SuperClaude MCP Server
Provides Git operations such as creating checkpoints and managing version control tasks through the SuperClaude toolkit.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@SuperClaude MCP ServerSwitch to architect persona"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
SuperClaude MCP Server
An MCP server that brings all SuperClaude features to Gemini CLI.
Prerequisites
SuperClaude must already be installed in Claude Code
Node.js 18 or higher
Gemini CLI installed
Related MCP server: Gemini MCP Server for Claude Code
Installation
Method 1: Local Installation
# Create project directory
mkdir superclaude-mcp && cd superclaude-mcp
# Copy files (save the code above)
# - superclaude-mcp-server.js
# - package.json
# Install dependencies
npm install
# Grant execution permissions
chmod +x superclaude-mcp-server.jsMethod 2: Global Installation
# Global install
npm install -g .
# Or use npm link
npm linkGemini CLI Configuration
Add the following to your ~/.gemini/settings.json file:
{
"mcpServers": {
"superclaude": {
"command": "node",
"args": ["/path/to/superclaude-mcp-server.js"],
"env": {
"CLAUDE_CONFIG_DIR": "${HOME}/.claude"
}
}
}
}Or configure using npx:
{
"mcpServers": {
"superclaude": {
"command": "npx",
"args": ["-y", "superclaude-gemini-integration-mcp"],
"env": {
"CLAUDE_CONFIG_DIR": "${HOME}/.claude"
}
}
}
}Usage
1. Verify MCP Server
gemini
# In Gemini CLI
/mcp
# Check if superclaude server is listed2. Using SuperClaude Commands
# Build project
gemini "Use sc_build to create a React app with TDD setup"
# Switch persona
gemini "Switch to architect persona using sc_persona"
# Analyze code
gemini "Run sc_analyze on the current codebase with deep analysis"
# Troubleshoot
gemini "Use sc_troubleshoot to debug the API connection issue"
# Create checkpoint
gemini "Create a git checkpoint named 'before-refactor'"3. Using Flags and Options
# Include flags
gemini "Use sc_build with react type and flags --tdd --magic"
# Use with persona
gemini "Use sc_analyze with security persona for vulnerability scanning"
# Evidence-based approach
gemini "Use sc_design with evidence for new authentication system"4. Token Optimization
# Set ultra-compressed mode
gemini "Set token mode to ultracompressed"
# All subsequent responses will be compressed
gemini "Build a complex microservices architecture"Available Tools
Command Tools (sc_*)
sc_build- Build projectssc_dev-setup- Set up development environmentsc_test- Create and run testssc_analyze- Analyze codesc_troubleshoot- Troubleshoot issuessc_improve- Improve codesc_explain- Explain codesc_deploy- Automate deploymentsc_migrate- Handle migrationssc_scan- Security scanningsc_estimate- Project estimationsc_cleanup- Clean up codesc_git- Git operationssc_design- System designsc_spawn- Create specialized agentssc_document- Generate documentationsc_load- Load configurations
Utility Tools
sc_persona- Switch personassc_checkpoint- Manage Git checkpointssc_token_mode- Set token optimization
Personas
Available personas:
architect- System Architectfrontend- Frontend Engineerbackend- Backend Engineersecurity- Security Engineerqa- QA Engineer
Advanced Usage
Using with GEMINI.md
Create a GEMINI.md file in your project root:
# SuperClaude Commands
## Shortcuts
- "sc:build" → Execute sc_build tool
- "sc:analyze" → Execute sc_analyze tool
- "sc:persona [name]" → Switch persona
## Default Persona
Activate architect persona at project start
## Token Mode
Automatically use compressed mode for complex tasksSetting Up Shell Aliases
Add to your .bashrc or .zshrc:
# SuperClaude shortcuts
alias gsc='gemini "Execute SuperClaude command"'
alias gsc-build='gemini "Use sc_build to"'
alias gsc-analyze='gemini "Use sc_analyze on"'
alias gsc-persona='gemini "Switch to persona"'Usage examples:
gsc-build "create a Next.js app with TypeScript"
gsc-analyze "the authentication module"
gsc-persona "security for threat modeling"Troubleshooting
MCP Server Not Visible
Restart Gemini CLI
Check configuration file path
Verify Node.js version (18+)
Commands Not Working
Verify SuperClaude installation:
ls ~/.claudeCheck logs:
gemini --verboseCheck MCP server status:
/mcpcommand
Personas Not Loading
Check persona file:
~/.claude/shared/superclaude-personas.ymlDefault personas will be used
Try manually switching personas
Contributing
Issues and PRs are always welcome!
License
MIT License
Available Tools
20 toolssc_analyzeC
Code analysis - Multi-dimensional analysis of code quality
| Name | Required | Description | Default |
|---|---|---|---|
| args | Yes | Command arguments and flags | |
| flags | No | Command-specific flags | |
| persona | No | Persona to use for this command | |
| evidence | No | Evidence-based methodology data |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. The term 'analysis' hints at a read-only operation but does not explicitly state side effects, output format, or whether any files are modified. It also fails to disclose how flags affect behavior.
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 extremely concise, but it is under-sized for a tool with four parameters and a nested evidence object. It reads like a title rather than a functional guide, sacrificing necessary detail for brevity.
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 output schema, no annotations, and a one-sentence description. The evidence object, flag enums, and persona options are not explained, making it very difficult for an agent to construct a valid or meaningful invocation.
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 describes all four parameters with basic descriptions, so schema coverage is 100%. However, the tool description adds no further meaning to parameters like args, flags, persona, or evidence, leaving their interplay unexplained.
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 states it performs 'multi-dimensional analysis of code quality', which conveys a general purpose but fails to specify what exactly it analyzes or what output it produces. It does not distinguish from sibling tools like sc_scan, leaving ambiguity about its unique role.
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?
There is no guidance on when to use this tool versus alternatives such as sc_scan or sc_improve. No context for prerequisites, intended use cases, or exclusions is provided, leaving the agent to guess.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sc_buildD
Universal project builder - Create any type of project with intelligent defaults
| Name | Required | Description | Default |
|---|---|---|---|
| args | Yes | Command arguments and flags | |
| flags | No | Command-specific flags | |
| persona | No | Persona to use for this command | |
| evidence | No | Evidence-based methodology data |
TDQS
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, but it fails to convey what happens during the build, potential side effects, required permissions, or output. The only hint is 'intelligent defaults,' which is vague and does not explain actual behavior.
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 only one sentence, but it is a vague tagline rather than a functional specification. It is under-specified, not concise in a helpful way—it lacks the details necessary for an agent to understand the 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?
With 4 parameters (including nested objects and enums), no output schema, and no annotations, the description is far too minimal to provide complete context. It fails to explain return values, side effects, or how to use the parameters, making it inadequate for safe invocation.
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 provides descriptions for all parameters, resulting in 100% coverage, so the baseline is 3. The description adds no parameter-level meaning beyond what the schema already states, but it does not need to because the schema is self-sufficient.
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 says 'Create any type of project' but the tool name suggests a build operation, creating a mismatch. 'Universal project builder' is virtually a tautology of the name, and there is no specific verb+resource scope that distinguishes it from siblings like sc_spawn or sc_dev-setup.
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 sc_build versus alternatives. The phrase 'universal project builder' implies broad applicability but gives no context about when it should be chosen over sibling tools (e.g., sc_spawn for creation or sc_dev-setup for setup).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sc_checkpointC
Create or restore git checkpoint
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | Checkpoint name | |
| action | Yes | Checkpoint action |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden but only says 'create or restore' without disclosing effects like potential overwriting on restore, saved state scope, or side effects. The missing 'list' action also creates ambiguity about available behaviors.
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 concise sentence with the action front-loaded. It is efficient but under-specified by omitting the 'list' enum value from the schema, making it not fully complete.
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 three distinct actions (create, restore, list) but the description only mentions two. No output schema, no annotations, and no behavioral details make this incomplete for an agent to use reliably.
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 covers 100% of parameters with descriptions (name and action), so baseline is 3. The description adds 'git checkpoint' context but does not elaborate how name and action interact 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?
Description uses specific verb 'Create or restore' and resource 'git checkpoint', clearly indicating it manages git checkpoints. However, it omits the 'list' action available in the schema, so it's not fully accurate but still clear.
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 sc_checkpoint versus sibling tools like sc_git. No prerequisites, alternatives, or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sc_cleanupC
Code cleanup - Remove technical debt
| Name | Required | Description | Default |
|---|---|---|---|
| args | Yes | Command arguments and flags | |
| flags | No | Command-specific flags | |
| persona | No | Persona to use for this command | |
| evidence | No | Evidence-based methodology data |
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 itself. 'Remove technical debt' implies modifying code, but the description does not state whether files are edited, whether changes are reversible, or what side effects the cleanup may have.
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 very short and front-loaded, consisting of just a label and a brief outcome phrase. It is not verbose, though it is slightly under-specified rather than optimally 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?
With no output schema, no annotations, and four parameters including a nested evidence object, the one-line description is insufficient for an agent to understand invocation context, return values, or side effects. It lacks essential operational details beyond the schema.
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 describes all four parameters (args, flags, persona, evidence) with coverage at 100%. The description adds no extra parameter semantics beyond what the schema already provides, so the baseline score applies.
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 performing code cleanup and removing technical debt, which names both the action and the target resource. However, it does not differentiate from sibling tools like sc_improve or sc_analyze, so it stops short of 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.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool instead of alternatives. It does not mention any exclusions, prerequisites, or scenarios where sc_cleanup is preferred over related tools such as sc_improve or sc_analyze.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sc_deployD
Deployment automation - Handle deployment workflows
| Name | Required | Description | Default |
|---|---|---|---|
| args | Yes | Command arguments and flags | |
| flags | No | Command-specific flags | |
| persona | No | Persona to use for this command | |
| evidence | No | Evidence-based methodology data |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full responsibility for disclosing behavioral traits such as side effects, permission requirements, or environment impact. It only mentions 'automation' and 'workflows' with no details about production changes, irreversible actions, or potential risks.
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 extremely short, but this is under-specification rather than effective conciseness. The phrase 'Deployment automation - Handle deployment workflows' provides no actionable information and fails to earn its place by adding value beyond the tool name.
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 (4 parameters, nested evidence object, no output schema), the description is woefully incomplete. It does not explain what the tool returns, what workflow it executes, or any edge cases, making it inadequate for guiding an agent.
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 describes all four parameters (args, flags, persona, evidence) with 100% coverage, so the schema already conveys most parameter meaning. The description adds no additional parameter context, keeping this at the baseline score.
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 'Deployment automation - Handle deployment workflows' essentially restates the tool name (sc_deploy) with generic phrasing. It lacks a concrete verb like 'deploy', 'rollback', or 'validate' and does not clarify a specific resource or action, making it hard to distinguish from sibling tools such as sc_build or sc_migrate.
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. There is no mention of scenarios like releasing to staging, production rollbacks, or validation steps, leaving the agent without context for correct selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sc_designD
System design - Architecture and design patterns
| Name | Required | Description | Default |
|---|---|---|---|
| args | Yes | Command arguments and flags | |
| flags | No | Command-specific flags | |
| persona | No | Persona to use for this command | |
| evidence | No | Evidence-based methodology data |
TDQS
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 does not state whether the tool is read-only, what it returns (e.g., a design document, recommendations, diagrams), whether it modifies anything, or any side effects. The description is a topic tag, not a behavioral specification.
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 short phrase, but this is under-specification, not effective conciseness. It lacks a full sentence and provides no structural information. Every word is generic ('system design', 'architecture', 'design patterns') and could apply to many tools.
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 4 parameters, a nested 'evidence' object, no output schema, no annotations, and 20 sibling tools. A single label cannot possibly provide the necessary context for an agent to select and invoke this tool correctly. It is completely inadequate for the complexity.
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 baseline is 3. The tool description adds a bit of context by referencing 'architecture and design patterns', which aligns with the flags --architecture and --patterns. However, it does not explain how to fill the required 'args' string or how the 'evidence' object should be structured, so it does not meaningfully enrich 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 'System design - Architecture and design patterns' is a label rather than a clear action. It lacks a verb (e.g., 'generate', 'analyze', 'document') and does not specify what the tool does with system design. It barely distinguishes from siblings like sc_document or sc_analyze, which could also involve design-related output.
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 given on when to use sc_design versus the many sibling tools (e.g., sc_analyze, sc_explain, sc_document). There is no mention of prerequisites, typical usage scenarios, or exclusions. The description is entirely silent on context and alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sc_dev-setupC
Development environment setup - Configure complete dev environment
| Name | Required | Description | Default |
|---|---|---|---|
| args | Yes | Command arguments and flags | |
| flags | No | Command-specific flags | |
| persona | No | Persona to use for this command | |
| evidence | No | Evidence-based methodology data |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must disclose behavioral traits. It implies a configuration action that may modify the system, but it does not state side effects, required permissions, or reversibility. This is a significant transparency gap for a setup tool.
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 short and front-loaded, but it is slightly redundant: 'Development environment setup' and 'Configure complete dev environment' essentially restate the same idea. It earns a middle score because it is not verbose but also not maximally efficient in message.
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 complexity (4 parameters, enums, nested objects) and lack of output schema or annotations, the description is far too minimal. It does not explain what the flags mean, how personas affect behavior, or what the 'evidence' object is for, making it incomplete for effective selection and invocation.
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 baseline is 3. The description itself does not add any parameter insights, and the schema descriptions are generic (e.g., 'Command-specific flags', 'Persona to use for this command'), so no extra meaning is provided 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 states a clear action ('Configure') and resource ('complete dev environment'), which distinguishes it from sibling tools like sc_build or sc_test. However, 'complete dev environment' is somewhat vague and could mean many things, 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.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives. The description does not mention any context, prerequisites, or exclusions, leaving the agent to infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sc_documentC
Documentation generation - Create comprehensive docs
| Name | Required | Description | Default |
|---|---|---|---|
| args | Yes | Command arguments and flags | |
| flags | No | Command-specific flags | |
| persona | No | Persona to use for this command | |
| evidence | No | Evidence-based methodology data |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only states a high-level outcome ('Create comprehensive docs') and does not explain whether existing files are overwritten, whether it analyzes source code, what the command arguments do, or how the persona affects output. The schema descriptions for parameters are generic and do not fill the gap.
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 only 6 words, which is under-specification for a tool with 4 parameters, enum flags, a persona selector, and nested evidence objects. It repeats the title's concept ('Documentation generation' vs 'Create comprehensive docs') and omits necessary structural details. This is not effective conciseness but rather a lack of informative content.
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 a relatively rich schema (multiple enum flags, persona, nested evidence) and no output schema, yet the description provides no context about how these elements interact, what the generated docs look like, or what 'comprehensive' means in practice. Without annotations or output schema, the description fails to give a complete picture for an AI agent to select and invoke the tool correctly.
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 four parameters. The description itself adds no parameter-specific meaning (it doesn't mention args, flags, persona, or evidence). Per the calibration, with high schema coverage the baseline is 3, and this description neither improves nor worsens the semantic understanding 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 tool's purpose: 'Documentation generation - Create comprehensive docs'. It uses a specific verb 'Create' and resource 'docs', which is distinct from the sibling tools like sc_build or sc_test. However, it does not specify the types of documentation (API, user, technical, readme) that are suggested by the flags enum, nor does it distinguish itself from other potential doc-related tools.
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 gives no guidance on when to use this tool versus the many siblings (sc_analyze, sc_explain, etc.). It does not mention any prerequisites, context, or scenarios where documentation generation would be appropriate. The phrase 'Create comprehensive docs' implies the purpose but does not provide situational advice or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sc_estimateC
Project estimation - Time and resource estimates
| Name | Required | Description | Default |
|---|---|---|---|
| args | Yes | Command arguments and flags | |
| flags | No | Command-specific flags | |
| persona | No | Persona to use for this command | |
| evidence | No | Evidence-based methodology data |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full responsibility for disclosing behavior. It only states that the tool provides time and resource estimates, but does not mention whether it is read-only, what inputs are required, what outputs are produced, or any side effects. This is insufficient for an agent to predict tool behavior.
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 extremely concise with two short phrases, but it borders on under-specification. It is not wordy, yet it provides only minimal information about the tool's purpose, making it less useful than a well-structured one-sentence description.
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 complexity (4 parameters, nested evidence object, no annotations, no output schema), the description is seriously incomplete. It fails to explain what inputs are needed, what outputs to expect, or how to effectively invoke the tool, leaving the agent without sufficient 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 description itself adds no parameter details, but the input schema already provides descriptions for all four parameters (100% coverage), including the nested evidence object. Since the schema carries the parameter semantics, the description's lack of param info is acceptable, though it does not enhance understanding.
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 being for 'Project estimation' focused on 'Time and resource estimates', which distinguishes it from siblings like sc_build or sc_test. However, it lacks a specific verb and could be more explicit about what the tool does (e.g., 'Estimate project time and resources').
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 alternatives. The description is purely a label and offers no context for selecting it among the many sibling tools, nor does it exclude any cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sc_explainC
Code explanation - Detailed documentation and understanding
| Name | Required | Description | Default |
|---|---|---|---|
| args | Yes | Command arguments and flags | |
| flags | No | Command-specific flags | |
| persona | No | Persona to use for this command | |
| evidence | No | Evidence-based methodology data |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full burden of behavioral disclosure. It only says 'Code explanation - Detailed documentation and understanding' and does not state whether the operation is read-only, what it returns, or any side effects. This is a complete lack of behavioral 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 extremely brief, but this is under-specification rather than effective conciseness. The single sentence conveys little meaningful information and does not earn 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 tool has 4 parameters including nested objects, no output schema, and no annotations. The description fails to explain the tool's purpose, usage, or behavior, making it completely inadequate for an agent to select and invoke correctly.
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 covers 100% of parameters, so the baseline is 3. The description adds no parameter meaning beyond what the schema already provides, and the schema descriptions themselves are reasonably 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 states 'Code explanation - Detailed documentation and understanding', which indicates the tool explains code, but it is vague and does not differentiate from sibling tools like sc_document or sc_analyze. The verb 'explain' is present, but the resource and scope are unclear.
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 usage guidance is provided. The description gives no indication of when to use sc_explain versus alternatives such as sc_analyze or sc_document, nor does it mention any prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sc_gitD
Git operations - Advanced git workflows
| Name | Required | Description | Default |
|---|---|---|---|
| args | Yes | Command arguments and flags | |
| flags | No | Command-specific flags | |
| persona | No | Persona to use for this command | |
| evidence | No | Evidence-based methodology data |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full responsibility for behavioral disclosure, but it only names the domain. It omits side effects, permissions, return formats, or operational impact, leaving the agent completely uninformed about what invoking this tool 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 extremely short, but it is under-specified rather than concisely informative. It lacks actionable detail and provides only a vague phrase that does not justify its brevity.
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 4 parameters including nested objects and no output schema, indicating potential complexity. Yet the description is a single vague phrase with no explanation of how to form git arguments, what flags do, how evidence is used, or what output to expect. This is completely inadequate.
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 baseline is 3. The tool description adds no parameter meaning; the schema's own parameter descriptions are generic (e.g., 'Command arguments and flags'), and the description does not clarify how to use them in practice.
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 'Git operations - Advanced git workflows' only restates the tool name at a categorical level without specifying a concrete action or resource. It does not indicate which particular git operations are supported or how it differs from other workflow tools.
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 usage context is provided. The description neither explains when to use sc_git over sibling tools nor mentions any prerequisites, exclusions, or alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sc_improveD
Code improvement - Enhance existing code
| Name | Required | Description | Default |
|---|---|---|---|
| args | Yes | Command arguments and flags | |
| flags | No | Command-specific flags | |
| persona | No | Persona to use for this command | |
| evidence | No | Evidence-based methodology data |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only states 'enhance existing code' without mentioning whether the tool modifies files, requires permissions, or has side effects. The flags (--refactor, --clean) imply mutation, but the description does not disclose this behavior.
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 extremely short, but this is under-specification rather than conciseness. It contains no structured information, front-loaded key facts, or elaboration on the flags and parameters. The brevity fails to serve the agent's needs.
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 complex inputs (flags, persona, evidence object), no output schema, and no annotations. The description provides no context about the command's purpose, expected inputs, or behavioral outcomes. It is completely inadequate for an agent to invoke correctly.
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% since each parameter has a description. The tool description adds no parameter-level semantics, so the baseline score of 3 applies. The schema itself provides adequate parameter documentation, though the description does not reinforce or clarify it.
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 phrase 'Code improvement - Enhance existing code' indicates a broad purpose of improving code, but it lacks specificity about what kinds of improvements are offered or what resource is affected. It is somewhat more than a tautology because it rephrases 'improve' as 'enhance', but it does not clearly distinguish from sibling tools like sc_analyze or sc_cleanup.
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 alternative sibling tools. It does not mention any context, prerequisites, or exclusions, leaving the agent without any basis for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sc_loadC
Load configurations - Apply saved configurations
| Name | Required | Description | Default |
|---|---|---|---|
| args | Yes | Command arguments and flags | |
| flags | No | Command-specific flags | |
| persona | No | Persona to use for this command | |
| evidence | No | Evidence-based methodology data |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are available, so the description carries full responsibility for behavioral disclosure. It only says 'Apply saved configurations', implying a mutating action, but doesn't disclose side effects, whether it overwrites existing configs, or what system state changes. This is 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 very short, a fragment of two phrases. It avoids verbosity, but it is under-specified rather than efficiently concise. The brevity leaves key details unresolved, so it doesn't earn its place as fully helpful.
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 4 parameters, no output schema, and no annotations, the description is incomplete. It fails to explain what 'configurations' are, how they are loaded, or how flags and persona affect behavior. A single-line description is insufficient for a tool of this complexity.
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%, with each parameter (args, flags, persona, evidence) having a description. The tool description adds no additional parameter semantics, so it relies on the schema. Baseline 3 applies.
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 'Load configurations - Apply saved configurations' indicates the tool loads/applies saved configs, and the verb 'load' aligns with the tool name. However, it is vague about what configurations are, the context, and how it differs from sibling tools like sc_persona or sc_build.
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 usage guidance is provided. The description does not state when to use this tool, mention prerequisites, or reference alternative sibling tools. Agents have no help deciding between sc_load and other tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sc_migrateD
Migration assistance - Database and code migrations
| Name | Required | Description | Default |
|---|---|---|---|
| args | Yes | Command arguments and flags | |
| flags | No | Command-specific flags | |
| persona | No | Persona to use for this command | |
| evidence | No | Evidence-based methodology data |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It does not mention that flags like --plan, --execute, --rollback, or --validate control migration phases, any side effects (e.g., schema changes), or the need for evidence/persona.
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 concise (one short phrase), but this brevity is under-specification, not efficient structure. It omits all operational detail and fails to leverage the available flag semantics.
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?
Despite having 4 parameters, nested objects, and a rich set of migration flags, the description provides only a vague scope. No output format, migration workflow, or relationship to code/database changes is explained. Sibling tools imply a CLI context, but this description is far from 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 schema fully describes all four parameters (args, flags, persona, evidence), and the description adds no parameter meaning beyond the schema. Baseline 3 is appropriate because the schema is comprehensive.
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's domain ('Database and code migrations') and uses 'Migration assistance' to imply a helping role. However, it lacks a specific verb like 'plan', 'execute', or 'manage', and does not differentiate from siblings beyond the migration topic.
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?
There is no guidance on when to use this tool versus other siblings like sc_build or sc_deploy. No context, prerequisites, or exclusions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sc_personaB
Switch active SuperClaude persona
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Persona name to activate |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full responsibility for disclosing behavioral traits. It states the action but does not explain what 'switch active persona' entails (e.g., persistence, effect on subsequent tool calls, reversibility). This is a significant gap for a state-changing tool.
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 filler. It is front-loaded and every word contributes to the meaning.
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 is simple (one enum parameter, no output schema), but as a state-changing operation it lacks key context such as return behavior or effect on the broader SuperClaude environment. The description is minimal but not severely deficient given the tool's simplicity.
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% with a clear enum description, so the baseline is 3. The tool description adds no additional meaning beyond the schema, but the schema fully documents the parameter, making this 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 uses a specific verb ('switch') and clearly identifies the resource ('active SuperClaude persona'). It distinguishes itself from all sibling tools, none of which mention persona management, making the purpose unambiguous.
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 alternatives or when switching personas is appropriate. The description only states the action without contextual direction, leaving the agent to infer usage from the schema enum values.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sc_scanC
Security scanning - Comprehensive security analysis
| Name | Required | Description | Default |
|---|---|---|---|
| args | Yes | Command arguments and flags | |
| flags | No | Command-specific flags | |
| persona | No | Persona to use for this command | |
| evidence | No | Evidence-based methodology data |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It only offers a vague 'comprehensive security analysis' without details on what is scanned, side effects, permissions, or output format. This provides minimal insight into actual tool behavior.
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 very concise, consisting of a single phrase with no wasted words. However, 'Security scanning' and 'Comprehensive security analysis' are somewhat redundant, yet the structure is front-loaded and appropriately sized for a high-level overview.
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?
This is a complex tool with four parameters, including a nested evidence object, and no output schema. The description provides no context about what the scanning entails, how to use flags or args, or what the tool returns, making it incomplete for effective invocation.
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 four parameters. The tool description adds no parameter-specific meaning, so the 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 'Security scanning - Comprehensive security analysis' clearly identifies the tool's core function (security scanning) and suggests broad coverage. It distinguishes from siblings like sc_analyze by specifying security, though it lacks explicit scope such as code, dependencies, or secrets.
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 given on when to use sc_scan versus other sibling tools like sc_analyze or sc_test. The description does not mention prerequisites, context, or exclusions, leaving the agent without direction on tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sc_spawnC
Create specialized agents - Spawn task-specific AI agents
| Name | Required | Description | Default |
|---|---|---|---|
| args | Yes | Command arguments and flags | |
| flags | No | Command-specific flags | |
| persona | No | Persona to use for this command | |
| evidence | No | Evidence-based methodology data |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits, but it only says 'create specialized agents' with no detail on side effects, permissions, reversibility, or operational behavior. The mutation implied by 'create' is stated, but nothing else is disclosed.
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 short but redundant: 'Create specialized agents' and 'Spawn task-specific AI agents' say essentially the same thing. It is not verbose, but a single concise sentence would be more effective without 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 has 4 parameters including a nested evidence object, no output schema, and no annotations, the description is minimal. It fails to explain how the flags/persona relate to spawning or what the expected outcome/return is. A more descriptive overview is needed for effective invocation.
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%: args, flags, persona, and evidence all have descriptions and enums. The description adds no parameter-level meaning, but the schema already provides sufficient semantics, meeting the baseline for full coverage.
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 states the tool creates/spawns task-specific AI agents, which is a clear verb-resource pair. It distinguishes from sibling tools that perform actions like build, test, or analyze, though it doesn't explicitly contrast with them. The wording is slightly redundant but the purpose is evident.
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 usage context is provided. The description does not say when to use this tool versus alternatives, nor does it mention any prerequisites or exclusions. An agent is left without guidance on selecting sc_spawn over other sc_* commands.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sc_testC
Testing framework - Create and run tests with coverage
| Name | Required | Description | Default |
|---|---|---|---|
| args | Yes | Command arguments and flags | |
| flags | No | Command-specific flags | |
| persona | No | Persona to use for this command | |
| evidence | No | Evidence-based methodology data |
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, file modifications, or required permissions. 'Create and run tests' is ambiguous about whether it creates test files or just executes a test suite, offering no 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 very short and free of fluff, but it is under-specified for a tool with 4 parameters, enums, and nested objects. It is front-loaded but lacks necessary detail to earn a higher score.
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 no annotations, no output schema, and a complex parameter set, the description is far from complete. It provides no context about expected inputs, outputs, or side effects, making it inadequate for a tool of this complexity.
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 all parameter descriptions exist in the schema. The tool description adds no additional parameter meaning beyond the schema, thus a 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-resource pair 'Create and run tests' and mentions coverage, which conveys the primary purpose. However, it does not differentiate from siblings beyond the obvious testing context, and the phrase 'Testing framework' is a noun phrase that adds little clarity.
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 sc_build or sc_analyze. No context, exclusions, or alternative suggestions are given, leaving the agent to infer usage solely from the name and short phrase.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sc_token_modeC
Set token optimization mode
| Name | Required | Description | Default |
|---|---|---|---|
| mode | Yes | Token optimization level |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only restates the tool's function without explaining side effects, persistence, reversibility, or impact on subsequent operations. This is a significant gap for a state-changing tool.
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 with no unnecessary padding. It is front-loaded and directly conveys the tool's purpose, which is appropriate for such 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?
While the schema covers parameter values, the description lacks any context about what the modes do, when to use them, or what happens after setting a mode. Without annotations or an output schema, this minimal description leaves the agent without enough information to make an informed invocation.
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 fully describes the single parameter 'mode' with an enum and a clear description ('Token optimization level'), so schema coverage is 100%. The tool description adds no additional semantic information beyond what the schema already provides, warranting the 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 action ('Set') and the target ('token optimization mode'), making the primary purpose unambiguous. However, it does not distinguish this tool from siblings like sc_analyze or sc_improve, though the verb+resource is specific enough.
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, and no prerequisites or exclusions are mentioned. The agent must infer usage solely from the tool's name and the action described.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sc_troubleshootC
Intelligent debugging - Systematic issue resolution
| Name | Required | Description | Default |
|---|---|---|---|
| args | Yes | Command arguments and flags | |
| flags | No | Command-specific flags | |
| persona | No | Persona to use for this command | |
| evidence | No | Evidence-based methodology data |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose side effects, permissions, or whether the tool modifies anything. The phrase 'intelligent debugging' hints at analysis but lacks concrete behavioral 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 short tagline rather than a functional description. While brief, it under-specifies the tool's purpose and usage, which is not true conciseness.
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 4 parameters, including a nested evidence object, and no output schema. The two-word description fails to explain what the tool does, what it returns, or how the parameters relate to troubleshooting, leaving it largely incomplete.
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 baseline is 3. However, the tool description itself adds no parameter meaning, and the schema descriptions are generic (e.g., 'Command arguments and flags'), yet they provide some minimal context.
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 'Intelligent debugging - Systematic issue resolution' is vague and fails to specify a concrete action or resource. It does not distinguish from siblings like sc_analyze or sc_explain, making it unclear what this tool uniquely does.
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?
There is no guidance on when to use this tool versus alternatives. The description offers no context, prerequisites, or exclusions, leaving the agent to guess.
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
v1.0.1- First observed
sc_analyze - First observed
sc_build - First observed
sc_checkpoint - First observed
sc_cleanup - First observed
sc_deploy - First observed
sc_design - First observed
sc_dev-setup - First observed
sc_document - First observed
sc_estimate - First observed
sc_explain - First observed
sc_git - First observed
sc_improve - First observed
sc_load - First observed
sc_migrate - First observed
sc_persona - First observed
sc_scan - First observed
sc_spawn - First observed
sc_test - First observed
sc_token_mode - First observed
sc_troubleshoot
TDQS
Most tools have clear, distinct purposes, but there is some overlap between sc_analyze, sc_improve, sc_cleanup, and sc_troubleshoot, which all deal with code modification. However, their descriptions specify different focuses (analysis, enhancement, cleanup, debugging), so an agent can usually select the right one.
All tools consistently use the sc_ prefix with lowercase hyphenated names (e.g., sc_dev-setup, sc_analyze). This uniform pattern makes the tool naming highly predictable and easy to navigate.
With 20 tools, the set is slightly above the ideal 3-15 range, but each tool serves a distinct development function, from building to deployment. The count feels comprehensive rather than bloated for an all-in-one development assistant.
The tool surface covers the entire development lifecycle—project creation, setup, testing, analysis, debugging, improvement, deployment, migration, security, estimation, documentation, and git operations. There are no obvious gaps that would force an agent into a dead end for common workflows.
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