SkillForge MCP
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool serves a distinct purpose: configure manages settings, get retrieves skill content, invoke executes a skill, lists skills, and reload rescans folders. No overlap or ambiguity.
Naming Consistency5/5All tools use a consistent 'skills__verb' pattern with clear verbs (configure, get, invoke, list, reload) indicating actions on the skill resource.
Tool Count4/55 tools is reasonable for a skill management server, covering core operations. Slightly low but appropriate for the focused domain.
Completeness4/5Covers listing, reading, invoking, configuring settings, and rescanning. Missing explicit create/update/delete for individual skill content, but the configure and reload tools handle folder-level changes.
Average 3.2/5 across 5 of 5 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 39 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.
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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 provided, so description must cover behavioral traits. It doesn't mention whether the operation is read-only, has side effects, requires authentication, or returns paginated results. 'List available skills' implies safe reading but is insufficient.
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?
One sentence, no wasted words. Clearly communicates the core function. Could be more informative without losing conciseness, but it is appropriately front-loaded.
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 3 optional parameters, no annotations, no output schema, and nearby siblings, the description is incomplete. It does not explain what 'available' means, the output format, or how filters interact. Leaves agent to guess.
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%, so description must compensate. It lists parameters (folder, search, source) but provides no details on their format, default behavior, or how they combine. The phrase 'optionally filtered' adds minimal value.
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?
The description clearly states it lists available skills with optional filtering, using specific verbs and resource. It distinguishes from siblings like skills__configure, skills__get, skills__invoke, skills__reload by focusing on listing rather than configuring, retrieving a single skill, invoking, or reloading.
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 (e.g., when to use skills__get instead). Lacks context about prerequisites or scenarios where filtering would be appropriate.
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 exist, so the description carries full responsibility for behavioral disclosure. It only mentions invocation and input forwarding, omitting side effects, error behavior, authorization needs, or whether it is read-only/destructive.
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 short sentence with no wasted words. It is concise and front-loaded, but additional structure (e.g., separating purpose and parameter notes) could improve clarity without harming conciseness.
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 lack of annotations, output schema, and parameter context, the description is insufficient. It does not specify return values, error conditions, or when to prefer this over sibling tools, leaving the agent underinformed.
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?
With 0% schema description coverage, the description should compensate but only glosses over parameters (name, input). It does not explain what constitutes a valid name, the expected format of input, or any constraints beyond the schema's type/default.
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 action (invoke), the resource (skill), and the mechanism (by name, forwarding input). It distinguishes from siblings like `skills__list` or `skills__configure` which are different operations.
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 is provided on when to use this tool versus its siblings, nor any conditions or prerequisites. The description implicitly suggests it is for executing a skill but lacks explicit usage context.
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 description indicates a read operation (retrieve) but lacks explicit statements about safety, permissions, or side effects. Since no annotations are provided, the description carries the burden; however, for a simple retrieval, the minimal description is adequate but not thorough.
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 that front-loads the key information. It is efficient and easy to parse, 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.
Completeness3/5Given 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 minimally complete. It explains the return value (body + metadata) but omits context like how to obtain skill names or any relationship to sibling tools, which limits completeness for an agent.
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?
The input schema has no descriptions, and the tool description adds no meaning beyond stating that the parameter 'name' refers to a skill's name. With 0% schema coverage, the description should compensate by explaining what constitutes a valid name (e.g., format, where to obtain it), but it does not.
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 states the verb 'Retrieve' and specifies the resource as 'full content (body + metadata) of a named skill.' This clearly distinguishes it from sibling tools like skills__list (which likely lists names only) and skills__configure/invoke/reload (which perform other actions).
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 is provided on when to use this tool versus alternatives. For example, it does not explain that skills__get is for full details while skills__list is for summaries, nor does it mention any prerequisites like needing the skill name from prior listing.
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 description explicitly states that the tool mutates persisted config under defaultConfigPath(), which is a key behavioral disclosure. However, it does not elaborate on side effects, reversibility, or error conditions, partially informing the agent.
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 concise with two sentences that efficiently convey the core purpose and key behavioral trait. No unnecessary words or fluff.
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 no output schema, no annotations, and 0% schema parameter coverage, the description is too brief. It fails to explain the action enum values or how parameters interact, leaving the agent with insufficient context to use the tool correctly.
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?
With 0% schema description coverage and no elaboration in the description, the parameter semantics are underdefined. The description mentions 'folders' and 'blacklist' but does not map them to schema parameters or explain their usage.
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 it manages configured skill folders, blacklist, and reset to defaults, which distinguishes it from sibling tools like skills__get or skills__invoke. It uses specific verbs and resources.
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, nor does it explain the context for different actions. It merely states what it does without usage context.
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 description discloses the rescan is global and the folder parameter is for validation only, but does not mention potential side effects, auth needs, or performance impact. Since annotations are absent, more detail would be beneficial.
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?
Two sentences with no wasted words. The action and output are front-loaded. Efficient structure.
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 no output schema, it describes the return value (diff and errors). The single optional parameter is explained. Could mention synchronous/asynchronous nature, but overall fairly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has no description for the parameter; the description adds meaning by explaining the folder parameter is for validation and the rescan remains global. This compensates for the 0% schema coverage.
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 action (force a full rescan) and what it returns (diff and per-file errors). It distinguishes from siblings like skills__configure and skills__list.
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 vs alternatives like skills__get or skills__invoke. The description does not mention prerequisites or context.
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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