extremely-optimize

extremely-optimize is a skill for Claude Code, Codex from OutlineDriven/odin-claude-plugin. It costs 30 tokens per session (1,685 once invoked), scanned A, original, Apache-2.0.

A performance-rebuilding method that measures a subsystem, separates its frequently used paths from rarely used ones, and redesigns the costly parts around their unavoidable work.

In plain words
What is it for?
Use it for a named slow path or a broader performance campaign. It profiles the workload, ranks targets, and rebuilds one target at a time with each change kept separate.
Why use it?
It addresses cases where repeated small fixes no longer produce useful speed gains because the underlying design remains expensive.

Skill for Claude CodeCodex

Written for Claude Code and Codex: shipped in a Claude Code plugin, but also agents/openai.yaml present.

Part of the odin-code plugin — 60 skills shipped together

Good fit Use it for a named slow path or a broader performance campaign. It profiles the workload, ranks targets, and rebuilds one target at a time with each change kept separate.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/outlinedriven/odin-claude-plugin/extremely-optimize
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.

Any agent
npx skills add OutlineDriven/odin-claude-plugin --skill extremely-optimize
Clone the repo
git clone --depth 1 https://github.com/OutlineDriven/odin-claude-plugin

Made for: Claude Code, Codex.

Or install odin-code, the plugin that ships this one along with the rest of its 60 skills.

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 extremely-optimize

README.md
[![agentmods](https://agentmods.dev/badge/skills/outlinedriven/odin-claude-plugin/extremely-optimize/github.svg)](https://agentmods.dev/skills/outlinedriven/odin-claude-plugin/extremely-optimize)
Your own site
<a href="https://agentmods.dev/skills/outlinedriven/odin-claude-plugin/extremely-optimize"><img src="https://agentmods.dev/badge/skills/outlinedriven/odin-claude-plugin/extremely-optimize/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 extremely-optimize

Your own site · 80×15
<a href="https://agentmods.dev/skills/outlinedriven/odin-claude-plugin/extremely-optimize"><img src="https://agentmods.dev/badge/skills/outlinedriven/odin-claude-plugin/extremely-optimize.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 30 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,685 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00030 $0.01685
Opus 5.5 $0.00012 $0.00674
Sonnet 5.5 $0.00006 $0.00337
Haiku 4.5 $0.00003 $0.00169

Measured 1mo ago against content hash d6e5ff035d62, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

extremely-optimize 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.

plugins/odin-code/skills/extremely-optimize/SKILL.md · 59 lines

How it starts

The opening of the file, as written. The whole thing — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Extremely optimize

Contract

Field Bound contract
Trigger Subsystem or repo-wide performance campaign against a measured floor; the user says "make this as fast as possible", "extremely optimize", or "grill every inefficiency"
Authority Reversible local: writes only VCS-tracked source targets (destructive; the exact set shown before mutation); rollback is version control. No remote mutation.
Side effect Hot-path source targets rewritten as atomic commits; non-wins reverted; boundary surfaces gated before any touch
Done Hot units rebuilt with an even win, cold units graded fixed/at-floor/left, residue gone, verifier green, target landed atomically

Inputs

  • A named subsystem path, or no path for a repo-wide survey. Repo-wide work is opt-in and never inferred. A bare invocation profiles the repo's own workload, then works the ranked list.
  • One runnable workload command exercising the target with representative input and taking at least one second of wall clock. Must be supplied or constructed before measurement begins.
  • The repo's own verifier command. Must be supplied or discovered before any target lands.

Procedure

  1. Pin the workload and baseline. Run hyperfine --warmup 3 --min-runs 10 '<cmd>'. Record median, stddev, min, max. Reject the measurement while stddev exceeds 20 % of median: pin CPU frequency, isolate the process, widen --min-runs, or enlarge the input until the noise clears. Use this number for every later comparison. Done when: a stable baseline median is recorded with stddev under 20 % of median.

  2. Split hot from cold. Profile the workload. A unit is hot when it holds ≥ 5 % of total measured time or its call count scales with input size; everything else is cold. Write both lists down. Where a sampling profiler disagrees with a call-count argument, believe the call count and confirm by instrumentation. Done when: both hot and cold lists are written down.

  3. State the contract, compute the floor. Work the hot list in descending order of time share. For each unit, write what it owes its callers based on call sites, tests, and the signature: never its own internals. Compute the floor from that contract alone: bytes that must move at achievable bandwidth, the algorithmic lower bound at a measured per-operation cost, and syscalls or round-trips the protocol cannot avoid. Show the arithmetic with eval, never in prose. Divide measured cost by floor; that multiple is the unit's headroom. A unit already within 2× of its floor is finished: record it and move on. Done when: every hot unit has its contract stated, floor computed, and headroom multiple recorded; units within 2× of floor are marked finished.

Read the full file on GitHub · 59 lines

Files

What ships with it

1 file 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.

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 Changed · -24 tokens per session d6e5ff035d62
  2. 1mo ago Changed · -62 lines · -34 tokens per session 440ec48f8779
  3. 1mo ago First seen · 121 lines · 88 tokens per session scan A 83ea73c4b238

Subscribe to this mod's changes

extremely-optimize is a skill published in the GitHub repository OutlineDriven/odin-claude-plugin (37 stars, last pushed 21d ago), licensed Apache-2.0. It adds 30 tokens to every session and 1,685 once invoked, about $0.0001 per session on Opus 5.5. 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.

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