codingbuddy: Command for Claude Code

.opencode/commands/plan-feature.md

plan-feature is a command for Claude Code, OpenCode from JeremyDev87/codingbuddy. It costs 0 tokens per session (224 once invoked), scanned A, original, MIT.

A command that studies a feature request and creates a structured implementation plan under the project’s .ai-rules standards. TDD means writing tests before the code they check; Test-After means adding tests after implementation.

In plain words
What is it for?
Use it to plan features, inspect recent project history, choose TDD or Test-After for different work, create a prioritised todo list, and produce the response in Korean.
Why use it?
It turns requirements and project context into an actionable plan with tasks, risks, testing choices, and quality checks.

Command for Claude CodeOpenCode

Written for OpenCode and Claude Code: installed under .opencode/, but also a Claude Code command (commands/*.md). Also seen: positional $N argument; mentions OpenCode.

This is JeremyDev87/codingbuddy's own configuration. It tells Claude Code and OpenCode how to work on codingbuddy 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 codingbuddy configures →

Reuse

Borrowing it

Nothing to install: this file belongs to JeremyDev87/codingbuddy. 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/JeremyDev87/codingbuddy/master/.opencode/commands/plan-feature.md
Clone the repo
git clone --depth 1 https://github.com/JeremyDev87/codingbuddy

Made for: Claude Code, OpenCode.

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-feature

README.md
[![agentmods](https://agentmods.dev/badge/commands/jeremydev87/codingbuddy/plan-feature/github.svg)](https://agentmods.dev/commands/jeremydev87/codingbuddy/plan-feature)
Your own site
<a href="https://agentmods.dev/commands/jeremydev87/codingbuddy/plan-feature"><img src="https://agentmods.dev/badge/commands/jeremydev87/codingbuddy/plan-feature/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-feature

Your own site · 80×15
<a href="https://agentmods.dev/commands/jeremydev87/codingbuddy/plan-feature"><img src="https://agentmods.dev/badge/commands/jeremydev87/codingbuddy/plan-feature.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 224 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. 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 $0.00000 $0.00224
Opus 5.5 $0.00000 $0.00090
Sonnet 5.5 $0.00000 $0.00045
Haiku 4.5 $0.00000 $0.00022

Measured 1mo ago against content hash ecbb0901ee97, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

plan-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 1mo 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.

.opencode/commands/plan-feature.md · 41 lines

What it actually says

PLAN Feature Command

Description

Analyze requirements and create structured implementation plan following .ai-rules standards.

Command

# Read context
READ packages/rules/.ai-rules/rules/core.md
READ packages/rules/.ai-rules/rules/project.md  
READ packages/rules/.ai-rules/rules/augmented-coding.md

# Analyze project state
RUN git status
RUN git log --oneline -10

# Create plan
PLAN implementation for: $1
- Follow TDD cycle for core logic
- Use Test-After for UI components
- Maintain 90%+ test coverage
- Apply SOLID principles
- Generate todo list with priorities
- Include risk assessment

# Output in Korean
RESPOND in Korean (한국어)

Usage

# In OpenCode CLI
/plan-feature "사용자 등록 기능"

Expected Output

  • Structured PLAN mode response
  • Todo list creation using todo_write tool
  • TDD vs Test-After strategy decision
  • File structure planning
  • Quality checklist
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. 1mo ago First seen · 41 lines · 0 tokens per session scan A ecbb0901ee97

Subscribe to this mod's changes

plan-feature is a command published in the GitHub repository JeremyDev87/codingbuddy (31 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 224 tokens. 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 2026-08-30.