblings like list_skill_files and load_skill_file by explicitly mentioning the full instructions and broader scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says to call this after search_skills to load a skill, providing clear when-to-use guidance. It does not explicitly exclude alternatives like load_skill_file or list_skill_files, but the workflow context is helpful and sufficient for a simple read operation.
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, but the description carries the burden well. It explicitly states that the tool only suggests skills and returns a list, while the actual orchestration/execution order is left to the agent. This sets clear expectations about the tool's advisory nature and lack of side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the purpose, and every word earns its place. It avoids redundancy and is easy to parse.
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 complete. It covers the input, output, and the agent's responsibility for orchestration, giving enough context for correct selection and invocation without extra fluff.
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 100% and the description's 'task_description' aligns with the schema's 'Full description of the task to accomplish'. The description adds no additional meaning beyond what the schema already captures, so the baseline 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 uses a specific verb ('suggest') and resource ('relevant skills') to state its function clearly. It distinguishes from sibling tools (search_skills, read_skill) by focusing on combining skills for a task rather than searching or reading individual skills.
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 clearly implies when to use: given a task description, to get skill recommendations. It also clarifies the agent retains control over orchestration and execution order, which is important guidance. However, it does not explicitly mention when not to use it or alternative tools for specific skill lookup.
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 present, the description carries the full transparency burden. It clarifies the read-only nature and the target within the skill directory, but it lacks details on return format, error handling for missing files, or path traversal limits.
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 exactly two sentences, front-loaded with the core purpose and followed by a single usage guideline. No word is wasted, and it maintains clarity.
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 two-parameter read operation, the description covers the what, when, and how to locate file paths via the skill instructions. It could mention discovering file paths with list_skill_files or error behavior, but the essentials are present.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers both parameters with descriptions and examples, so the baseline is 3. The description adds meaningful context by specifying the types of files (scripts, configs, README) and that paths come from the skill instructions, enriching the file_path semantics beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Read a specific file from within a skill's directory', with a specific verb and resource. It distinguishes itself from sibling tools by referencing usage after read_skill and targeting scripts, configs, README, and other resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly instructs to use this tool after read_skill when accessing referenced files, providing a clear use case. It implicitly names read_skill as the alternative for reading the skill's main instructions.
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. The verb 'List' implies a read-only operation, and the description transparently states what is returned (categories with counts). It adds useful context about the library. No hidden behaviors are indicated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the main action, and includes a clear usage hint. Every word earns its place with no redundancy or wasted text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a low-complexity, zero-parameter tool with no output schema. The description sufficiently explains what it does and when to use it, and it clearly separates itself from sibling tools. No additional context is needed for an 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?
The tool has zero parameters, which earns a baseline of 4. The description adds no parameter-specific information because none is needed; the schema is empty and fully covered.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'List' and identifies the resource 'skill categories in the codex-skills library' with additional detail about skill counts. It clearly distinguishes itself from sibling tools like list_skill_files and search_skills.
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 states when to use the tool: 'Use this to get an overview of available domains.' This provides clear context, though it does not mention when not to use it or name specific alternatives, which would warrant a 5.
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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