AgentStack
Sign in Publish
MCP servers Skills Toolkits Why AgentStack Sell Docs
Sign in
SKILL verified MIT Self-run

Repo Orient

skill-contextosai-skills-repo-orient · by contextosai

Map an unfamiliar software repository from code and configuration. Use when Codex needs to understand a new codebase, locate entry points or ownership boundaries, explain architecture and runtime flow, identify where a change belongs, or prepare for implementation without yet modifying files. Produce an evidence-backed repository map, not a directory listing or README paraphrase.

↗ Repository
— No reviews yet
0 installs
6 views
0.0% view→install

Install

$ agentstack add skill-contextosai-skills-repo-orient

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • ✓ Prompt-injection patterns
  • ✓ Secret / credential exfiltration
  • ✓ Dangerous shell & filesystem operations
  • ✓ Untrusted network calls
  • ✓ Known-malicious package signatures

What it can access

  • ✓ Network access No
  • ✓ Filesystem access No
  • ✓ Shell / process execution No
  • ✓ Environment & secrets No
  • ✓ Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

Are you the author of Repo Orient? Claim this listing to set pricing, connect Stripe payouts, and keep 70% of every sale.
Sign up to claim

About

Repository Orientation

Build the smallest accurate mental model needed for the user's task.

Protocol

  1. Read applicable AGENTS.md files and inspect git status. Treat existing

changes as user work.

  1. Inventory with rg --files, bounded by relevant top-level directories.

Identify manifests, lockfiles, build/test config, deployment config, and generated/vendor boundaries.

  1. Infer the repository shape: application, library, monorepo, service set,

plugin, infrastructure, or hybrid. Verify the inference from manifests.

  1. Trace one real execution path from an external entry point to its terminal

effect. Follow imports/calls, configuration, persistence, and outbound I/O; do not infer architecture from names alone.

  1. Trace the requested concern separately. Locate its definition, runtime

wiring, tests, and operational surface. Search symbols and call sites before reading entire large files.

  1. Identify boundaries that constrain a change: public API, data/schema,

process/service, trust/authorization, transaction, concurrency, and release.

  1. Stop when the model answers the user's question. Do not exhaustively catalog

unrelated modules.

Evidence discipline

  • Cite concrete path:line references for important claims.
  • Distinguish observed facts from inferences. State what would falsify an

inference when uncertainty matters.

  • Treat README and diagrams as orientation leads, then reconcile them with

executable code and configuration.

  • Call out stale, duplicated, dead, generated, or bypassed paths.
  • If multiple entry points differ materially, map each relevant path rather

than inventing one universal flow.

Output

Use references/repository-map.md. Lead with the answer the user needs, then give the execution path, boundaries, change location, and open questions. Skip sections that add no decision value.

Do not edit the repository unless the user also requests a change.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

No reviews yet — be the first.

Write a review

Versions

  • v0.1.0 Imported from the upstream source.

More in AI & ML