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archy_graph_focus

Return a focused subgraph of a Python codebase centered on specified modules, with configurable depth and direction. Each node shows instability (Martin's I); each edge shows import line numbers for dependency analysis.

Instructions

Return a subgraph centered on one or more modules. Pass qualnames (e.g. 'archy.parser') or file paths. depth caps hop distance; direction is 'in' (who depends on me), 'out' (my dependencies), or 'both'. Each node carries instability (Martin's I); each edge carries the source line numbers of the import statements. Prefer this over archy_impact when you want forward dependencies, edge-level detail, or a bounded blast radius.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes
modulesYes
depthNo
directionNoboth
internal_onlyNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
rootYes
parse_errorsYes
nodesYes
edgesYes
unresolvedNo
Behavior4/5

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

With no annotations, the description carries the full transparency burden. It describes the returned subgraph's contents (node instability, edge line numbers), parameter effects (depth caps, direction options), and scope (bounded blast radius). It does not explicitly state that the tool is read-only, but the nature of returning a subgraph implies no side effects. A minor gap is the lack of clarity on whether 'path' is the project root or file path for modules.

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 four sentences, each adding unique value: purpose, parameter details, output content, and usage guidance. It is front-loaded with the core action and efficient with no redundant words.

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

Completeness3/5

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

Given the tool has 5 parameters and an output schema exists, the description covers most aspects but lacks explanation for 'internal_only' and could clarify the 'path' parameter. The presence of an output schema reduces the need to detail return structure, but the missing parameter info is a gap.

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 0%, so the description must compensate. It explains 'modules', 'depth', and 'direction' but does not explain 'internal_only' and the distinction between 'path' and 'modules' is ambiguous. With 5 parameters and only 3 partially explained, the description does not fully cover the parameter semantics.

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 'Return a subgraph centered on one or more modules' and specifies how to specify modules via qualnames or file paths. It also distinguishes from sibling tools by noting 'Prefer this over archy_impact when you want forward dependencies, edge-level detail, or a bounded blast radius.'

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 provides a when-to-use comparison: 'Prefer this over archy_impact when you want forward dependencies, edge-level detail, or a bounded blast radius.' This gives clear guidance on when to choose this tool over a specific alternative.

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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