auto-engineer: Skill for Claude Code

.claude/skills/seed/SKILL.md

seed is a skill for Claude Code from dburkart/auto-engineer. It costs 77 tokens per session (5,773 once invoked), scanned A, original, BSD-3-Clause.

A setup tool for adding the auto-engineer software-delivery toolkit to another project. It detects the project’s programming stack and GitHub settings, then writes customised guidance and Docker files into that project.

In plain words
What is it for?
Use it when starting the toolkit in a project, configuring its automated development loop, detecting missing settings, and creating only the needed project files.
Why use it?
It avoids manually copying and adapting setup files while preserving any existing skills with the same names.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter. Also seen: reads .claude/ paths; mentions subagents; names the AskUserQuestion tool.

This is dburkart/auto-engineer's own configuration. It tells Claude Code how to work on auto-engineer itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything auto-engineer configures →

Not installable: its command points at a path on the author’s own machine, so it runs nowhere else. The line is /home/agent/work.

Reuse

Borrowing it

Nothing to install: this file belongs to dburkart/auto-engineer. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/dburkart/auto-engineer/main/.claude/skills/seed/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/dburkart/auto-engineer

Made for: Claude Code.

Wrote 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.

agentmods badge for seed

README.md
[![agentmods](https://agentmods.dev/badge/skills/dburkart/auto-engineer/seed/github.svg)](https://agentmods.dev/skills/dburkart/auto-engineer/seed)
Your own site
<a href="https://agentmods.dev/skills/dburkart/auto-engineer/seed"><img src="https://agentmods.dev/badge/skills/dburkart/auto-engineer/seed/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.

agentmods 80×15 button for seed

Your own site · 80×15
<a href="https://agentmods.dev/skills/dburkart/auto-engineer/seed"><img src="https://agentmods.dev/badge/skills/dburkart/auto-engineer/seed.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 77 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,773 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. ✓ AI security review Sonnet 5 · 7 Sept 2026 📄 Read the review
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00077 $0.05773
Opus 5.5 $0.00031 $0.02309
Sonnet 5.5 $0.00015 $0.01155
Haiku 4.5 $0.00008 $0.00577

Measured 1mo ago against content hash 2bfaf1247b65, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

seed 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 1mo 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.

.claude/skills/seed/SKILL.md · 430 lines

How it starts

The opening of the file, as written. The whole thing — 430 lines — stays where its author put it; the contents beside it link to each section on GitHub.

seed

Configures the auto-engineer toolkit for a target project. Always runs from within this auto-engineer repo — it never copies itself. Reads templates from templates/ (relative to this repo's root), substitutes {{PLACEHOLDER}} values, and writes the results into the target project.

Does not touch any pre-existing .claude/ directory in the target. Skills are written into .claude/skills/ but only for skill names that don't already exist there. settings.local.json and .claude/.gitignore are only created if absent.

When to invoke

  • User says "seed a project", "set up auto-engineer", "configure the loop", or /seed.
  • Accepts an optional positional argument: the path to the target project.
  • If no path is given as an argument, ask for it as the first action (before any detection).

Step 0 — Get the target path

If the user did not provide a path as an argument, ask:

"What's the path to the project you want to seed? (absolute or relative to your home directory)"

Resolve to an absolute path. Verify the directory exists. If it doesn't exist, ask whether to create it. Abort with a clear error if the user declines creation and the path is missing.

All subsequent file reads and writes use <target>/ as the root.


Phase 1 — Detect project state

cd into the target directory for all detection commands. Determine whether this is an existing project (has .git) or a new project (no git history yet).

Existing project detection

Run these in parallel from <target>/:

# GitHub owner/repo
gh repo view --json owner,name --jq '"\(.owner.login)/\(.name)"'

# Current authenticated user (for assignee default)
gh api user --jq .login

# Existing labels
gh label list --json name,description --limit 100

# CI workflows
ls .github/workflows/*.yml 2>/dev/null || true

Also scan for tech stack indicators by checking for file existence in <target>/:

File Stack Default commands
Cargo.toml Rust build: cargo build, test: cargo test, format: cargo fmt --all, lint-fix: cargo clippy --fix --allow-dirty --allow-staged && cargo fmt --all
go.mod Go build: go build ./..., test: go test ./..., format: gofmt -w ., lint-fix: golangci-lint run --fix
package.json Node/TS build: npm run build, test: npm test, format: npm run format, lint-fix: npm run lint --fix
pyproject.toml or setup.py Python build: python -m build, test: pytest, format: ruff format ., lint-fix: ruff check --fix .
Makefile Make-based Read the Makefile for targets: look for build, test, lint, format
None of the above Unknown Will need to prompt user

Read the full file on GitHub · 430 lines

Changes

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.

  1. 1mo ago First seen · 430 lines · 77 tokens per session scan E 2bfaf1247b65

Subscribe to this mod's changes

seed is a skill published in the GitHub repository dburkart/auto-engineer (5 stars, last pushed 6mo ago), licensed BSD-3-Clause. It adds 77 tokens to every session and 5,773 once invoked, about $0.0003 per session on Opus 5.5. 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.

Related

Other skills, from other repositories

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens