agentskills-mcp
Server Quality Checklist
Latest release: v0.1.1
- Disambiguation5/5
Each tool has a clearly distinct purpose: fetching a specific skill, installing it locally, listing repositories, searching skills, and suggesting scaffolds. No overlap or ambiguity.
Naming Consistency5/5All tools follow a consistent snake_case pattern with the prefix 'github_skills_' and verb_noun structure, e.g., get_skill, install_skill, list_repositories.
Tool Count5/5With 5 tools, the set is well-scoped for managing GitHub skills. It covers key operations without being overwhelming or insufficient.
Completeness4/5Core operations (get, install, list, search, scaffold) are covered, but missing an uninstall or delete tool is a minor gap. Overall, the surface is fairly complete for its domain.
Average 3.4/5 across 5 of 5 tools scored. Lowest: 2.8/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- 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.
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.jsonto the root of your repository:{ "$schema": "https://glama.ai/mcp/schemas/server.json", "maintainers": [ "your-github-username" ] }Then . Browse examples.
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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?
The description 'download' implies writing to disk, which aligns with readOnlyHint: false but adds no further behavioral details beyond the annotations. It does not mention side effects like directory creation, permissions required, or error scenarios. Annotations already provide non-destructive and non-idempotent hints, so the description adds limited value.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no unnecessary words. It is front-loaded with the core action. However, it could be slightly more structured by including parameter hints, but it is not verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool installs skills to disk and has multiple parameters, the description is too sparse. It does not mention the installation process, the role of parameters, or what the output schema contains (though output schema exists but is not shown). The description lacks completeness for a mutating tool with file system impact.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage at the top level, the description should explain key parameters. It does not mention skill_slug, destination_dir, overwrite, or preserve_repo_prefix, leaving the agent to rely solely on nested schema descriptions. The description fails to add semantic context beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool downloads a skill directory from GitHub to a local folder. This distinguishes it from sibling tools like get_skill (retrieval) or search_skills (search), making the purpose specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 (e.g., get_skill for info, suggest_skill_scaffold for creation). It does not mention prerequisites, such as needing a specific GitHub repository URL, nor does it specify 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?
Annotation already indicate read-only, idempotent, and non-destructive behavior. Description adds that search matches against names and paths, which is useful but not extensive. No mention of pagination, rate limits, or auth requirements. With annotations covering safety, this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence that is front-loaded with the action and resource. No redundant or unnecessary information. Every word carries meaning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema and annotations, the description is moderately complete. However, it lacks mention that the search covers 'configured GitHub repositories' (which appears in the annotation title but not in the description itself). Could also clarify that results are from all registered repositories.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Context indicates 0% schema description coverage, but the actual schema has descriptions for each parameter inside the nested object. Nevertheless, the description does not explain any parameter details, such as what 'query' represents or the effect of 'limit' and 'response_format'. This fails to compensate for the reported low coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool searches skill directories by matching a query against names and paths. It effectively distinguishes itself from sibling tools like get_skill (single skill) and install_skill (installation). However, it could be more specific about the search scope (e.g., across repositories).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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_skill or list_repositories. Does not mention that this is for searching across all configured repos, nor provides examples. The description only states what it does, not when to prefer 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?
Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, openWorldHint=true. The description adds that it uses 'closest existing skills as examples', which provides additional behavioral context but does not contradict annotations. No further behavioral traits (e.g., rate limits, auth needs) are disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that conveys the core purpose without any waste. Every word is meaningful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 3 parameters and an output schema, but the description is minimal. It does not explain what the scaffold contains, how grounding works, or the return structure. While the output schema likely covers return details, the description lacks sufficient contextual completeness for a tool with moderate complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% (description does not mention parameters). The input schema itself contains adequate descriptions for 'request', 'limit', and 'response_format', so the agent can rely on the schema. However, the description fails to compensate for the low coverage by adding any parameter context beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool creates a grounded starter scaffold for a new skill using closest existing skills as examples. This specific verb+resource combination distinguishes it from sibling tools like github_skills_get_skill (retrieve), github_skills_install_skill (install), github_skills_list_repositories (list), and github_skills_search_skills (search).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool should be used when creating a new skill scaffold, but does not explicitly state when to use it versus alternatives or when not to use it. No when-not or exclusion guidance is 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?
Annotations already declare the tool as readOnlyHint, destructiveHint false, idempotentHint true, and openWorldHint true, covering safety. The description adds context about fetching 'key files' from a 'skill directory', but does not disclose additional behavioral details such as authentication or 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that conveys the core action without any superfluous words. It is front-loaded and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one required parameter, output schema present), the description is largely adequate. However, it could be improved by hinting at the typical use case (e.g., after searching skills) or defining 'key files'. The lack of such context slightly reduces completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides zero information about the parameters or their usage; it neither repeats nor elaborates on the schema's detailed property descriptions. Since schema description coverage is 0% (the description does not address parameters), the agent must rely solely on the schema, missing any high-level guidance on parameter selection.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies the verb ('Fetch'), resource ('key files for a specific skill directory'), and source ('from GitHub'), making the purpose unambiguous. It effectively distinguishes from sibling tools (install, list repos, search, suggest scaffold) which have different functions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does 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, nor does it provide exclusions. Usage is implied by the name and description, but no guidance is given on sequencing (e.g., after searching) or scenarios to avoid.
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?
Annotations already indicate readOnlyHint=true, destructiveHint=false, and idempotentHint=true. The description simply states 'List' which is consistent. It does not add behavioral context beyond what annotations provide, such as whether the list is alphabetical or if it refreshes. With annotations covering safety, the description is adequate but not additive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence containing only essential information: verb, resource, and scope. No filler words. This is ideal conciseness and front-loads the key action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (list with one optional format parameter), an output schema exists to document return values. The description is complete enough to understand the tool's purpose and usage. It may lack an explicit note that it only shows configured (not all) repositories, but that is implied by 'configured for this MCP server'. A slight improvement would be stating that the list is pre-configured.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has one parameter (response_format) which is already documented in the schema with a description 'Output format' and enum values. Schema coverage is effectively 100% because the parameter has a schema description. The tool description does not mention or add to parameter semantics, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'List', the specific resource 'GitHub skill repositories', and the scope 'configured for this MCP server'. This distinguishes it from siblings like github_skills_get_skill (retrieves a single skill) and github_skills_search_skills (searches), providing unambiguous purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide explicit guidance on when to use this tool versus alternatives, nor does it state prerequisites or exclusions. However, the purpose is self-evident for listing configured repositories, and the read-only annotations imply safe use. A more explicit note about when to prefer this over search or get would elevate the score.
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.
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