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Atomic-Germ

Optimist MCP Server

by Atomic-Germ

analyze_dependencies

Analyze project dependency graphs to locate circular dependencies and get actionable update suggestions for cleaner code.

Instructions

Map and analyze dependency graphs

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYesProject root path
checkCircularNoDetect circular dependencies
suggestUpdatesNoSuggest dependency updates

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral transparency. 'Analyze' implies a read-only operation, but the tool does not disclose whether it scans configuration files, whether 'suggestUpdates' has side effects, or what kind of output the agent should expect.

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 extremely concise, front-loaded with the core purpose, and contains no filler or redundancy. The single sentence earns its place, even though it is sparse in broader context.

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?

With no output schema, no annotations, and a very short description, the tool is incomplete from an agent's perspective. The agent does not know what the analysis produces, how results are returned, or what side effects may occur when 'suggestUpdates' is enabled. Given the tool's moderate complexity, more context is needed.

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

Parameters3/5

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

Schema description coverage is 100%, so the parameters are already documented in the input schema. The description adds no additional meaning beyond what the schema already provides, 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.

Purpose5/5

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

The description states a specific action, 'Map and analyze dependency graphs', and the resource ('dependency graphs') clearly distinguishes it from sibling tools focused on performance, memory, complexity, code smells, dead code, hot paths, and refactoring. An agent can infer the tool's purpose without opening the schema.

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

Usage Guidelines2/5

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

There is no guidance on when to choose this tool over alternatives or when not to use it. The description does not mention exclusions, prerequisites, or comparison to shadowing sibling tools like analyze_complexity or detect_code_smells.

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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