Structured Workflow MCP
Structured Workflow MCP Server
NOTE: I am not currently working on this or actively maintaining it. I learned a few things about prompting and agents while making this MCP server. It has a lot of very valuable ideas that could be used or improved upon as an MCP server but I'm also looking at ways to incorporate the core ideas into Agents, for example, in Claude. The core idea here is that AI should follow specific, pre-determined steps to solving a problem, just like we as humans might do and there may be other ways to achieve this apart from this MCP server.
An MCP server that enforces disciplined programming practices by requiring AI assistants to audit their work and produce verified outputs at each phase of development.
Why I Built This
TLDR: I got tired of repeating "inventory and audit first" across every AI platform and prompt, so I built an MCP server that automatically enforces this disciplined approach. It forces AI to think systematically and follow structured phases instead of jumping straight into code changes.
So I've built an MCP server that fits into my workflow and thinking process while I'm programming. I made it available via npx and you can download it yourself if you want something local.
In essence I was doing some repeated tasks with AI where I wanted it to complete refactoring work for part of a larger project. I was struggling because it was often missing or glossing over key things: classes or systems that already exist (a preferences service for example), creating duplicates of things, or when correcting mistakes, leaving orphaned unused methods/code around places, and when writing tests it would often pull in the wrong imports or put these together in the wrong way resulting in syntax errors but would jump straight into writing the next test without fixing the first one that was broken.
I sort of stumbled on this idea of the model needing to perform an audit and inventory of the current project (or not even the whole project--just one layer or feature in a project) before moving to any kind of implementation phase and it needed a lint iterate lint phase. I tried this with rules with limited success and then prompting with much better success but I was constantly repeating myself.
So I started noodling on this idea of an MCP server that forced the AI to work through a problem in phases or lanes. So that's what this does. There's a number of different workflow styles and I'm open to any other ideas or improvements.
Feel free to check it out if it helps your use case. It's a work in progress but it has been doing a pretty great job for what I'm using it for now. Happy to share more if you are interested.
Related MCP server: Universal Spec Architect
Features
Enforced Workflow Phases - AI must complete specific phases in order (setup, audit, analysis, planning, implementation, testing, etc.)
Mandatory Output Artifacts - Each phase requires structured documentation or verified outputs before proceeding
Multiple Workflow Types:
Refactor workflows for code improvement
Feature development with integrated testing
Test-focused workflows for coverage improvement
Test-driven development (TDD) cycles
Custom workflows for specialized needs
Output Verification - The server validates that outputs contain meaningful content and proper structure
Session State Management - Tracks progress and prevents skipping phases
How It Works
Here's how the AI moves through a structured workflow:
graph TD
A[🚀 Start Workflow] --> B[AI Gets Phase Guidance]
B --> C{Create Phase Output}
C --> D[Auto-Save with Numbered Naming<br/>00-setup-confirmation-2025-01-07.md]
D --> E[Phase Validation]
E --> F{All Phases Done?}
F -->|No| G[Move to Next Phase]
G --> B
F -->|Yes| H[Workflow Complete!]
style A fill:#e1f5fe
style B fill:#f3e5f5
style C fill:#fff3e0
style D fill:#e8f5e8
style E fill:#fff9c4
style H fill:#e8f5e8What happens at each step:
Start Workflow - AI calls a workflow tool (refactor_workflow, create_feature_workflow, etc.)
AI Gets Phase Guidance - Server provides specific instructions for current phase (audit, analyze, implement, etc.)
Create Phase Output - AI works through the phase and creates documentation/artifacts
Auto-Save - Files are automatically saved with numbered naming in task directories
Phase Validation - Server validates outputs meet requirements before proceeding
Next Phase - Process repeats until workflow is complete
One benefit of this breakdown is that the AI agent receive instruction sets that are relevant to the current phase and not the entire workflow. This can help prevent the AI from getting lost in the weeds of the entire workflow and instead focus on the current phase. An interesting article on this can be read here: LLMs Get Lost In Multi-Turn Conversation
Workflow Output
AI-Generated Documentation
The server suggests numbered workflow files as you progress through phases. The AI assistant handles the actual file creation using its own tools:
workflows/
├── your-task-name/
│ ├── 01-audit-inventory-2025-01-04.md
│ ├── 02-compare-analyze-2025-01-04.json
│ ├── 03-question-determine-2025-01-04.md
│ ├── 04-write-or-refactor-2025-01-04.md
│ ├── 05-test-2025-01-04.json
│ ├── 06-lint-2025-01-04.json
│ ├── 07-iterate-2025-01-04.md
│ └── 08-present-2025-01-04.mdWorkflow Architecture
File Handling: The server provides suggested paths and formats but does not directly write files. Instead, it instructs the AI assistant to create these files using its own file system access.
Consistent Naming: Files follow a standardized naming convention with phase numbers, names, and timestamps.
Environment Independence: The architecture works across any environment where the AI has appropriate file system permissions.
Graceful Degradation: If the AI is unable to create files, the workflow continues in memory-only mode - your progress isn't interrupted.
Installation
Quick Start (Recommended) - Zero Installation
Add to your AI assistant config - Uses npx automatically:
💡 Note: I recommend using
@latestto ensure you always get the newest features and fixes. Without@latest, npx may cache older versions.
VS Code / Cursor / Windsurf - Add to your MCP settings:
{
"mcp": {
"servers": {
"structured-workflow": {
"command": "npx",
"args": ["structured-workflow-mcp@latest"],
"env": {}
}
}
}
}Claude Desktop - Add to your claude_desktop_config.json:
{
"mcpServers": {
"structured-workflow": {
"command": "npx",
"args": ["structured-workflow-mcp@latest"],
"env": {}
}
}
}Global Installation (Optional)
You can install globally on your machine using NPM:
npm install -g structured-workflow-mcpThen use in your AI assistant config:
{
"mcp": {
"servers": {
"structured-workflow": {
"command": "structured-workflow-mcp",
"args": [],
"env": {}
}
}
}
}With custom output directory:
{
"mcp": {
"servers": {
"structured-workflow": {
"command": "structured-workflow-mcp",
"args": ["--output-dir", "/home/user/workflow-outputs"],
"env": {}
}
}
}
}Manual Installation
For developers, you can clone the repository and build it locally:
git clone https://github.com/kingdomseed/structured-workflow-mcp
cd structured-workflow-mcp
npm install && npm run buildUsage
Once configured in your AI assistant, start with these workflow tools:
mcp__structured-workflow__build_custom_workflow- Create custom workflowsmcp__structured-workflow__refactor_workflow- Structured refactoringmcp__structured-workflow__create_feature_workflow- Feature developmentmcp__structured-workflow__test_workflow- Test coverage workflows
Example Output Artifacts
The server enforces that AI produces structured outputs like these:
AUDIT_INVENTORY Phase Output:
{
"filesAnalyzed": ["lib/auth/user_service.dart", "lib/auth/auth_middleware.dart"],
"dependencies": {
"providers": ["userProvider", "authStateProvider"],
"models": ["User", "AuthToken"]
},
"issues": [
"Single Responsibility Principle violation - handles too many concerns",
"File approaching 366 lines - recommended to keep widgets smaller"
],
"changesList": [
{
"action": "CREATE",
"file": "lib/auth/components/auth_form.dart",
"description": "Extract authentication form logic",
"justification": "Component focused on form validation only"
}
]
}COMPARE_ANALYZE Phase Output:
{
"approaches": [
{
"name": "Incremental Component Extraction",
"complexity": "Medium",
"risk": "Low",
"timeEstimate": "30-45 minutes"
}
],
"recommendation": "Incremental Component Extraction",
"justification": "Provides best balance of benefits vs. risk",
"selectedImplementationOrder": [
"1. Extract form component (lowest risk)",
"2. Create validation service",
"3. Refactor main view"
]
}Each phase requires documented analysis and planning before the AI can proceed to implementation.
Tools
Workflow Entry Points
refactor_workflow - Start a structured refactoring process with required analysis and planning phases
create_feature_workflow - Develop new features with integrated testing and documentation requirements
test_workflow - Add test coverage with mandatory analysis of what needs testing
tdd_workflow - Implement Test-Driven Development with enforced Red-Green-Refactor cycles
build_custom_workflow - Create workflows with custom phases and validation requirements
Phase Guidance Tools
audit_inventory_guidance - Forces thorough code analysis and change cataloging
compare_analyze_guidance - Requires evaluation of multiple approaches with pros/cons
question_determine_guidance - Mandates clarification and finalized planning
phase_output - Validates and records structured outputs from each phase
workflow_status - Check current progress and validation state
Usage
The server enforces structured workflows through mandatory phases. Each workflow type has different phase requirements:
Refactor Workflow: AUDIT_INVENTORY → COMPARE_ANALYZE → QUESTION_DETERMINE → WRITE_OR_REFACTOR → LINT → ITERATE → PRESENT
Feature Workflow: PLANNING → QUESTION_DETERMINE → WRITE_OR_REFACTOR → TEST → LINT → ITERATE → PRESENT
Test Workflow: AUDIT_INVENTORY → QUESTION_DETERMINE → WRITE_OR_REFACTOR → TEST → ITERATE → PRESENT
TDD Workflow: PLANNING → WRITE_OR_REFACTOR → TEST → (Red-Green-Refactor cycles) → LINT → PRESENT
Input Validation
The server requires:
task(string): Description of what you want to accomplishoutputArtifacts(array): Structured documentation for each completed phase
Output Validation
Each phase completion is validated for:
Meaningful content length (minimum 10 characters)
Valid JSON format for structured outputs
Phase-specific content requirements
Proper documentation of decisions and analysis
Safety Rule
Files must be read before modification. This prevents accidental data loss and ensures informed changes.
Development
npm run dev # TypeScript compiler in watch mode
npm run lint # Run linter
npm run typecheck # Type checking
npm test # Run testsHow It Works
AI starts a workflow using one of the entry point tools
Server creates a session and tracks phase progression
Each phase requires specific outputs before proceeding
The
phase_outputtool validates artifacts have meaningful contentAI cannot skip phases or claim completion without verified outputs
Session state prevents circumventing the structured approach
Testing the MCP Server
You can quickly try out the Structured Workflow MCP server using the test prompts and helper scripts included in this repository.
Build the server (if you haven't already):
npm run buildStart the server:
node dist/index.jsOpen the test prompt
docs/test_prompt/mcp_server_test_prompt.mdin your preferred MCP-compatible AI client and paste the contents.Alternatively, open the sample project located in
refactor-test/for an end-to-end refactor workflow demo. Follow the steps in itsREADME.mdto run and observe the structured workflow in action.Watch the AI progress through each phase and verify the structured outputs produced.
Sample Prompts
The docs/sample_prompts directory contains several ready-to-use prompts illustrating typical workflows:
feature_workflow_prompt.mdrefactor_workflow_prompt.mdtest_workflow_prompt.mdtdd_workflow_prompt.mdcustom_workflow_prompt.md
Use these as a starting point and adapt them to your projects.
Building
npm install
npm run buildThe server uses TypeScript with the @modelcontextprotocol/sdk and runs locally via stdio transport.
Pull Requests Welcome
I welcome and encourage pull requests! Whether you're fixing bugs, adding features, or improving documentation, your contributions are valuable.
Please follow these steps:
Fork the repository on GitHub.
Create a new branch:
git checkout -b feature/your-feature.Make your changes and commit with clear, descriptive messages.
Write tests for any new functionality and ensure all existing tests pass.
Push to your branch:
git push origin feature/your-feature.Open a pull request and describe your changes clearly.
See CONTRIBUTING.md for more details, if available.
Thank you for contributing!
License
This MCP server is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License.
Available Tools
20 toolsaudit_inventory_guidanceA
Get guidance for the AUDIT_INVENTORY phase - analyze code and catalog changes
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only states it provides guidance, but does not mention whether it is read-only, requires authentication, or what 'guidance' entails (e.g., textual steps, examples).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently conveys the purpose and scope. It is front-loaded with the phase name and action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is sufficient for a no-parameter tool but lacks details about the output or how guidance is presented. With no output schema, more context on the format (e.g., text, list) would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, so the description does not need to add parameter semantics. The baseline is 4 for no parameters, and the description is adequate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it provides guidance for the AUDIT_INVENTORY phase, specifying the action 'analyze code and catalog changes'. This distinguishes it from sibling guidance tools focused on other phases (e.g., iterate_guidance, setup_guidance).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage during the AUDIT_INVENTORY phase but lacks explicit when-to-use or when-not-to-use guidance. No alternatives are mentioned despite multiple sibling guidance tools existing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
build_custom_workflowA
Build a custom workflow with full control over phases and configuration. Use specific workflow tools (refactor_workflow, create_feature_workflow, etc.) for optimized presets.
| Name | Required | Description | Default |
|---|---|---|---|
| task | Yes | Description of the programming task | |
| workflowType | No | Use a predefined workflow type or custom for full control | custom |
| selectedPhases | No | Select which phases to include in your workflow | |
| iterationLimits | No | Set iteration limits before escalation to user input | |
| outputPreferences | No | ||
| userCheckpoints | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden for behavioral disclosure. The description only states the tool's purpose and alternatives, but fails to disclose important behavioral traits such as whether it creates a new workflow, modifies an existing one, requires authentication, or has any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, front-loaded with the core purpose, and immediately followed by guidance on alternatives. Every sentence adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 6 parameters including nested objects, and no output schema. The description is too brief to cover the tool's complexity. It does not explain what the tool returns, how iteration limits work, or typical usage patterns, leaving gaps for an AI agent to understand the full context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes parameters well with coverage of 67%. The description adds minimal extra meaning beyond stating 'full control over phases and configuration', which is already implied by the schema. Baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Build' with 'custom workflow' as the resource, clearly distinguishing the tool's purpose. It explicitly contrasts with sibling tools by noting that optimized presets are available via refactor_workflow, create_feature_workflow, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool ('for full control') vs when to use alternatives ('Use specific workflow tools for optimized presets'). This gives a clear decision criterion.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
compare_analyze_guidanceA
Get guidance for the COMPARE/ANALYZE phase - evaluating approaches
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears full responsibility for behavioral disclosure. It only states that the tool 'gets guidance,' which is a minimal read behavior. It does not describe what the guidance consists of, whether it is static or dynamic, or any side effects. The description lacks transparency about the tool's actual behavior beyond its basic function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that communicates the tool's purpose without any superfluous words. It is well-structured and front-loaded with the key action and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no parameters, no output schema, and no annotations. The description states its purpose but does not elaborate on the form or content of the returned guidance, nor does it provide context about how the guidance relates to the broader workflow. It is minimally complete for a simple guidance tool but lacks depth.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema is empty, so schema coverage is 100% by default. The description does not add any parameter information, but none is needed since there are no parameters. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
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 get guidance for the COMPARE/ANALYZE phase, specifically for evaluating approaches. The verb 'get' and resource 'guidance' are specific, and the phase name distinguishes it from sibling guidance tools for other phases (e.g., audit, iterate, test).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool should be used during the COMPARE/ANALYZE phase by naming that phase, but it does not explicitly state when to use or when not to use it, nor does it mention alternatives among the sibling guidance tools. Usage guidance is implicit but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
create_feature_workflowC
Start a structured workflow for adding new functionality with integrated testing
| Name | Required | Description | Default |
|---|---|---|---|
| task | Yes | Description of the feature to create | |
| context | No | Additional context (optional) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description mentions 'structured workflow' and 'integrated testing' but does not disclose what actions are taken, such as file creation, test execution, or user prompts. The agent has little insight into side effects or required permissions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence is concise and front-loaded with the key action. However, it could benefit from a second sentence to clarify scope or output.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a workflow tool with nested parameters and no output schema, the description is too brief. It lacks details on workflow steps, return value, or integration with sibling tools. Incomplete for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema covers 100% of parameters with descriptions. The description adds no additional meaning beyond the schema, which already explains 'task' and 'context' with sub-properties. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Start' and resource 'structured workflow for adding new functionality with integrated testing'. It distinguishes from siblings like tdd_workflow and test_workflow by emphasizing integrated testing, but could be more specific about the unique workflow.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does 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. No prerequisites or conditions provided. The user must infer from context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
discover_workflow_toolsA
List the workflow guidance tools provided by this MCP server
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must cover behavioral traits. It only states the action (list), but does not disclose whether the operation is read-only, requires authentication, or what happens if no tools are available. For a benign listing tool, this is minimally adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the key information. Every word is necessary, with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no parameters, no output schema), the description is sufficiently complete. It explains what the tool does without needing extra details about return format, as a list of tool names is straightforward.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no parameters (100% coverage), so the description adds no param-specific details. However, the baseline for zero parameters is 4, and the description adds the context that tools are from 'this MCP server', which is useful beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'List' and the resource 'workflow guidance tools provided by this MCP server'. It distinguishes the tool from siblings, which are individual guidance or workflow tools, making it clear this is a discovery endpoint.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context (when you need to see available tools), but lacks explicit when-not or alternative tools. However, for a simple listing tool, the context is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
iterate_guidanceA
Get guidance for the ITERATE phase - fixing issues
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits such as whether the tool is read-only, requires authentication, or has side effects. The description adds no behavioral context beyond the name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words. It could be slightly more informative, but it is appropriately concise for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no parameters and no output schema, so the description carries full weight. It explains the phase and purpose adequately but lacks details on the type of guidance provided, making it minimally complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has no parameters; schema coverage is 100%. With zero parameters, the baseline is 4. The description adds no parameter details, but none are needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool provides guidance for the ITERATE phase with the specific focus of 'fixing issues'. This distinguishes it from sibling guidance tools for other phases.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use during the ITERATE phase when fixing issues, but provides no explicit guidance on when to use versus other guidance tools or any exclusions. Context signals show no additional hints.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
lint_guidanceA
Get guidance for the LINT phase - verifying code quality
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavioral traits. It only states the purpose and does not disclose any side effects, authorization needs, or expected behavior (e.g., read-only, caching). For a query-like tool, this is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is front-loaded and concise. Every word earns its place, with no waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters, no output schema, and a simple purpose, the description is largely complete. However, it could be improved by mentioning that it provides guidance specific to code quality verification during linting, which is slightly redundant but sufficient. Sibling differentiation is implicit via the phase name.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has no parameters, and the schema coverage is 100%. The description adds no additional meaning beyond the schema, but the baseline for zero parameters is 4 according to guidelines.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
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 get guidance for the LINT phase, specifically verifying code quality. It uses a specific verb and resource, and it distinguishes itself from sibling tools like test_guidance or refactor_guidance by naming the phase.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 iterate_guidance or setup_guidance. It does not mention any prerequisites, exclusions, or context for choosing this tool over others.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
phase_outputA
Record the output/results when completing a workflow phase - REQUIRES ACTUAL OUTPUT ARTIFACTS with numbered file naming
| Name | Required | Description | Default |
|---|---|---|---|
| phase | Yes | The phase you are completing | |
| output | Yes | The results/findings from this phase | |
| outputArtifacts | Yes | MANDATORY: List of actual output artifacts you created for this phase (use numbered file names) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses a key requirement: 'REQUIRES ACTUAL OUTPUT ARTIFACTS with numbered file naming'. This informs the agent of a critical behavioral constraint. It does not cover other aspects like authentication or side effects, but for a recording tool, the given transparency 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence. It conveys the essential purpose and a critical requirement without extraneous text. Every word serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (nested objects, three required params, no output schema) and the presence of complete schema descriptions, the description covers the core functionality and a key constraint. It is slightly incomplete in explaining the return value, but that is not critical for this tool's use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters. The description adds a minor note about 'numbered file naming' which is also present in the schema. Beyond that, it does not provide additional semantic value, meeting the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Record the output/results when completing a workflow phase'. The verb 'Record' and resource 'output/results' are specific. It distinguishes from sibling tools by focusing on output recording rather than guidance or validation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when completing a workflow phase and emphasizes mandatory output artifacts. However, it does not explicitly state when not to use this tool or mention alternatives like validate_phase_completion. The guidance is present but incomplete.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
present_guidanceA
Get guidance for the PRESENT phase - summarizing work
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only mentions 'get guidance' without explaining what guidance entails, side effects, or permissions. The description adds little beyond the tool name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with necessary information, front-loading 'PRESENT phase'. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given multiple sibling guidance tools and no output schema, the description is minimal. It does not explain what the guidance response contains or how to use it, leaving the agent with insufficient context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters (0), and schema coverage is 100%. Baseline for 0 parameters is 4. The description does not need to add parameter info, but it adds some context about the phase.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Get guidance for the PRESENT phase - summarizing work', specifying the verb (Get guidance) and resource (PRESENT phase). It distinguishes from sibling tools like iterate_guidance or compare_analyze_guidance which target other phases.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Description implies usage for the PRESENT phase but does not explicitly state when to use this tool over alternatives like compare_analyze_guidance or setup_guidance. No exclusions or context are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
question_determine_guidanceC
Get guidance for the QUESTION_DETERMINE phase - clarify and finalize plan
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description gives no behavioral context. It does not state whether the tool is read-only, if it modifies state, or any other side effects. The agent is left guessing about the tool's impact.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the key information. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is too brief given the lack of output schema and annotations. It does not explain what the guidance will contain, how to interpret it, or any additional context needed for an agent to understand the tool's output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With zero parameters, the schema is fully covered. The description adds no parameter details, but that is acceptable since no parameters exist. The purpose is made clear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as providing guidance for a specific phase (QUESTION_DETERMINE) and mentions the goal of clarifying and finalizing the plan. It distinguishes itself from sibling guidance tools by naming a unique phase.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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. It implies use during the QUESTION_DETERMINE phase but does not specify preconditions, when not to use, or mention sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
refactor_guidanceB
Get guidance for the WRITE/REFACTOR phase - implementing changes
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It states 'Get guidance,' implying a read-only, non-destructive operation, but does not disclose any behavioral traits such as side effects, auth needs, or rate limits. The description is insufficient for a full behavioral understanding.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that front-loads the purpose. Every word is necessary, and it is appropriate for a tool with no parameters. No wasted information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, few other tools, and zero parameters, the description is minimally adequate. It tells the agent the phase and action, but lacks details on what the guidance contains or how it is structured. It is complete enough for a simple guidance tool but could be improved with more context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are zero parameters, so the baseline is 4 per instructions. The description adds context that the guidance is for the refactor phase, which provides some meaning beyond the empty schema. However, it doesn't elaborate on any potential inputs, which would be unnecessary given no parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool provides guidance for the WRITE/REFACTOR phase, which is a specific phase. It distinguishes from sibling tools like 'setup_guidance' and 'test_guidance' by naming the phase, but the description does not explicitly contrast with those siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies it should be used during the WRITE/REFACTOR phase but provides no explicit when-to-use or when-not-to-use guidance. No alternatives are mentioned, leaving ambiguity about when to choose this over other guidance tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
refactor_workflowB
Start a structured refactoring workflow to improve existing code without changing functionality
| Name | Required | Description | Default |
|---|---|---|---|
| task | Yes | Description of what you want to refactor | |
| context | No | Additional context (optional) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It correctly states the behavioral constraint of no functionality change, but omits other aspects like whether the workflow is synchronous, requires user input, or has side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence that is concise and front-loaded with the action. All words are necessary and contribute to clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Lacks output schema or description of return value. For a workflow-starter, the agent would benefit from knowing what to expect (e.g., a status or workflow ID). Also no mention of how the workflow progresses.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. However, the description adds no additional meaning beyond the schema; it does not explain how parameters like 'task' or 'context' are used in the workflow.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool starts a refactoring workflow to improve code without changing functionality. It distinguishes from sibling 'refactor_guidance' by specifying it as a workflow, but could be more precise about what starting a workflow entails.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does 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 'refactor_guidance' or 'create_feature_workflow'. The description does not provide context for appropriate use or exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
setup_guidanceA
Get guidance for the SETUP phase - initialize workflow and establish patterns
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It implies a read-only operation ('get guidance') but does not explicitly disclose behavioral traits like side effects or safety. Adequate but minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with purpose. No wasted words, perfectly concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no parameters, no output schema), the description covers the phase and purpose adequately. Could mention expected output type but not necessary for basic guidance.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters in input schema, so parameter semantics are not applicable. Description does not add anything about parameters, but baseline for zero parameters is 4 as no additional value is required.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly specifies the verb 'get guidance' and resource 'SETUP phase'. It distinguishes from sibling guidance tools by naming the phase, though could be more precise about what 'guidance' entails.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides context that it is for the SETUP phase during initialization, but lacks explicit when-to-use or when-not-to-use guidance and does not reference alternatives despite many sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
tdd_workflowC
Start a Test-Driven Development workflow with Red-Green-Refactor cycles
| Name | Required | Description | Default |
|---|---|---|---|
| task | Yes | Description of the feature to develop using TDD | |
| context | No | Additional context (optional) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It only mentions the workflow name without disclosing side effects, required permissions, or whether it modifies files or runs commands.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no redundant words. Efficient and to the point.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With nested objects, no output schema, and no annotations, the description is too sparse. It doesn't explain return values or how the workflow interacts with the environment.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description does not add any parameter-specific meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool initiates a TDD workflow with Red-Green-Refactor cycles, which distinguishes it from sibling tools like 'test_workflow' or 'refactor_workflow'. However, it could be more specific about what 'starting' entails.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does 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 'test_workflow' or 'create_feature_workflow'. The description lacks context about prerequisites or 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.
test_guidanceA
Get MANDATORY guidance for the TEST phase - execute tests and validate functionality after refactoring
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description does not disclose any behavioral traits such as side effects, security requirements, 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with key information, no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no parameters, no output schema), the description adequately conveys its purpose and context, though return format is unspecified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With zero parameters, the baseline is 4. The description adds context about the guidance's purpose, which is meaningful.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool provides mandatory guidance for the TEST phase after refactoring, distinguishing it from sibling tools like test_workflow.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It specifies when to use (test phase after refactoring) but does not explicitly mention alternatives or when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
test_workflowC
Start a focused workflow for writing or improving test coverage
| Name | Required | Description | Default |
|---|---|---|---|
| task | Yes | Description of what to test or test coverage to add | |
| context | No | Additional context (optional) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits such as side effects, required permissions, or whether the workflow is mutable. It only states the action without detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. It efficiently conveys the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the nested input schema and lack of output schema, the description is too brief. It doesn't explain what the workflow does, its output, or any side effects, leaving significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema documents parameters adequately. The tool description adds no extra meaning beyond the schema, resulting in a baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool starts a workflow for writing or improving test coverage, with a specific verb and resource. However, it doesn't differentiate from similar sibling tools like tdd_workflow or test_guidance, preventing a higher score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does 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. The description implies usage for test coverage tasks but lacks explicit context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
user_input_required_guidanceA
Handle escalation to user input when iteration limits reached or checkpoints triggered
| Name | Required | Description | Default |
|---|---|---|---|
| trigger | Yes | What triggered the escalation | |
| context | No | Additional context about the escalation |
TDQS
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 only states the high-level action ('handle escalation') without detailing what happens post-escalation (e.g., tool behavior, side effects, or expected return). This is insufficient for an agent to understand consequences.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with key action and conditions. No redundant or unnecessary words. Efficiently conveys the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 parameters, no output schema), the description is adequate but lacks guidance on what happens after escalation or how the agent should proceed. It covers the trigger conditions but is incomplete for full autonomous use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents the parameters well. The description adds no extra meaning beyond listing trigger conditions. Baseline score of 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Handle escalation', the resource 'user input', and the conditions 'when iteration limits reached or checkpoints triggered'. This is specific and distinct from sibling tools, which are more about general guidance or workflow actions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on when to use this tool (when iteration limits or checkpoints are triggered), but does not explicitly mention when not to use it or suggest alternative tools among the siblings. The usage is implied rather than explicitly bounded.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validate_actionC
Check if an action follows critical safety rules
| Name | Required | Description | Default |
|---|---|---|---|
| action | Yes | The action you want to take | |
| targetFile | Yes | The file you want to act on |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits. It only says 'check', implying a read operation, but does not specify side effects, permissions, or return value. Minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence without fluff. It is concise, though it could benefit from more detail without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description is insufficient. It does not explain what the tool returns (e.g., boolean, error list) or how to interpret results, leaving the agent underinformed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so both parameters are already described. The tool description adds no further semantics beyond the schema, meeting the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool checks if an action follows critical safety rules. It uses a specific verb and resource, but lacks detail on what constitutes 'critical safety rules', making it slightly vague.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does 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 like 'validate_phase_completion'. There is no mention of prerequisites or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validate_phase_completionC
Validate that current phase meets all completion requirements before allowing progression
| Name | Required | Description | Default |
|---|---|---|---|
| phase | Yes | The phase to validate | |
| completedWork | Yes | Description of work completed in this phase | |
| createdFiles | No | List of files created during this phase |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries full burden, but it fails to disclose outcomes of validation (e.g., success/failure, side effects), required permissions, or error handling. The tool's behavior beyond the basic function is opaque.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, clear sentence with no extraneous information. Every word serves a purpose, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema and annotations, the description should explain return values and completion requirements. It does not, leaving agents uncertain about validation logic and expected outputs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3; the description adds no additional meaning for parameters. It does not clarify how 'completedWork' content or 'createdFiles' list affect validation criteria.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool validates phase completion before progression, using a specific verb and resource. It distinguishes from sibling guidance tools, though it does not explicitly contrast with them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use this tool versus alternatives, and does not mention prerequisites or exclusions. Siblings include many guidance and workflow tools, but no comparison is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
workflow_statusA
Check current workflow progress and session state
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must fully disclose behavior. It only says 'check', implying read-only, but does not confirm lack of side effects, authentication needs, or what 'session state' entails.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. It efficiently communicates the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description is minimal. It does not explain what kind of progress information is returned, whether it is synchronous, or how it relates to sibling status-checking tools. For a tool with no parameters, it is somewhat complete but lacks helpful context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, so schema description coverage is 100%. The description does not need to add parameter meaning. The baseline for 0 params is 4, and the description is adequate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('check') and the resource ('current workflow progress and session state'). It distinguishes itself from sibling tools like build_custom_workflow and discover_workflow_tools by focusing on status checking.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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, nor does it mention prerequisites or conditions. It simply states what it does without context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
20 tool updates
- First observed
audit_inventory_guidance - First observed
build_custom_workflow - First observed
compare_analyze_guidance - First observed
create_feature_workflow - First observed
discover_workflow_tools - First observed
iterate_guidance - First observed
lint_guidance - First observed
phase_output - First observed
present_guidance - First observed
question_determine_guidance - First observed
refactor_guidance - First observed
refactor_workflow - First observed
setup_guidance - First observed
tdd_workflow - First observed
test_guidance - First observed
test_workflow - First observed
user_input_required_guidance - First observed
validate_action - First observed
validate_phase_completion - First observed
workflow_status
TDQS
Each tool targets a distinct phase or action, with clear guidance tools for specific workflow stages and separate workflow building tools. There is no overlap in purpose.
Most tools follow a 'verb_noun' or 'phase_guidance' pattern with underscores, but 'phase_output' deviates slightly. Overall, the naming is mostly consistent and predictable.
With 20 tools covering guidance for various phases, workflow stereotypes, validation, and status, the count is well-scoped for a workflow-oriented server.
The tool set comprehensively covers the full workflow lifecycle from setup through completion, including guidance for common phases, multiple workflow types, and validation checks.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Connectors
Deterministic AI code review, with an audit record. Governance inside the agent loop.
Adaptive plan/build/review cycles for AI coding assistants, persisted across sessions.
Verifies AI agent work end to end: real artifacts and outcomes checked, not self-reported success.
Architecture compiler for AI code. 11 tools, 92 actions, 872 Lean4 proofs, 100/100 self-cert.
Related MCP Servers
- AlicenseNot gradedqualityDmaintenanceEnforces engineering governance for AI-driven software projects, ensuring state over prompt, freeze over generate, and audit over output through the 5S workflow.1MIT
- FlicenseNot gradedqualityDmaintenanceEnforces a rigorous spec-driven engineering workflow for AI coding assistants, requiring requirements, design, and task planning before any code is written.-
- AlicenseNot gradedqualityCmaintenanceProtocol-enforced learning system combining memory-augmented reasoning with workflow automation to improve AI assistant reliability by ensuring they learn from past experiences before making code changes.12MIT
- AlicenseNot gradedqualityAmaintenanceEnforces structured, evidence-guided software engineering tasks with cognitive actions (investigate, plan, verify, remember) and persistent state for LLM-based coding agents.1MIT
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/kingdomseed/structured-workflow'
If you have feedback or need assistance with the MCP directory API, please join our Discord server