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SKILL verified MIT Self-run

Project Context Bootstrap

skill-markoblogo-abvx-agent-skills-project-context-bootstrap · by markoblogo

Bootstrap usable project context before deep implementation work. Use when entering a new or unfamiliar repo, installing agent workflows into an existing codebase, auditing stale docs, or preparing a project for repeatable long-running agent work. Detect the stack, ask the user about the project, summarize understanding, propose compact context artifacts, and update only with approval.

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Install

$ agentstack add skill-markoblogo-abvx-agent-skills-project-context-bootstrap

✓ 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.

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About

Project Context Bootstrap

Create a compact, durable working model of a repo before the agent starts inventing one from guesswork.

Goal

Turn a repo with weak or missing agent-facing context into a repo with:

  • a clear stack and structure summary;
  • known commands and verification paths;
  • durable context files or notes with real content;
  • explicit approval before reorganizing existing docs.

Workflow

  1. Detect
  • inspect project manifests, lockfiles, workspace layout, test commands, and major directories;
  • detect whether context already exists: AGENTS.md, docs/ai/, runbooks, plans, or other agent-facing docs.
  1. Study existing context first
  • if the repo already has useful docs, read them before proposing replacements;
  • separate what looks good, stale, missing, or conflicting.
  1. Ask
  • have a real project-discovery conversation with the user;
  • cover what the product is, who uses it, main features, risky areas, workflow conventions, and external dependencies;
  • follow up until the project is actually understandable.
  1. Summarize
  • restate your understanding in concise project language;
  • confirm accuracy before writing or reorganizing context.
  1. Propose
  • suggest the smallest useful context structure:
  • top-level AGENTS.md or compact startup doc;
  • docs/ai/architecture.md;
  • docs/ai/how-to-test.md;
  • task-specific notes only if needed;
  • ask before reorganizing or overwriting anything durable.
  1. Populate
  • write real content from code and user input, not placeholders;
  • include concrete commands, file paths, key modules, and current conventions.
  1. Validate
  • verify the new context is small, accurate, and actually useful for the next session.

Existing Repo Rules

  • Preserve good context; do not replace it with generic scans.
  • Show what you want to keep, improve, and add before changing layout.
  • Never silently move or delete user-written docs.

Compression Rules

  • Keep startup context compact.
  • Put deeper material behind explicit paths.
  • Prefer one good entrypoint per topic instead of many tiny fragmented notes.

Final Report

Include what was detected, what was confirmed by the user, what context was added or updated, and what should be read first in the next session.

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.

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Versions

  • v0.1.0 Imported from the upstream source.