Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add stark-ai-de/agent-skills --skill repo-map-zoom-outgit clone --depth 1 https://github.com/stark-ai-de/agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/stark-ai-de/agent-skills/repo-map-zoom-out)<a href="https://agentmods.dev/skills/stark-ai-de/agent-skills/repo-map-zoom-out"><img src="https://agentmods.dev/badge/skills/stark-ai-de/agent-skills/repo-map-zoom-out/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/stark-ai-de/agent-skills/repo-map-zoom-out"><img src="https://agentmods.dev/badge/skills/stark-ai-de/agent-skills/repo-map-zoom-out.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00060 | $0.00661 |
| Opus 5 | $0.00030 | $0.00331 |
| Sonnet 5 | $0.00012 | $0.00132 |
| Haiku 4.5 | $0.00006 | $0.00066 |
Grade A, and why
repo-map-zoom-out scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Repo Map Zoom Out
Goal
Build a compact map of an unfamiliar code area so implementation starts with the right boundaries, dependencies, and validation path.
When to use
- The user asks to understand a subsystem, route, package, workflow, or architecture boundary.
- A change looks risky because callers, data flow, or ownership are unclear.
- An agent needs context before editing but should avoid broad file dumping.
When not to use
- The user needs a direct code fix and the relevant files are already known.
- The task is a full repo audit; use
repo-health-audit. - The user wants an ADR; use
adr-writerafter the decision is clear.
Inputs to inspect
- Repo tree, package files, routing files, tests, ADRs, domain docs, and validation docs.
- Existing code search results for entry points, callers, imports, and tests.
- CodeGraph or ast-grep outputs when available, but do not require them.
Workflow
- Define the target area and the question the map must answer.
- Identify entry points, exported APIs, routes, commands, jobs, or event handlers.
- Trace likely callers, callees, imports, data models, and side effects.
- Locate tests, fixtures, validation commands, docs, and relevant ADRs.
- Produce a compact map with likely edit surfaces and risk points.
- Recommend next implementation or investigation steps.
Safety rules
- Do not read broad files just to fill space; prefer targeted search and source ranges.
- Do not treat naming similarity as proof of ownership.
- Do not propose edits until the map identifies the likely affected surface.
- Do not claim complete coverage when only a subset was inspected.
References
No bundled references. If codegraph-ast-grep is available and the repo is indexed, it can help with symbol lookup and structural search. Local ADRs and domain docs should be inspected when relevant.
Scripts
No bundled scripts.
Output format
Return:
- Target question
- Entry points
- Main data or call flow
- Ownership boundaries
- Tests and validation
- Relevant docs or ADRs
- Likely edit surfaces
- Risks and unknowns
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 85 lines · 60 tokens per session scan A 3e4ad498ef15
repo-map-zoom-out is a skill published in the GitHub repository stark-ai-de/agent-skills (5 stars, last pushed 2d ago), licensed Apache-2.0. It adds 60 tokens to every session and 661 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
openlore-brainstorm
Transform a feature idea into an annotated story using a Domain Sketch or Constrained Option Tree. Use when asked to brainstorm, explore, or shape a feature before implementation.
openlore-execute-refactor
Apply a confirmed .openlore/refactor-plan.md with a test gate after each change. Use when asked to execute or continue an OpenLore refactoring plan.
openlore-plan-refactor
Identify a high-priority refactoring target, assess its blast radius, and write .openlore/refactor-plan.md without changing code. Use when asked to plan or prioritize a refactor.
openlore-debug
Debug with OpenLore structural context, an explicit root-cause hypothesis, and RED/GREEN verification. Use when a bug, failure, or regression needs diagnosis and repair.
openlore-implement-story
Implement a brownfield story with OpenLore orientation, risk checks, spec validation, tests, and drift detection. Use when asked to implement or continue a story in an existing codebase.
openlore-write-tests
Write and run real tests for a function or spec scenario after reading implementation and contract evidence. Use when asked to add, improve, or repair tests without stubs or placeholders.