MCP Project Initializer

by Syndicats

Overview Schema Related Servers Score Discussions

TypeScript

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Server Quality Checklist

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

Latest release: v0.1.0
Disambiguation4/5
Most tools have distinct purposes in the MCP project creation workflow, but 'setup_project_foundation' and 'generate_mcp_server' could potentially overlap in scope regarding project structure creation. The descriptions clarify that 'setup_project_foundation' handles initial structure with documentation while 'generate_mcp_server' creates the full implementation, but the boundary isn't perfectly clear.
Naming Consistency5/5
All tools follow a consistent verb_noun naming pattern with clear action-oriented verbs (add, confirm, generate, get, set, setup, start) followed by descriptive nouns. The naming convention is uniform throughout the entire toolset with no mixing of styles or conventions.
Tool Count5/5
10 tools is an appropriate number for a project initialization server that guides users through a multi-step process. Each tool appears to serve a specific purpose in the workflow, from starting the process to setting requirements to generating the final implementation.
Completeness4/5
The toolset covers the complete project creation lifecycle from initiation to implementation, with good coverage of requirements gathering, configuration, and generation steps. A minor gap exists in modification capabilities - once a project is generated, there's no clear way to update or modify existing project elements beyond the initial creation flow.
Average 3/5 across 10 of 10 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 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.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions adding documentation but fails to specify whether this is a creation, update, or append operation, what permissions are required, or how it interacts with existing project data. This lack of detail makes it difficult for an agent to predict outcomes accurately.
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, efficient sentence that directly states the tool's function without unnecessary words. It is front-loaded with the core action and resource, making it easy to parse quickly, which is ideal for conciseness in tool selection.
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?
Given the lack of annotations and output schema, the description is incomplete for a tool that modifies project data. It doesn't explain what happens after adding documentation (e.g., success indicators, error handling, or impact on the project), leaving gaps in understanding the tool's full behavior and outcomes.
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 has 100% description coverage, clearly defining both parameters ('documentationUrls' and 'customContext'). The description adds no additional meaning beyond the schema, such as examples or constraints, but since the schema is comprehensive, a baseline score of 3 is appropriate as it doesn't detract from understanding.
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 action ('Add') and the target ('additional documentation, API specs, or links to the project'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'set_project_description', which might handle similar content, leaving room for ambiguity in tool selection.
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 'set_project_description' or other sibling tools. There are no explicit instructions on prerequisites, context, or exclusions, leaving the agent to infer usage based on the tool name alone.
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 provided, the description carries the full burden of behavioral disclosure. It describes the tool's function but lacks critical behavioral details such as whether this triggers side effects, requires specific user permissions, or how it integrates with workflow steps. The description doesn't compensate for the missing annotations.
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, clear sentence with no wasted words. It's front-loaded with the core purpose and efficiently communicates the essential action without unnecessary elaboration.
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?
Given no annotations and no output schema, the description is incomplete for a tool that likely triggers workflow progression. It doesn't explain what happens after confirmation, return values, or error conditions, leaving significant gaps in understanding the tool's role and effects.
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 100% description coverage, so the baseline is 3. The description adds value by emphasizing that the user must 'explicitly confirm' and 'proceed to the next step,' which provides context beyond the schema's enum values, though it doesn't detail parameter syntax or format further.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool's purpose as capturing user confirmation to proceed to the next step, which is clear but somewhat vague about what 'next step' refers to in context. It doesn't distinguish this tool from potential sibling confirmation tools (though none are listed), but it's not a tautology of the name.
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 or prerequisites. It implies usage when user confirmation is needed but doesn't specify context, timing, or exclusions, leaving the agent to infer when this is 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 are provided, so the description carries the full burden of behavioral disclosure. It states the tool generates a PRD but lacks details on what 'comprehensive' entails, whether it's a read-only or write operation, potential side effects (e.g., creating files), or output format. For a tool with no annotation coverage, this is a significant gap in transparency about its behavior and 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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core function ('generate a comprehensive PRD') and avoids redundancy. Every part of the sentence contributes to understanding the tool's role.
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?
Given the complexity of generating a PRD, no annotations, and no output schema, the description is incomplete. It doesn't explain what the PRD includes (e.g., 'detailed requirements, architecture, and implementation plan' are only hinted in the schema), how the output is delivered, or error handling. For a tool with significant behavioral implications, more context is needed to guide an agent effectively.
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 description doesn't explicitly mention parameters, but the input schema has 100% coverage with a single parameter 'description' well-documented as a 'high-level overview'. Since schema coverage is high, the baseline is 3. The description implies the parameter is used for requirements input but adds no extra semantic context beyond what the schema provides.
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 tool's purpose: to 'generate a comprehensive Product Requirements Document (PRD)' from provided requirements. It specifies the verb ('generate') and resource ('PRD'), making the function understandable. However, it doesn't explicitly differentiate from sibling tools like 'add_project_documentation' or 'generate_mcp_server', which may have overlapping documentation-related functions.
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 mentions that the AI will generate a PRD, but doesn't specify prerequisites, timing (e.g., early in project setup), or how it relates to siblings like 'set_project_name' or 'setup_project_foundation'. Without this context, an agent might struggle to choose this tool appropriately in a workflow.
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 provided, the description carries full burden for behavioral disclosure. It states 'Set' which implies a write/mutation operation, but doesn't disclose whether this requires specific permissions, whether the change is reversible, what happens to existing technology settings, or any side effects. The description adds minimal behavioral context beyond the basic action.
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, clear sentence with zero wasted words. It's front-loaded with the essential information and doesn't contain any unnecessary elaboration. This is an excellent example of concise technical documentation.
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 mutation tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what happens after setting the technology stack, whether there are dependencies on other setup steps, what validation occurs, or what the expected outcome should be. The agent would need to guess about the tool's behavior and effects.
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 has 100% description coverage and clearly documents the single 'technology' parameter with its enum values. The description doesn't add any parameter semantics beyond what's already in the schema - it doesn't explain what 'technology stack' means in practice or provide usage examples. Baseline 3 is appropriate when schema coverage is complete.
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 action ('Set') and the resource ('technology stack for the MCP server'), making the purpose immediately understandable. It doesn't explicitly differentiate from siblings like set_project_name or set_project_description, but the specificity of 'technology stack' provides reasonable distinction.
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 like set_project_name or set_project_description. There's no mention of prerequisites, sequencing (e.g., whether this should come before or after other setup steps), or what happens if called multiple times.
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 of behavioral disclosure. It states this is a generation tool but doesn't clarify if it's a read-only operation, what permissions are needed, whether it overwrites existing files, or what the output entails (e.g., file creation, code generation). For a tool with zero annotation coverage, this is a significant gap in transparency.
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, efficient sentence that front-loads the key action ('generate'). It avoids unnecessary words, though it could be slightly more structured by explicitly mentioning dependencies or outcomes. Every word earns its place, making it appropriately concise.
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?
Given the complexity of generating a complete MCP server, the description is incomplete. With no annotations, no output schema, and minimal behavioral details, it fails to provide enough context for an agent to understand the tool's full impact, such as what 'complete implementation' includes or how it interacts with other project setup tools. This is inadequate for a potentially high-stakes generation tool.
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 0 parameters with 100% coverage, so no parameter documentation is needed. The description adds context by implying the generation is 'based on all gathered requirements,' which provides semantic meaning beyond the empty schema, though it doesn't detail what those requirements are. Baseline is 4 for zero parameters.
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 action ('generate') and the target resource ('complete MCP server implementation'), making the purpose understandable. However, it doesn't differentiate this tool from its siblings like 'setup_project_foundation' or 'start_mcp_project', which might have overlapping scopes in the MCP project workflow.
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 mentions 'based on all gathered requirements' but doesn't specify what constitutes 'gathered requirements' or how this relates to sibling tools like 'setup_project_foundation' or 'confirm_and_proceed', leaving the agent with no explicit usage context.
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 of behavioral disclosure. It states the tool retrieves status, implying a read operation, but doesn't disclose any behavioral traits such as permissions needed, rate limits, error conditions, or what the status response includes. For a tool with zero annotation coverage, this is a significant gap in transparency.
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, clear sentence: 'Get the current status of the project creation conversation.' It is front-loaded with the core purpose, has zero wasted words, and is appropriately sized for a simple tool, earning the highest score for efficiency.
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?
Given the complexity of a status-checking tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the status entails (e.g., stages, errors, progress), how it's formatted, or any dependencies. For a tool that likely returns meaningful state information, more context is needed to guide the agent effectively.
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 0 parameters with 100% coverage, meaning there are no parameters to document. The description doesn't need to add parameter semantics beyond the schema, so it meets the baseline of 4 for tools with no parameters, as it doesn't contradict or omit any parameter information.
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 tool's purpose: 'Get the current status of the project creation conversation.' It uses a specific verb ('Get') and identifies the resource ('status of the project creation conversation'). However, it doesn't explicitly differentiate from sibling tools like 'confirm_and_proceed' or 'setup_project_foundation' that might also relate to conversation states, so it doesn't reach the highest score.
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 doesn't mention prerequisites, timing, or how it differs from sibling tools such as 'confirm_and_proceed' or 'setup_project_foundation' in the context of project creation conversations. This leaves the agent with minimal context for tool selection.
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 provided, the description carries full burden for behavioral disclosure. It states 'Set' implies a mutation/write operation, but doesn't clarify permissions needed, whether the change is reversible, error conditions, or side effects. For a mutation tool with zero annotation coverage, this leaves significant behavioral gaps unaddressed.
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, efficient sentence that states the tool's purpose without unnecessary words. It's appropriately sized for a simple tool with one parameter and is front-loaded with the essential information. Every word earns its place with zero waste.
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 mutation tool with one parameter and no output schema, the description covers the basic purpose adequately. However, without annotations or output schema, it should ideally provide more behavioral context about the mutation operation. The description is minimally complete but leaves gaps that could help an agent use it more effectively.
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%, with the single parameter 'name' fully documented in the schema. The description adds no additional parameter information beyond what's already in the structured schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.
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 action ('Set') and target resource ('name for the MCP server project'), making the purpose immediately understandable. It distinguishes itself from siblings like 'set_project_description' and 'set_project_technology' by specifying it handles the project name specifically. However, it doesn't explicitly contrast with all siblings, preventing a perfect score.
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 doesn't mention prerequisites (e.g., whether a project must exist first), timing considerations, or relationships with siblings like 'set_project_description' or 'setup_project_foundation'. Without any usage context, the agent must infer when this tool is 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 are provided, so the description carries the full burden. It mentions 'interactive process' but doesn't clarify what that entails—e.g., whether it prompts for user input, requires specific permissions, has side effects, or what the expected behavior is. This leaves significant gaps in understanding the tool's 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 a single, efficient sentence that directly states the tool's purpose without any fluff. It's front-loaded and appropriately sized for a no-parameter tool, making it 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?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'interactive process' means, what happens after starting, or any behavioral context. For a tool that likely initiates a multi-step workflow, more detail is needed to guide effective use.
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 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate. Baseline is 4 for zero parameters, as it avoids unnecessary information.
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 action ('begin the interactive process') and resource ('creating a new MCP server project'), making the purpose evident. It doesn't explicitly differentiate from sibling tools like 'generate_mcp_server' or 'setup_project_foundation', which might have overlapping functionality, so it doesn't reach the highest score.
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. With siblings like 'generate_mcp_server' and 'setup_project_foundation', it's unclear if this is an initial step, a wrapper, or a distinct process. No explicit when/when-not or alternative usage is 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the directory must be absolute, but doesn't cover critical aspects like whether this creates directories, requires permissions, has side effects, or what happens on success/failure. For a tool that likely modifies project state, this is a significant gap in transparency.
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, efficient sentence that's front-loaded with the essential information. Every word earns its place by emphasizing 'ABSOLUTE' and clarifying the tool's purpose without unnecessary elaboration.
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?
Given this is likely a state-modifying tool with no annotations and no output schema, the description is insufficient. It doesn't explain what the tool returns, what happens after setting the directory, or how it interacts with the broader project setup workflow. For a tool with one parameter but potentially significant behavioral implications, more context is needed.
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%, so the schema already fully documents the single parameter. The description adds no additional parameter semantics beyond what's in the schema (both emphasize 'ABSOLUTE' and provide similar examples). This meets the baseline of 3 when schema does the heavy lifting.
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 specific action ('Set') and resource ('ABSOLUTE directory path where the project should be created'), distinguishing it from siblings like set_project_name or set_project_description. It precisely defines what the tool does without being vague or tautological.
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. While it specifies the directory must be absolute, it doesn't indicate prerequisites (e.g., whether this should be called before or after other setup steps), exclusions, or relationships with sibling tools like setup_project_foundation or start_mcp_project.
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 states 'Create' but doesn't disclose behavioral traits such as whether this is idempotent, what permissions are required, if it overwrites existing structures, or what the output looks like. For a creation tool with zero annotation coverage, this is a significant gap in transparency.
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, efficient sentence that front-loads the core action ('Create the project structure') and details the components (rules, documentation, PRD). There is zero waste or redundancy, making it highly concise and well-structured for quick understanding.
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 0 parameters, no annotations, and no output schema, the description is minimally adequate. It explains what the tool does but lacks details on behavior, output, or integration with siblings. For a creation tool, it should ideally cover more about effects and dependencies, but the simplicity of the schema keeps it from being incomplete.
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 0 parameters with 100% coverage, so no parameter documentation is needed. The description adds value by specifying what gets created (rules, documentation, PRD), which provides semantic context beyond the empty schema. Baseline is 4 for 0 parameters, as the description appropriately focuses on outcomes rather than inputs.
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 action ('Create') and the resource ('project structure'), specifying what gets created (rules, documentation, PRD). It distinguishes from siblings like 'set_project_name' or 'add_project_documentation' by covering broader foundational setup. However, it doesn't explicitly contrast with 'start_mcp_project' or 'generate_mcp_server', which might overlap in purpose.
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 explicit guidance on when to use this tool versus alternatives is provided. The description implies it's for initial project setup, but it doesn't specify prerequisites (e.g., after setting project name or directory) or exclusions (e.g., not for incremental updates). With siblings like 'add_project_documentation' for specific tasks, the lack of comparative context leaves usage ambiguous.
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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