c31-dev

A guided software-development process for starting a new project or feature. It moves through requirements questioning, a PRD, technical planning, and execution, with user approval between stages.

In plain words
What is it for?
Use it to clarify needs, write a product requirements document, create a technical plan, and carry out the approved work.
Why use it?
It helps turn an unclear idea into an agreed plan before coding 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/chianw/c31/c31-dev
Any agent
npx skills add ChianW/C31 --skill c31-dev
Clone the repo
git clone --depth 1 https://github.com/ChianW/C31

Made for: Claude Code, Codex.

Per session 128 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,565 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 $0.00128 $0.02565
Opus 5 $0.00064 $0.01282
Sonnet 5 $0.00026 $0.00513
Haiku 4.5 $0.00013 $0.00257

Measured 2d ago against content hash def95ff05ec6, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

c31-dev 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.

skills/core/c31-dev/SKILL.md · 206 lines

How it starts

The opening of the file, as written. The whole thing — 206 lines — stays where its author put it; the contents beside it link to each section on GitHub.

C31-Dev — 完整开发流水线引导

Philosophy

Process over speed. Shared understanding before execution.

C31-Dev 不是"一键自动化",而是"有刹车的流水线"。每个阶段的用户确认是不可跳过的——这正是它存在的理由。

Pipeline 概览

┌──────────┐     ┌──────────┐     ┌──────────┐     ┌──────────┐
│  C31-    │ ──→ │  C31-    │ ──→ │  C31-    │ ──→ │  C31-    │
│  Grill   │     │  Spec    │     │  Plan    │     │  LFG     │
│ (拷问)   │     │ (PRD)    │     │ (蓝图)   │     │ (执行)   │
└──────────┘     └──────────┘     └──────────┘     └──────────┘
     ↑                 ↑                ↑                ↑
  用户确认          用户确认         用户确认         用户确认
  "共识达成"        "PRD OK"        "Plan OK"        "开干"

触发条件

  • "我要做个…" / "我想开发…" / "I want to build..."
  • "实现这个…" / "开发新功能"
  • "走完整流程" / "pipeline" / "全流程"
  • 任何从零开始构建软件/工具/功能的请求

Workflow

Phase 0: 初始化

步骤 0.1: 读取已有上下文

  • 检查 memory/.planning/phases/ 是否有相关 PRD/Plan
  • 检查 memory/grill-sessions/ 是否有相关共识文档
  • 搜索 memory/ 看是否有历史项目关联

步骤 0.2: 初始化状态

  • 创建/读取 memory/.planning/pipeline-state-{project}.md
  • 标记当前阶段为 grill
  • 向用户说明 Pipeline 流程和确认门控机制

"进入 C31-Dev 流水线。我们会依次经过 Grill(需求拷问)→ Spec(PRD)→ Plan(技术规划)→ Work(执行)。每个阶段需要你的确认才能进入下一步。随时可以喊停。"

Phase 1: Grill(需求拷问 + 复杂度判定)

Grill 阶段同时承担复杂度判定职责——通过逐层拷问暴露隐藏假设,让真实复杂度自然浮现。不需要预评估。

步骤 1.1: 遵循 skills/C31-grill/SKILL.md 的完整流程:

  • 一次一问,附带推荐答案
  • 自动检测新术语、关键决策、记忆冲突
  • 实时写入 memory/glossary.mdmemory/decisions/

步骤 1.2: 复杂度判定(Grill 过程中自然浮现)

信号 含义
3-5 个问题后用户说"行了,很清楚了" 项目简单,可能跳过 Spec 直接 Plan 或直接 Work
多个分支都需要深入确认 标准流程:Grill → Spec → Plan → Work
涉及架构变更、安全、外部依赖 深度流程:Grill 不跳过,Plan 需 CEDAR + STRIDE

步骤 1.3: 共识确认

  • 输出共识文档摘要
  • 询问用户:"共识是否达成?进入 Spec 阶段,还是跳过直接 Plan/Work?"
  • 选项:确认进 Spec / 跳过 Spec 直接 Plan / 跳过 Spec+Plan 直接 Work / 继续 Grill / 暂停

Phase 2: Spec(PRD 撰写)

激活条件:Grill 共识达成后,用户未选择跳过

步骤 2.1: 读取 Phase 1 的共识文档(如存在)和现有 REQUIREMENTS.md

步骤 2.2: 遵循 skills/C31-spec/SKILL.md 的 5 步流程:

  1. 必要时拦截"直接写代码"的冲动
  2. 渐进式披露 5 个问题
  3. 撰写 PRD → memory/.planning/phases/XX-PRD.md
  4. 验证门:成功标准可验证?边界非空?
  5. 生成 PLAN 骨架

Read the full file on GitHub · 206 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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 · 206 lines · 128 tokens per session scan A def95ff05ec6

Subscribe to this mod's changes

c31-dev is a skill published in the GitHub repository ChianW/C31 (1 stars, last pushed 7d ago), licensed MIT. It adds 128 tokens to every session and 2,565 once invoked, about $0.0006 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.

Related

Other skills, from other repositories

compare-harnesses

Diff two scaffolded harnesses (ADR-031). Reports manifest meta drift + host list + per-file fingerprint changes (added/removed/changed). Exits 0 IDENTICAL, 1 DRIFT, 2 missing manifest. Use --bundle for the ADR-031 schema-1 JSON envelope.

ruvnet/metaharness · 66 tokens

create-harness

Scaffold your own focused AI agent harness — pick host (Claude Code, Codex, pi.dev, Hermes), template, agents, skills, and ship a npm-publishable harness with its own npx CLI. Use when a user asks to "create my own agent harness", "scaffold a harness", "make a custom Claude Code plugin like ruflo", or "build a…

ruvnet/metaharness · 89 tokens

diag-harness

Kernel-version skew check (ADR-027). Reports manifest surface + manifest kernel + installed kernel + verdict (match/patch-diff/minor-diff/major-diff). Exits 1 on minor/major skew with a copy-pasteable npm install @metaharness/[email protected] next step. Exits 2 if no .harness/manifest.json at path.

ruvnet/metaharness · 85 tokens

example-harness

Scaffold a ready-made AI agent harness in one command from the 19 published @metaharness/ example packages — 9 host integrations (Claude Code, Codex, Hermes, pi.dev, OpenClaw, RVM, Copilot, OpenCode, GitHub Actions) + 10 vertical pods (devops, research, trading, support, legal, coding, education, sales, gaming…

ruvnet/metaharness · 90 tokens

oia-manifest

Emit .harness/oia-manifest.json declaring layer alignment with the OIA v0.1 9-layer reference architecture. Self-describes the harness's MCP wiring, witness signing, audit log, identity posture (always 'none' at v0.1). --check verifies an existing manifest, --dry-run prints without writing, --json emits to stdout.

ruvnet/metaharness · 79 tokens

repo-genome

7-section readiness scorecard for a LOCAL repo. Reports repo type + agent topology + MCP risk + test confidence + release readiness + recommended harness plan + scorecard. Exit 0 ready, 1 needs-work, 2 blocked. --json for the 6-field scorecard, --bundle for the ADR-031 schema-1 envelope.

ruvnet/metaharness · 73 tokens