plan

A command that turns a feature request into an implementation plan with impact analysis, meaning a review of which parts of the codebase may be affected. It can accept input from a ticket or description and save the plan in the project.

In plain words
What is it for?
Use it to explore a repository, identify affected areas, create a feature plan, and run the configured planning checks.
Why use it?
It helps reveal dependencies and the likely blast radius before coding begins. This gives the team a structured plan and review point for larger changes.

Command

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/galando/temper/plan
Clone the repo
git clone --depth 1 https://github.com/galando/temper
Per session 8 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 808 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 $0.00808
Opus 5 $0.00004 $0.00404
Sonnet 5 $0.00002 $0.00162
Haiku 4.5 $0.00001 $0.00081

Measured yesterday against content hash b77221ceba77, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, 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 yesterday.

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 · 65 lines

How it starts

The opening of the file, as written. The whole thing — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Plan a Feature

Goal: Transform feature request into implementation plan with impact analysis.

Feature: $ARGUMENTS

Execution

Full methodology: Read $CLAUDE_PLUGIN_ROOT/reference/plan.md

Subprocess Mode

If $CLAUDE_PLUGIN_ROOT/scripts/temper config get stages.subprocess false returns true, don't run the methodology inline (skip the reference read and Quick Reference below). Launch the same isolated subprocess /temper uses — model from temper model plan, prompt: "Follow $CLAUDE_PLUGIN_ROOT/agents/plan.md exactly. Feature: $ARGUMENTS. Spec path: .temper/specs/{feature-slug}. Standalone run — no orchestrated Intent stage ran: author intent.md yourself per reference/plan.md's standalone case, and pass --spec-path .temper/specs/{feature-slug} to every temper gate call." Print the returned box verbatim, then run both gates + the approval AskUserQuestion per Deterministic Gate below — the subprocess is headless and already recorded its evidence; the human gate stays in this context either way.

Quick Reference

  1. Detect input (Jira/GitHub/description)
  2. Explore with your own tools (a nested Explore subagent is a judgment call for large repos, not a mandatory step)
  3. Research external docs if needed
  4. Assess complexity + risk (trivial/simple/medium/complex)
  5. Blast radius analysis, measured not estimated (consumers, contracts, security hot paths)
  6. Derive BDD scenarios from the blast radius (medium+ complexity) — before architecture
  7. Clarify if ambiguous (max 2-3 questions, informed by scenarios)
  8. Generate exactly intent.md + tasks.md + plan.md — never a fourth file — to .temper/specs/{feature}/ with file-to-scenario traceability
  9. For Medium and Complex: generate mermaid diagram + ASCII art equivalent in plan.md (## Diagram section); render ASCII in terminal summary (not raw mermaid)
  10. Record temper state set complexity <tier>, then run BOTH gates with an explicit spec path and fix any FAIL — see Deterministic Gate below: temper gate intent --spec-path .temper/specs/{feature-slug} (whenever intent.md exists — authored here or picked up as a draft) and temper gate plan --spec-path .temper/specs/{feature-slug}
  11. Present for approval with 4 options: Continue / Walkthrough / Change / Save

Read the full file on GitHub · 65 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. yesterday First seen · 65 lines · 8 tokens per session scan A b77221ceba77

Subscribe to this mod's changes

plan is a command published in the GitHub repository galando/temper (15 stars, last pushed 3d ago), licensed MIT. It adds 8 tokens to every session and 808 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 2026-08-30.