do-feature

do-feature is a skill for Claude Code, Codex from w693847022/memory_service. It costs 8 tokens per session (584 once invoked), scanned A, original, MIT.

A guided workflow for developing a software feature from project confirmation through solution design, coding, and tests.

In plain words
What is it for?
Recording a feature, exploring the codebase, choosing and documenting an implementation plan, writing code, running unit and integration tests, and updating the development log.
Why use it?
It keeps the feature’s plan, implementation, tests, and development history together instead of handling each part separately.

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/w693847022/memory_service/do-feature
Any agent
npx skills add w693847022/memory_service --skill do-feature
Clone the repo
git clone --depth 1 https://github.com/w693847022/memory_service

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 do-feature

README.md
[![agentmods](https://agentmods.dev/badge/skills/w693847022/memory_service/do-feature.svg)](https://agentmods.dev/skills/w693847022/memory_service/do-feature)
Your own site
<a href="https://agentmods.dev/skills/w693847022/memory_service/do-feature"><img src="https://agentmods.dev/badge/skills/w693847022/memory_service/do-feature.svg" alt="Measured on agentmods" height="20"></a>
Per session 8 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 584 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 $0.00008 $0.00584
Opus 5 $0.00004 $0.00292
Sonnet 5 $0.00002 $0.00117
Haiku 4.5 $0.00001 $0.00058

Measured 4d ago against content hash 672074a17fd5, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

do-feature 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 4d 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.

examples/skills/do-feature/SKILL.md · 106 lines

What it actually says

简短功能开发技能

⚠️ 重要指令

DO NOT ENTER PLAN MODE - 此技能要求直接执行,不进入计划模式

所有memory_mcp的操作使用子代理来处理,减少主窗口上下文


使用示例

/skill do-feature "feature: 添加用户登录功能"

流程概览

阶段1(项目确认) → 阶段2(方案设计) → 阶段3(代码实现)

阶段 1: 项目确认

目标: 确认项目和创建feature记录

流程:

  1. 解析入参,提取功能描述(去掉 feature: 前缀)
  2. 调用 ./project-confirmation.md 技能创建feature记录
    Skill: project-confirmation, args: "<功能描述>"
    
  3. 获取 feature_id

输出:

  • feature_id: 功能ID
  • project_id: 项目ID

阶段 2: 方案设计与选择

调用技能处理该阶段: solution-design

Skill: solution-design, args: "<feature_id>"

技能会完成:

  1. 方案设计(探索代码库并设计方案)
  2. 用户选择方案
  3. 方案详细规划
  4. 创建note记录完整方案
  5. 更新development-log

输出:

  • selected_solution: 选择的实现方案

阶段 3: 代码实现与测试

调用技能处理该阶段: code-implementation

Skill: code-implementation, args: "<feature_id>"

技能会完成:

  1. 代码实现
  2. 单元测试
  3. 整合测试
  4. 更新development-log

输出:

  • implementation_result: 实现结果

完成展示

feature:
  - feature_id
  - feature:summary
  - feature:content

note:
  - note_id:summary (implementation-plan)
  - note_id:summary (development-log)

总结本次修改:xxx
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. 4d ago First seen · 106 lines · 8 tokens per session scan A 672074a17fd5

Subscribe to this mod's changes

do-feature is a skill published in the GitHub repository w693847022/memory_service (1 stars, last pushed 3mo ago), licensed MIT. It adds 8 tokens to every session and 584 once invoked, about $0.0000 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

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

brainstorming

You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

obra/superpowers · 37 tokens

auto-perf-optimize

Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.

microsoft/vscode · 62 tokens

chat-perf

Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.

microsoft/vscode · 51 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens