auto-implement

auto-implement is a skill for Claude Code, Codex from careerchain-ys/stdd. It costs 134 tokens per session (3,119 once invoked), scanned A, original, Apache-2.0.

An automated workflow that takes a software task from an issue, document, URL, or plain description through clarification, specifications, planning, coding, testing, review, design updates, and pull-request creation.

In plain words
What is it for?
Use it to turn a GitHub issue or other task description into requirements and technical design, then implement, test, review, and prepare the change for a pull request.
Why use it?
It organizes the many stages between an idea and a reviewed code change, especially when the original request is incomplete or unclear.

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/careerchain-ys/stdd/auto-implement
Any agent
npx skills add careerchain-ys/stdd --skill auto-implement
Clone the repo
git clone --depth 1 https://github.com/careerchain-ys/stdd

Made for: Claude Code, Codex.

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 auto-implement

README.md
[![agentmods](https://agentmods.dev/badge/skills/careerchain-ys/stdd/auto-implement.svg)](https://agentmods.dev/skills/careerchain-ys/stdd/auto-implement)
Your own site
<a href="https://agentmods.dev/skills/careerchain-ys/stdd/auto-implement"><img src="https://agentmods.dev/badge/skills/careerchain-ys/stdd/auto-implement.svg" alt="Measured on agentmods" height="20"></a>
Per session 134 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,119 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 $0.00134 $0.03119
Opus 5 $0.00067 $0.01559
Sonnet 5 $0.00027 $0.00624
Haiku 4.5 $0.00013 $0.00312

Measured 3d ago against content hash aa8cc99589ba, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

auto-implement 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 3d 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.

.agents/skills/auto-implement/SKILL.md · 183 lines

How it starts

The opening of the file, as written. The whole thing — 183 lines — stays where its author put it; the contents beside it link to each section on GitHub.

自動実装オーケストレーション

実装したい課題(GitHub issue / 自由記述の要望 / 既存ドキュメント / Slack・Notion などの参照 / URL)を受け取り、ヒアリングで対象を確定したうえで、Spec作成→実装→QA→コードレビュー→PR作成までを自動で実行するオーケストレーションスキル。

入力は GitHub issue に限らない。 issue 番号があればそれを使うが、無くてもよい。入力が無い / 曖昧な場合は Step 1 のヒアリングで対象を具体化してから進める。

引数

形式: [<入力>] [--mode <full|spec-only|impl-only|quick>]

  • <入力>(任意): #<issue番号> / issue URL / 自由記述のタスク説明 / ドキュメントのパス・URL のいずれでも可。省略可能。
  • --mode(任意): 実行モード。

Step 1: 入力のヒアリングと確定

auto-implement の対象(実装したい issue / 課題 / 要望)を確定するフェーズ。いきなり実装に進まず、まずここで対象を明確にする。

  1. 初期入力の取り込み: 引数で入力が与えられていれば、その種別を判定する。
    • #<番号> または issue URL → GitHub issue(Step 2 で gh 取得)
    • 自由記述のテキスト → タスク記述としてそのまま扱う
    • ファイルパス / ドキュメント URL → 読み込んでタスク記述の素材にする
  2. ヒアリング: 入力が無い、または上記だけでは auto-implement を始めるのに不十分な場合は、ユーザーに以下を確認する(AskUserQuestion 等で簡潔に):
    • 何を実装したいか(目的・背景・解決したい課題)
    • 入力ソース(GitHub issue / 自由記述 / 既存ドキュメント / その他)— issue なら番号を聞く
    • スコープ・制約(対象アプリ / 機能、含める・含めないもの、既知の制約)
  3. 確定: 課題内容が「Spec 作成に着手できる程度」に具体化できたら、要点をユーザーに復唱して確認を取る。曖昧なまま先に進まない。

このヒアリングの結果(タスクのタイトル相当・本文相当・スコープ)を、以降のフェーズの**入力(タスク記述)**として扱う。

Step 2: 入力情報の取得・正規化

Step 1 で確定した入力を、以降のフェーズが扱えるタスク記述(タイトル相当・本文相当・補足)に正規化する。

  • GitHub issue の場合: GitHub MCP tools または gh issue view で取得する。
    • タイトル / 本文(description) / ラベル / コメント
  • issue 以外の場合(自由記述・ドキュメント等): ヒアリング結果や参照ドキュメントから、タイトル相当・本文相当・スコープを構成する。ラベルは無いものとして扱う。

以降のステップで「issue」と記載がある箇所は、issue 以外の入力ではこの正規化済みタスク記述に読み替える。

Step 3: 実行モード判定

--mode が指定されている場合はそのモードを使用。未指定の場合は以下のロジックで自動判定する(issue 以外の入力では「ラベル」条件は対象外。タイトル・本文の内容で判定する):

条件 モード
(issue の場合)ラベルに bug を含む / 不具合の修正が主目的 impl-only
ラベルに documentation を含む、またはタイトルに「Spec」「リバースエンジニアリング」を含む spec-only
タイトルに「typo」「修正」を含む、または本文が短い(200文字以下) quick
上記いずれにも該当しない full

Read the full file on GitHub · 183 lines

Files

What ships with it

1 file 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. 3d ago First seen · 183 lines · 134 tokens per session scan A aa8cc99589ba

Subscribe to this mod's changes

auto-implement is a skill published in the GitHub repository careerchain-ys/stdd (2 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 134 tokens to every session and 3,119 once invoked, about $0.0007 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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