setup

A brownfield workspace-onboarding workflow that reads an existing codebase and drafts product, architecture, and specification documents from it.

In plain words
What is it for?
Use it to inspect a repository, document its product and module structure, record unknowns as questions, and complete initial workspace setup.
Why use it?
It gives future work a shared project memory based on the code, while asking the developer only about details the code cannot reveal.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/iwe-org/dev-workspace/setup
Any agent
npx skills add iwe-org/dev-workspace --skill setup
Clone the repo
git clone --depth 1 https://github.com/iwe-org/dev-workspace

Made for: Claude Code, Codex.

Per session 79 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 938 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00079 $0.00938
Opus 5 $0.00039 $0.00469
Sonnet 5 $0.00016 $0.00188
Haiku 4.5 $0.00008 $0.00094

Measured 2d ago against content hash 144651a61948, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

setup 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 2d 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/setup/SKILL.md · 68 lines

How it starts

The opening of the file, as written. The whole thing — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Workspace setup

Turn the blank workspace into this project's memory. The codebase is the primary source — read it first and draft from evidence; ask the developer only what the code can't answer. Every future session reads what you write here.

Steps

  1. Assess. Read data/product.md. List which ✏️ blocks are unfilled. If everything is filled, ask what to revise instead of re-onboarding.
  2. Locate the codebase. Ask where the project's code lives (often the parent or a sibling directory of this workspace, or this workspace may sit inside the repo itself). If the project is greenfield — no code yet — skip to step 4 and run the interview alone.
  3. Scan. Read the repository's README, package manifests, build configuration, entry points, directory layout, and test setup. Draft from what you find:
    • data/product.md — What is it, Platforms, Stack from direct evidence; leave ✏️ plus a concrete question under any section the code can't answer (Users, Constraints usually need the developer).
    • One starting data/architecture/<slug>.md describing the module layout and any design decisions visible in the code (state management, storage, process boundaries). Say "unknown" where you'd be guessing. (The deep, per-module map under data/codebase/ is out of scope for setup — file it as follow-up work rather than attempting it here.)
    • Propose (don't yet write) spec docs for the 2–3 most load-bearing behaviors you can identify.
  4. Interview. Ask in batches, conversationally:
    • Product: the one-liner; who uses it and for what; who it's not for.
    • Reality: current stage, what's shipped vs. aspirational, the next thing they intend to build.
    • Constraints: performance budgets, compatibility promises, licensing, privacy — anything every plan must respect.
    • Rules: recurring instructions they find themselves repeating to agents or contributors — these become the Authoring rules section.
  5. Write. Fill every data/product.md section, deleting the italic instruction lines as sections fill; add a dated entry to its Changelog. Write the confirmed architecture doc(s) and any spec stubs the developer approved, linking each from data/architecture.md / data/spec.md.
  6. Close the loop. Mark the finished onboarding tasks (fill-product-doc, and capture-current-architecture if step 3 ran): iwe update -k data/backlog/<slug> --set stage=done --set completed=<today>, and move their links in data/backlog.md to ## Done. Delete the example docs — every *.example.md under data/ (iwe delete <key> per doc). iwe delete removes their inclusion links from hubs automatically but flattens inline links to plain text: sweep the hub files and remaining docs for leftover de-linked example lines and remove them.
  7. Validate & commit. iwe normalize, then iwe schema validate — both must pass clean. Commit with a message like setup: product doc filled, architecture captured, examples removed.

Read the full file on GitHub · 68 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. 2d ago First seen · 68 lines · 79 tokens per session scan A 144651a61948

Subscribe to this mod's changes

setup is a skill published in the GitHub repository iwe-org/dev-workspace (5 stars, last pushed 23d ago), licensed MIT. It adds 79 tokens to every session and 938 once invoked, about $0.0004 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.