scaffold

A planning method that compares several possible build orders for a software design and combines them into one recommended sequence.

In plain words
What is it for?
Use it with a design document, prototype, or product requirements document to plan how modules, integrations, tests, and deployment should be built.
Why use it?
It makes dependencies, milestones, testing needs, deployment work, and risks visible before implementation starts.

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/sjarmak/coding-agent-workflows/scaffold
Any agent
npx skills add sjarmak/coding-agent-workflows --skill scaffold
Clone the repo
git clone --depth 1 https://github.com/sjarmak/coding-agent-workflows

Made for: Claude Code, Codex.

Per session 37 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,910 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 $0.00037 $0.01910
Opus 5 $0.00018 $0.00955
Sonnet 5 $0.00007 $0.00382
Haiku 4.5 $0.00004 $0.00191

Measured 2d ago against content hash 510846ff9da6, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

scaffold 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.

source/skills/scaffold/SKILL.md · 189 lines

How it starts

The opening of the file, as written. The whole thing — 189 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Scaffold: Build-Order Planning

Take a chosen design (from diverge-prototype or any architecture decision) and spawn N independent agents, each proposing a different build-order strategy. Each produces a sequenced implementation plan with milestones, dependencies, and a risk assessment; the results synthesize into one recommended build plan.

Arguments

[N] [path/to/design.md | inline description]

  • N is the number of strategies (default 4, min 2, max 6).
  • Input is a path to a design doc/prototype/PRD, or an inline description of what needs to be built. Missing or unclear: ask the user to clarify before starting.

Phase 1: Understand the Design

Read the design doc, prototype, or PRD provided. Extract the following:

  • Components to build: every distinct module, service, or subsystem
  • Dependencies between them: what requires what
  • External integrations: third-party APIs, databases, services
  • Testing requirements: what needs testing and at what level
  • Deployment needs: infrastructure, environments, CI/CD

Prepare a build brief that summarizes:

  • What needs to be built
  • What exists already (if working within an existing codebase)
  • What the constraints are (technical, timeline, team)

Present the build brief to the user and confirm before proceeding. Adjust if the user gives feedback.

Phase 2: Spawn Sequencing Agents

Launch all N agents in parallel using the Agent tool. Each agent receives the build brief plus a unique sequencing strategy drawn from this pool (assign strategies 1 through N):

  1. "Riskiest-First": Start with the highest-uncertainty components. Front-load risk to learn early whether the approach works. Motto: "fail fast on the hard stuff."
  2. "Demo-able First": Start with the components that produce visible, testable output. Build stakeholder confidence early. Motto: "something to show every sprint."
  3. "Dependency-Topological": Strict dependency order. Build foundations first, layers on top. Nothing starts until its dependencies are complete. Motto: "no stubs, no mocks, each piece works when built."
  4. "Vertical Slice": Build one thin end-to-end path through the entire system first. Proves integration works before widening. Motto: "narrow and deep before wide."
  5. "Test Infrastructure First": Start with test harness, CI/CD, monitoring, observability. Build the ability to verify before building things to verify. Motto: "confidence before velocity."
  6. "Parallel Tracks": Identify independent work streams that can proceed simultaneously. Optimize for team throughput. Motto: "max parallelism, defined interfaces."

Read the full file on GitHub · 189 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 · 189 lines · 37 tokens per session scan A 510846ff9da6

Subscribe to this mod's changes

scaffold is a skill published in the GitHub repository sjarmak/coding-agent-workflows (2 stars, last pushed 1mo ago), licensed MIT. It adds 37 tokens to every session and 1,910 once invoked, about $0.0002 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.

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