plan

An agent role that creates a step-by-step technical implementation plan from requirements, architecture, work breakdown, and an API contract. It saves the plan in .ai/temp/plan.md for engineers to use.

In plain words
What is it for?
Planning software changes and giving downstream engineers a shared implementation reference.
Why use it?
It turns broad technical requirements into an ordered plan before implementation begins.

Agent

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 agents/nelson820125/iforgeai/plan
Clone the repo
git clone --depth 1 https://github.com/nelson820125/iforgeai
Per session 54 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 212 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 $0.00054 $0.00212
Opus 5 $0.00027 $0.00106
Sonnet 5 $0.00011 $0.00042
Haiku 4.5 $0.00005 $0.00021

Measured 3d ago against content hash de6965bb12d4, 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 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.

copilot/agents/plan.agent.md · 19 lines

What it actually says

#file:{{INSTALL_SKILLS_PATH}}/plan/SKILL.md

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 · 19 lines · 54 tokens per session scan A de6965bb12d4

Subscribe to this mod's changes

plan is an agent published in the GitHub repository nelson820125/iforgeai (8 stars, last pushed 4mo ago), licensed MIT. It adds 54 tokens to every session and 212 once invoked, about $0.0003 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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