plan

plan is a command for Claude Code from d-padmanabhan/agent-engineering-handbook. It costs 13 tokens per session (418 once invoked), scanned A, original, MIT.

A command that puts the coding agent into a planning phase before implementation.

In plain words
What is it for?
Use it before code changes to define the problem, solution, alternatives, risks, dependencies, tests, and implementation plan.
Why use it?
It makes the agent inspect the request and existing code, consider options, document affected files, and wait for approval before writing code.

Command for Claude Code

Written for Claude Code: a Claude Code command (commands/*.md).

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 commands/d-padmanabhan/agent-engineering-handbook/plan
Clone the repo
git clone --depth 1 https://github.com/d-padmanabhan/agent-engineering-handbook

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/commands/d-padmanabhan/agent-engineering-handbook/plan.svg)](https://agentmods.dev/commands/d-padmanabhan/agent-engineering-handbook/plan)
Your own site
<a href="https://agentmods.dev/commands/d-padmanabhan/agent-engineering-handbook/plan"><img src="https://agentmods.dev/badge/commands/d-padmanabhan/agent-engineering-handbook/plan.svg" alt="Measured on agentmods" height="20"></a>
Per session 13 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 418 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 5.1 $0.00013 $0.00418
Opus 5 $0.00006 $0.00209
Sonnet 5 $0.00003 $0.00084
Haiku 4.5 $0.00001 $0.00042

Measured 6d ago against content hash ca32e9a59733, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

plan 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 6d 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.

commands/plan.md · 75 lines

What it actually says

PLANNING MODE ACTIVATED

You are now in PLANNING phase. Do NOT write code yet.

Your Tasks

  1. Analyze the Request

    • Understand scope, constraints, and requirements
    • Identify what's essential vs nice-to-have
    • Note any ambiguities
  2. Check Existing Code

    • Look for patterns, conventions, and reusable components
    • Understand the current architecture
    • Identify files/modules that will be affected
  3. Design the Solution

    • Propose approach with rationale
    • Consider 2-3 alternatives with pros/cons
    • Identify dependencies and risks
    • Plan testing strategy
  4. Document the Plan

    • Update tasks.md or active-context.md if they exist
    • List files to be modified
    • Outline implementation steps
  5. Present and WAIT

    • Show the plan clearly
    • Ask for explicit approval before proceeding (HITL / human-in-the-loop)
    • Answer any clarifying questions

Output Format

## Plan: [Brief Title]

### Problem
[What we're solving]

### Proposed Solution
[Your approach]

### Alternatives Considered
1. [Alternative 1] - [Why not chosen]
2. [Alternative 2] - [Why not chosen]

### Files Affected
- `path/to/file1.py` - [What changes]
- `path/to/file2.py` - [What changes]

### Implementation Steps
1. [Step 1]
2. [Step 2]
3. [Step 3]

### Risks
- [Risk 1]
- [Risk 2]

### Testing Strategy
- [How to test]

Rules

  • Ask max 3 clarifying questions if scope is ambiguous
  • Do NOT start coding until user approves
  • Keep plans concise but complete
  • Consider security implications
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. 6d ago First seen · 75 lines · 13 tokens per session scan A ca32e9a59733

Subscribe to this mod's changes

plan is a command published in the GitHub repository d-padmanabhan/agent-engineering-handbook (16 stars, last pushed 6d ago), licensed MIT. It adds 13 tokens to every session and 418 once invoked, about $0.0001 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 2026-08-30.