EngramGraph: Skill for Claude Code

.agents/skills/plan/SKILL.md

plan is a skill for Claude Code from AsiaOstrich/EngramGraph. It costs 74 tokens per session (2,397 once invoked), scanned C, original, MIT.

A tool that turns specification documents or written requirements into a plan.json task plan. A specification is a written description of what a system should do and how it should be built.

In plain words
What is it for?
Use it to create plans from Markdown specs, OpenSpec changes, or free-text requirements before running them with an orchestration tool.
Why use it?
It removes the manual work of turning requirements into ordered, executable tasks and can read several specification formats.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter. Also seen: mentions CLAUDE.md; installed under .agents/ (shared by several agents); mentions AGENTS.md.

This is AsiaOstrich/EngramGraph's own configuration. It tells Claude Code how to work on EngramGraph 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 EngramGraph configures →

Reuse

Borrowing it

Nothing to install: this file belongs to AsiaOstrich/EngramGraph. 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/AsiaOstrich/EngramGraph/main/.agents/skills/plan/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/AsiaOstrich/EngramGraph

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 plan

README.md
[![agentmods](https://agentmods.dev/badge/skills/asiaostrich/engramgraph/plan/github.svg)](https://agentmods.dev/skills/asiaostrich/engramgraph/plan)
Your own site
<a href="https://agentmods.dev/skills/asiaostrich/engramgraph/plan"><img src="https://agentmods.dev/badge/skills/asiaostrich/engramgraph/plan/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 plan

Your own site · 80×15
<a href="https://agentmods.dev/skills/asiaostrich/engramgraph/plan"><img src="https://agentmods.dev/badge/skills/asiaostrich/engramgraph/plan.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 74 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,397 The whole file, excluding the scripts and references it only reads on demand.
Security scan C 1 finding. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00074 $0.02397
Opus 5.5 $0.00030 $0.00959
Sonnet 5.5 $0.00015 $0.00479
Haiku 4.5 $0.00007 $0.00240

Measured 14d ago against content hash 14359e142649, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade C, and why

plan scanned grade C with 1 finding 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 14d 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.

Recursive force deletehighDestructive command

rm -rf with a variable or a broad path is one typo away from removing the wrong tree.

3. **安全掃描**:task.spec 不含危險指令(`rm -rf /`、`DROP DATABASE`、`git push --force`)
.agents/skills/plan/SKILL.md · 236 lines

How it starts

The opening of the file, as written. The whole thing — 236 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/plan — 從 Spec 自動生成 plan.json

用法

/plan <spec-file.md>              # Spec 模式(自有格式 / SpecKit)
/plan <openspec-change-dir/>      # OpenSpec 模式
/plan "需求描述文字"               # 需求模式
/plan                             # 互動模式(自動偵測)

執行流程

Step 1: 輸入辨識與格式偵測

根據引數類型判斷使用模式:

引數是 .md 檔案:

  1. 讀取檔案內容
  2. 偵測格式:
    • 含 ## Requirements 且 ## Technical Design → 自有格式(SPEC-NNN-*.md)
    • 含 ## Summary 且 ## Detailed Design → SpecKit 格式
    • 其他 .md → 嘗試解析為通用 Spec(按自有格式處理,缺少的欄位由 AI 補充)

引數是目錄:

  1. 檢查是否含 proposal.md + tasks.md → OpenSpec 格式
  2. 否則報錯:「此目錄不符合 OpenSpec 結構」

引數是字串描述(非檔案路徑): → 需求模式

無引數: → 互動模式

  1. 偵測 openspec/ 目錄存在? → 列出 changes 讓使用者選擇
  2. 偵測 specs/*.md 存在? → 列出可用 Spec 讓使用者選擇
  3. 都沒有 → 進入需求模式問答

Step 2: 專案 Context 收集

讀取目標專案的關鍵資訊:

  1. CLAUDE.md / AGENTS.md — 語言、框架、測試工具、開發規範
  2. package.json / pyproject.toml — 可用 scripts(build, test, lint)

從 Context 推斷:

  • 主要語言(TypeScript / Python / 其他)
  • 預設 verify_command(如 pnpm build && pnpm test、pytest -x)
  • 預設 lint_command(如 pnpm lint、ruff check .)

Step 3: Spec 解析

依偵測到的格式,解析 Spec 內容:

自有格式(SPEC-NNN-*.md)

提取以下區段:

  • Summary / Motivation → 理解背景與需求動機
  • Requirements (REQ-NNN) → 功能需求列表
  • Acceptance Criteria (AC-N) → Given/When/Then 驗收條件
  • Technical Design → Phase 分層、每個 Phase 的實作項目
  • Test Plan → 測試清單
  • Risks → 風險評估
OpenSpec(change 目錄)

讀取以下檔案:

  • proposal.md → Why(動機)、What Changes(變更項目)、Impact
  • tasks.md → - [ ] checklist 項目
  • design.md(若存在)→ 技術決策
  • specs/*/spec.md(若存在)→ Requirements(SHALL/MUST 語句)、Scenarios
SpecKit(SPEC-ID.md)

提取以下區段:

  • Summary / Motivation → 背景
  • Detailed Design → 技術實作步驟
  • Acceptance Criteria → checkbox 驗收條件
  • Dependencies → 外部依賴
  • Risks → 風險

Step 4: Task 切分

依格式套用不同映射規則:

自有格式映射規則
Spec 區段 plan.json 欄位 映射規則
Technical Design > Phase 一組 tasks 每個 Phase 的每個實作項目 = 1 個 task
Phase 實作項目描述 task.spec 合併:項目描述 + 相關 REQ + 技術細節
Acceptance Criteria (AC-N) task.acceptance_criteria 分配到最相關的 task
Summary / Motivation task.user_intent 萃取與 task 最相關的意圖
Test Plan task.verify_command 推斷測試指令

Read the full file on GitHub · 236 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. 14d ago First seen · 236 lines · 74 tokens per session scan C 14359e142649

Subscribe to this mod's changes

plan is a skill published in the GitHub repository AsiaOstrich/EngramGraph (3 stars, last pushed today), licensed MIT. It adds 74 tokens to every session and 2,397 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-16.

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