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dependency_tree

Read-onlyIdempotent

Show the dependency tree for a Python project to reveal package relationships and hierarchy. Optionally limit depth or target a specific project directory.

Instructions

Display the project's dependency tree.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
depthNoOptional maximum tree depth.
project_pathNoOptional project working directory.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds the core behavior ('display') but does not go beyond that. It does not mention output format, how the tree is computed, or any potential side effects, though for a read-only tool this is acceptable. With annotations present, the description offers minimal additional behavioral context.

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 a single, concise sentence that immediately states the purpose. There is no filler or redundant information. Every word earns its place, making it an excellent example of concise writing.

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?

The tool is simple, has a fully described input schema, annotations for safety, and an output schema (not shown but referenced in context). The description is sufficient for a basic display tool, though it could optionally mention that it operates on the current project directory or respects lockfiles. Given the structured metadata, the description is complete enough for an AI agent to use the tool correctly.

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%: both 'depth' and 'project_path' have descriptions in the schema. The description itself does not add parameter-specific meaning, but it is not required given the schema's completeness. This matches the baseline for high schema coverage.

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 'Display the project's dependency tree' uses a specific verb ('Display') and a clear resource ('dependency tree'), making the tool's purpose immediately understandable. It also distinguishes itself from sibling tools like pip_list or pip_freeze, which focus on packages rather than the dependency tree structure.

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?

The description provides no guidance on when to use this tool versus alternatives. There is no mention of scenarios, exclusions, or related tools such as pip_list or pip_freeze. For example, a user might benefit from knowing whether this is the right choice for inspecting installed dependencies versus the project's declared dependency tree.

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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