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get_overview

Get an architecture map of an unfamiliar repository, including key modules, entry points, git health, and knowledge distribution. Start here when exploring a new codebase.

Instructions

Architecture map for an unfamiliar repo — first call when you don't know your way around.

Returns the synthesised overview plus key modules, entry points, repo-wide
git health (hotspot count, churn trend, bus-factor distribution), the
knowledge map (top owners, knowledge silos), and the community summary.
Skip this on subsequent calls — once you have the map, jump straight to
``get_context`` / ``get_answer``.

Compact by default: ``content_md`` carries only the overview essay's summary
section — the rest of the essay repeats ``key_modules`` / ``entry_points`` /
``architecture.layers``. Pass ``include=["content"]`` for the full essay.

In workspace mode:
- Omit ``repo`` for the default repo's overview plus a workspace footer.
- ``repo="all"`` returns the cross-repo topology (co-changes, package deps,
  API contracts) — no single-repo detail.
- ``repo="<alias>"`` targets one specific repo.

Args:
    repo: Repository alias, path, or ID. Use ``"all"`` for workspace overview.
    include: Opt-in extras. ``"content"`` returns the full overview essay in
        ``content_md`` instead of the compact summary section.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repoNo
includeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Discloses compact default behavior and how to get full essay via include parameter. Explains workspace mode behaviors for different repo values. No annotations are provided, so the description carries the burden and does so well, though it could mention if the tool is idempotent or has side effects (likely none, but not stated).

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?

Well-structured with clear sections, bullet points, and code formatting. Every sentence adds value. Slightly long but appropriate given the detail needed; could be slightly more concise.

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

Completeness5/5

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

Given two parameters and an output schema, the description covers purpose, usage, behavior, parameter details, return contents, and workspace modes. It is sufficiently complete for an AI agent to use correctly.

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

Parameters5/5

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

Schema coverage is 0%, but the description thoroughly explains both parameters: repo can be alias, path, ID, 'all', or omitted for default; include can be 'content' to get full essay. This adds significant meaning beyond the bare 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: 'Architecture map for an unfamiliar repo — first call when you don't know your way around.' It specifies what it returns (overview, modules, entry points, git health, knowledge map, community summary) and explicitly distinguishes from siblings by advising to use get_context/get_answer on subsequent calls.

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?

Provides explicit guidance: 'first call when you don't know your way around' and 'Skip this on subsequent calls — once you have the map, jump straight to get_context / get_answer.' Also describes workspace mode usage with repo parameter options ('all', alias, default).

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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