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.
npx agentmods add skills/richfrem/agent-plugins-skills/os-evolution-plannernpx skills add richfrem/agent-plugins-skills --skill os-evolution-plannergit clone --depth 1 https://github.com/richfrem/agent-plugins-skillsWrote 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.
[](https://agentmods.dev/skills/richfrem/agent-plugins-skills/os-evolution-planner)<a href="https://agentmods.dev/skills/richfrem/agent-plugins-skills/os-evolution-planner"><img src="https://agentmods.dev/badge/skills/richfrem/agent-plugins-skills/os-evolution-planner.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00103 | $0.02590 |
| Opus 5 | $0.00051 | $0.01295 |
| Sonnet 5 | $0.00021 | $0.00518 |
| Haiku 4.5 | $0.00010 | $0.00259 |
Grade A, and why
os-evolution-planner 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.
How it starts
The opening of the file, as written. The whole thing — 244 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Role
os-evolution-planner transforms an evolution goal into a structured task plan and a Copilot CLI delegation prompt that can be dispatched in one premium request. Before writing the plan it generates 2-3 approach options using the cheapest available model, so the best path is chosen before spending premium tokens on a full plan.
Inputs
| Input | How provided | Default |
|---|---|---|
| Target plugin | argument or interview question | required |
| Target skill or agent | argument or interview question | "all" (full plugin audit) |
| Evolution goal | argument or interview question | required |
| Auto-detect gaps | flag | true |
| Dispatch immediately | flag | false (present for human review) |
Phase 0 — Read Environment Profile
Before doing anything else, check context/memory/environment.md:
- If it exists, read the
## Delegation Strategysection to determine:- Brainstorm model (cheapest available)
- Dispatch backend (Copilot CLI or Claude subagent)
- If it does not exist, default to Claude-only mode and note:
"No environment profile found — defaulting to Claude-only. Run
os-environment-probeto unlock low-cost Copilot or Agy brainstorming."
Phase 1 — Brainstorm Options (cheap model)
Do this before gap detection and before writing any plan.
Native Plan Mode required for Phases 0-1: per graph-planning-superpowers-policy.md §2.1,
enter host-native Plan Mode (Claude Code /plan, or the host's equivalent) before Phase 0 begins.
Phases 0-1 are read/analysis-only — checking the environment profile and generating approach
sketches. Do NOT write the task plan, delegation prompt, or any target file until the user has
selected an option (A/B/C/modify) below and Plan Mode is exited.
Using the cheapest available model, generate 2-3 distinct approaches to the evolution goal. Each approach sketch is ~3-5 sentences: what it does, what it doesn't do, estimated effort, key tradeoff.
Model selection (use first that is available per environment profile):
What ships with it
4 files 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.
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.
- yesterday Changed ccb3cf37451c
- 5d ago First seen · 244 lines · 103 tokens per session scan A 2ac2e37c7d23
os-evolution-planner is a skill published in the GitHub repository richfrem/agent-plugins-skills (6 stars, last pushed yesterday), licensed MIT. It adds 103 tokens to every session and 2,590 once invoked, about $0.0005 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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