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MUSE-CODE-SPACE

Vibe Coding Documentation MCP (MUSE)

muse_auto_tag

Automatically suggests and applies tags to coding sessions, analyzes content and code blocks, and learns from examples to improve tagging accuracy.

Instructions

Automatically suggests and applies tags to sessions. Actions: suggest (recommend tags), apply (add tags to session), train (learn from examples), config (configure tagging behavior).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYesAction to perform
sessionIdNoSession ID to analyze or update (for suggest/apply)
contentNoText content to analyze for tags
codeBlocksNoCode blocks to analyze
maxTagsNoMaximum number of tags to suggest (default: 5)
minConfidenceNoMinimum confidence threshold 0-1 (default: 0.7)
includeExistingNoInclude existing tags when applying (default: true)
categoriesNoFilter suggestions by category
examplesNoTraining examples for train action
enableAutoTagNoEnable/disable auto-tagging (for config)
defaultCategoriesNoDefault categories to use (for config)
customPatternsNoCustom patterns for tag detection (for config)
useAINoUse AI for tag suggestions (default: false)
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. While it lists four actions, it doesn't describe what each action actually does beyond their names, doesn't mention permissions required, doesn't indicate whether operations are destructive (e.g., does 'apply' overwrite existing tags?), and provides no information about rate limits, error conditions, or response formats. The description is insufficient for a tool with 13 parameters and multiple operational modes.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately concise - a single sentence stating the purpose followed by a parenthetical list of actions. Every element serves a purpose with no wasted words. However, the structure could be improved by front-loading more critical information about the tool's primary use cases rather than burying action details in parentheses.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex tool with 13 parameters, 4 distinct actions, no annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns, how different actions interact, what 'training' actually entails, or how configuration affects behavior. The agent would struggle to use this tool effectively without trial-and-error, especially given the multiple operational modes and numerous parameters.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds minimal value beyond what's in the schema - it mentions the four action types but doesn't provide additional context about parameter usage, dependencies between parameters, or which parameters are relevant for which actions. The baseline score of 3 reflects adequate schema coverage with minimal description enhancement.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Automatically suggests and applies tags to sessions' with specific actions listed. It distinguishes itself from siblings by focusing on tagging operations rather than analysis, summarization, or session management. However, it doesn't explicitly contrast with specific sibling tools like 'muse_session_stats' or 'muse_analyze_code'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage through the action list (suggest, apply, train, config), suggesting different scenarios for each action. However, it doesn't provide explicit guidance on when to choose this tool over alternatives like 'muse_session_stats' for session metadata or 'muse_analyze_code' for code analysis. No 'when-not-to-use' guidance or prerequisite information is included.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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