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get_why

Retrieves architectural decisions and evidence commits behind code. Query by question, file path, or get a decision health dashboard. Falls back to git archaeology for undocumented paths.

Instructions

Why this code is shaped this way — decision records + evidence commits.

Call before refactors or pattern divergences. Query modes: a question
("why is auth using JWT?"), a file path (governing decisions + origin
story + alignment score), a question anchored to targets, or no query
(decision health dashboard). Falls back to git archaeology when no
decisions exist for a path — never empty.

Args:
    query: question, file/module path, or omit for the dashboard.
    targets: optional file paths to anchor the search.
    repo: usually omitted.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repoNo
queryNo
targetsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations provided, so description carries full burden. It discloses fallback to git archaeology and that results are never empty, but lacks details on side effects, permissions, or rate limits. Adequate but not comprehensive.

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

Conciseness4/5

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

Description is front-loaded with the core purpose, followed by usage guidelines and parameter details. Slightly lengthy but every sentence adds value. Could be more concise but is well-organized.

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?

Covers query modes, fallback behavior, and parameter usage. Output schema exists but is not described, yet the description gives enough context for an agent to understand what the tool returns (decision records, evidence, alignment score). Fairly complete.

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?

Schema description coverage is 0%, so description must compensate. It explains each parameter's purpose: query (question, path, or omit), targets (optional file paths), repo (usually omitted). Adds significant meaning beyond the schema.

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's purpose: explaining why code is shaped as it is via decision records and evidence commits. It distinguishes from siblings (e.g., get_answer, get_context) by focusing on design decisions and git archaeology.

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?

Explicitly recommends using the tool before refactors or pattern divergences, and describes query modes. It does not explicitly state when not to use, but the context is clear enough for agents to decide.

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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