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coalesce-transform-mcp

coalesce-transform-mcp

Official
by Coalesce-Software-Inc
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TypeScript
Local

Analyze Workspace Patterns

analyze_workspace_patterns
Read-onlyIdempotent

Scans workspace nodes to detect package adoption, pipeline layers, and data modeling methods, then generates actionable recommendations.

Instructions

Analyze workspace node patterns to detect package adoption, pipeline layers, data modeling methodology, and generate recommendations.

This performs a whole-workspace scan (summary-level, all nodes) and returns a compact profile. Use it for profiling/overview tasks, NOT for finding a specific node — for that use search_workspace_content or get_workspace_node. If you want a reusable local snapshot of full node bodies, use cache_workspace_nodes (an explicit full pull).

Args:

  • workspaceID (string, required): The workspace ID to analyze

Returns: Workspace profile with package adoption, pipeline layers, naming conventions, and recommendations.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "workspaceID": "<workspaceID>"
    },
    "name": "analyze_workspace_patterns"
  }
}

Input Schema

NameRequiredDescriptionDefault
workspaceIDYesThe workspace ID to analyze

Output Schema

NameRequiredDescriptionDefault
nodeCountNo
analyzedAtNo
methodologyNo
workspaceIDNo
layerPatternsNo
packageAdoptionNo
recommendationsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.10.1

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so safety is covered. The description adds valuable context: it performs a whole-workspace scan at summary-level and returns a compact profile. There is no contradiction with annotations.

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

Conciseness5/5

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

The description is concise, with a clear opening sentence, a paragraph for usage guidelines, and separated Args/Returns sections. No unnecessary words; every sentence adds value.

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

Completeness5/5

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

Given the tool has only one parameter, rich annotations, and an output schema referenced in the description, the description fully explains the scope (whole-workspace summary scan) and return value (profile with adoption, layers, naming, recommendations). It is complete for its complexity.

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 coverage is 100% (only workspaceID). The description's Args section repeats the parameter without adding extra meaning, format examples, or constraints. Baseline 3 is appropriate since schema already documents the parameter.

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

Purpose5/5

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

The description clearly states the tool analyzes workspace node patterns to detect package adoption, pipeline layers, data modeling methodology, and generate recommendations. It distinguishes itself from siblings like search_workspace_content and get_workspace_node by specifying it is for profiling/overview tasks, not for finding specific nodes.

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

Usage Guidelines5/5

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

The description explicitly states when to use the tool (profiling/overview tasks) and when not to use it (finding a specific node), and provides direct alternatives: search_workspace_content, get_workspace_node, and cache_workspace_nodes. This gives clear guidance.

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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