Skill7

Server Quality Checklist

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

Latest release: v1.1.0
Disambiguation3/5
Most tools are distinct, but get_skill and get_skill_content have overlapping purposes since full details likely include content. list_skills and search_skills also have similar retrieval functions, though with different filters.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern with underscores (list, get, search, suggest), making actions predictable. Minor inconsistencies like singular versus plural nouns are acceptable.
Tool Count5/5
Six tools is well-scoped for a skills management and workflow suggestion server, fitting comfortably in the optimal range.
Completeness4/5
The skill browsing surface is well covered with list, get, search, and content retrieval, plus categories. However, there are no tools for creating, updating, or deleting skills, and workflow functionality is limited to suggestion only, leaving some potential dead ends.
Average 3.3/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 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 is passing
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

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It does not disclose return format, error behavior, whether raw content is returned, or any side effects—leaving significant behavioral ambiguity.
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 short sentence with no redundant words. It is appropriately front-loaded and concise, though its brevity contributes 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?
Despite being a simple one-parameter tool with no output schema, the description does not explain return values, usage context, or how it differs from siblings. The lack of annotations increases the need for more contextual detail.
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 only parameter (skillId) with 100% description coverage. The description adds no additional meaning 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb ('Read') and a specific resource ('full SKILL.md content'). It distinguishes the tool from list_skills and search_skills, though it does not explicitly clarify how it differs from get_skill.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus its siblings, no preconditions, and no exclusions. It is a bare statement of function without usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only says 'Search skills by keyword' and reveals nothing about return format, pagination, ordering, default limit behavior, or safety (e.g., read-only). This is a minimal explanation that fails to convey any behavioral trail beyond the tool's name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence: 'Search skills by keyword'. It is front-loaded with the verb and resource, and every word earns its place. No unnecessary information is included.
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?
For a search tool with no output schema and no annotations, the description is too sparse. It does not explain what the search returns, how results are ordered, or how the limit parameter affects results. It also does not clarify when to select this tool over list_skills or get_skill, making it incomplete for an AI agent to use reliably.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 50% (query has a description, limit does not). The description maps to the query parameter but adds no meaning for the limit parameter. Since schema coverage is not high, the description should compensate, but it does not, leaving limit's purpose and default unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Search') and resource ('skills') with a specific method ('by keyword'). This distinguishes it from sibling tools like list_skills and get_skill, making its purpose unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as list_skills or get_skill. It does not mention exclusions or preferred contexts, leaving the agent without explicit decision criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only states 'Get a workflow suggestion', which suggests a read-only operation, but does not disclose what a workflow suggestion is, what the output looks like, or whether any processing is involved.
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?
One short, front-loaded sentence with no wasted words. It is concise and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple, but the description is too sparse. Without an output schema or annotations, the agent has no idea what a workflow suggestion consists of, how it relates to the sibling skill tools, or what to expect in the response.
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% and the single parameter 'goal' is documented. The description adds no new meaning beyond 'for a goal', so it does not improve on 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 uses a specific verb ('Get') and identifies the resource ('a workflow suggestion') plus the intent context ('for a goal'). This clearly distinguishes it from sibling skill-related tools like list_skills 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 Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus the sibling tools. 'For a goal' implies a vague context, but there is no explicit mention of scenarios, prerequisites, 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?
There are no annotations provided, so the description carries the full burden of behavioral disclosure. The description only says 'Get full details' which is read-only by implication, but it does not state this explicitly, nor does it mention any potential errors, permissions, or what 'full details' entails. It offers no behavioral insight beyond what the tool name and schema already convey.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence: 'Get full details of a skill.' It is front-loaded with the verb and resource, contains no filler, and every word contributes to clarity.
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 get-by-ID tool with one parameter and no output schema, the description is minimally adequate but leaves ambiguity. It says 'full details' but does not specify what those details are, nor does it describe the response shape. Given the lack of an output schema, more detail would be helpful for a complete understanding.
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 description coverage is 100% (skillId is described as 'Skill ID'). The description does not add any additional meaning to the parameter beyond what the schema already provides. This meets the baseline for schema-heavy parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the purpose: to get full details of a skill. It uses a specific verb ('Get') and resource ('skill'), which makes the core action unambiguous. However, it does not distinguish itself from sibling tool get_skill_content, which could be seen as overlapping.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage: when you need full details of a skill identified by an ID. It does not explicitly state when to use this over list_skills or search_skills, nor does it mention alternatives or when not to use it. Usage guidance is implied but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It only says 'list skills with optional category filter' and does not mention pagination, sorting, return format, or whether the list is complete or partial. The schema includes limit/offset but their presence is not explained.
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, front-loaded sentence with no unnecessary words, making it easy for an agent to quickly parse its purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple listing tool, the description is minimal but adequate for understanding the core action. However, it lacks details about pagination controls (limit/offset) and doesn't clarify how it differs from search_skills, leaving gaps in completeness given the absence of annotations and output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is only 33% (category alone has a description); limit and offset have no descriptions. The tool description adds no new meaning for these parameters and merely echoes 'optional category filter', which is already present in the schema. It does not compensate for the undocumented parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with the verb 'List' and resource 'skills', and mentions the optional 'category filter', which differentiates it from sibling tools like get_skill (specific skill retrieval) and search_skills (keyword search).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies a general listing use case with optional filtering, but it does not explicitly state when to prefer this over search_skills or get_categories, nor does it mention any exclusions or alternatives.
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 of behavioral disclosure. It indicates a read operation ('Get all') and mentions return content ('with counts'), but does not disclose behavior such as ordering, pagination, or whether empty categories are included.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, front-loaded with the action and resource, and contains no unnecessary words. It earns its place without 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?
For a tool with no parameters and no output schema, the description adequately communicates the purpose and return value. However, it leaves minor ambiguities like sorting order or whether counts include categories with zero skills, which could be clarified.
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, giving a baseline of 4. The description correctly omits parameter details since there are none, and the schema already indicates an empty object.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves all skill categories with counts, using a specific verb and resource. This distinguishes it from sibling tools like list_skills or get_skill, which operate on skills rather than categories.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention suitable contexts, exclusions, or why one might choose get_categories over list_skills or search_skills.
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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