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codegraph_shared

Identify shared packages across multiple projects, sorted by dependency count, to reveal common dependencies and potential infrastructure reuse.

Instructions

Packages shared across multiple projects in the code graph.

Returns list of packages with the projects that depend on them, sorted by number of projects (most shared first). Useful for finding common dependencies and potential shared infrastructure.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

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

  1. First observedv0.6.0

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: returns a list, includes dependent projects, and sorts by number of projects (most shared first). It does not describe side effects, but the nature ('Returns') implies a read-only query. Minor gaps like pagination or error handling are not critical for a zero-parameter tool.

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 and front-loaded: it opens with the core purpose ('Packages shared...') and then explains the output and sorting. Every sentence adds value, and there is no filler. It is appropriately sized for a simple tool.

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

Completeness4/5

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 annotations) and the presence of an output schema, the description covers the essential information: what it returns, the ordering, and a use case. It does not explain what constitutes a 'package' or a 'project,' but these are likely defined elsewhere in the code graph context. Overall, it is sufficiently complete for an agent to call it correctly.

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

Parameters4/5

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

There are zero parameters, so the schema coverage is 100% by default. The baseline for zero parameters is 4, and the description offers no parameter details because none exist. This score reflects that there is nothing to explain and the description is not lacking in this area.

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 specific resource ('packages shared across multiple projects') and the action ('Returns list...'). It is distinct from siblings like codegraph_stats or codegraph_query by focusing on shared dependencies across projects. The wording is unambiguous and directly conveys what the tool does.

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

Usage Guidelines4/5

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

The description provides explicit context for when to use the tool: 'Useful for finding common dependencies and potential shared infrastructure.' This gives clear use-case guidance. However, it does not explicitly mention when not to use it or name alternative tools, so it falls short of the highest score for explicit exclusions.

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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