performance-goal

performance-goal is a skill for Claude Code, Codex from Yeachan-Heo/oh-my-codex. It costs 27 tokens per session (789 once invoked), scanned A, original, MIT.

A performance-optimization workflow that uses evaluator checks and saved planning records. Performance optimization means making software faster or more efficient.

In plain words
What is it for?
Use it to improve application performance, run evaluation gates, and pass optimization work safely between agents.
Why use it?
It provides checks for deciding whether an optimization helped and preserves the work between handoffs.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions Codex.

Good fit Use it to improve application performance, run evaluation gates, and pass optimization work safely between agents.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/yeachan-heo/oh-my-codex/performance-goal
About the project

oh-my-codex is a workflow layer for OpenAI Codex CLI that adds prompts, agent teams, skills, hooks, HUDs, and other runtime assistance while leaving Codex as the execution engine. It is for people who use Codex CLI and want structured workflows and additional help as tasks become larger. The catalogue entries are its skills, hooks, and MCP integrations for those Codex workflows.

Yeachan-Heo/oh-my-codex · 33,722 stars · on GitHub · oh-my-codex.dev

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 Yeachan-Heo/oh-my-codex --skill performance-goal
Clone the repo
git clone --depth 1 https://github.com/Yeachan-Heo/oh-my-codex

Made for: Claude Code, Codex.

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 performance-goal

README.md
[![agentmods](https://agentmods.dev/badge/skills/yeachan-heo/oh-my-codex/performance-goal/github.svg)](https://agentmods.dev/skills/yeachan-heo/oh-my-codex/performance-goal)
Your own site
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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 performance-goal

Your own site · 80×15
<a href="https://agentmods.dev/skills/yeachan-heo/oh-my-codex/performance-goal"><img src="https://agentmods.dev/badge/skills/yeachan-heo/oh-my-codex/performance-goal.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 27 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 789 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. ✓ AI security review Fable 5.1 · 6 Sept 2026 📄 Read the review 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 $0.00027 $0.00789
Opus 5.5 $0.00011 $0.00316
Sonnet 5.5 $0.00005 $0.00158
Haiku 4.5 $0.00003 $0.00079

Measured 2mo ago against content hash 5adac796c4d8, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

performance-goal 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 2mo 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

plugins/oh-my-codex/skills/performance-goal/SKILL.md · 69 lines

How it starts

The opening of the file, as written. The whole thing — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Performance Goal Workflow

Use this skill when a user asks OMX to optimize performance and wants a goal-oriented loop rather than a one-off review.

Contract

  • OMX owns durable workflow state under .omx/goals/performance/<slug>/.
  • Codex goal mode owns only the active-thread focus/accounting primitive.
  • Shell commands do not mutate hidden Codex goal state. They write artifacts and emit model-facing handoff text.
  • No optimization work may start until an evaluator command and pass/fail contract exist.
  • Do not call update_goal({status: "complete"}) until the evaluator has a passing checkpoint and a completion audit proves the objective is done; then call get_goal again and pass that fresh snapshot to omx performance-goal complete --codex-goal-json.

CLI

Create the workflow and evaluator contract:

omx performance-goal create \
  --objective "Reduce CLI startup latency by 20%" \
  --evaluator-command "npm run perf:startup" \
  --evaluator-contract "PASS when p95 latency improves by 20% and regression tests pass" \
  --slug startup-latency

Emit the Codex goal handoff:

omx performance-goal start --slug startup-latency

Record evaluator evidence:

omx performance-goal checkpoint --slug startup-latency --status pass --evidence "benchmark + tests passed"
omx performance-goal checkpoint --slug startup-latency --status fail --evidence "benchmark regressed"
omx performance-goal checkpoint --slug startup-latency --status blocked --evidence "missing fixture"

Complete only after a passing checkpoint:

omx performance-goal complete --slug startup-latency --evidence "final evaluator evidence" --codex-goal-json <get_goal-json-or-path>

Agent Loop

  1. Run omx performance-goal create if no workflow exists.
  2. Run omx performance-goal start and follow the handoff:
    • call get_goal;
    • call create_goal only when no active goal exists and the objective is explicit;
    • work only against the evaluator contract;
    • after evaluator pass and completion audit, call update_goal({status: "complete"}), call get_goal again, and pass that snapshot to omx performance-goal complete --codex-goal-json;
    • after omx performance-goal complete succeeds, run /goal clear in the Codex UI before starting another goal in this same thread/session; OMX prints this terminal cleanup step but does not invoke hidden clear routes;
  3. Optimize in small reversible patches.
  4. Run the evaluator and related regression tests.
  5. Record each pass/fail/blocker with checkpoint.
  6. Complete only when the pass artifact exists and no required work remains.

Read the full file on GitHub · 69 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. 2mo ago First seen · 69 lines · 27 tokens per session scan A 5adac796c4d8

Subscribe to this mod's changes

performance-goal is a skill published in the GitHub repository Yeachan-Heo/oh-my-codex (33,722 stars, last pushed 3d ago), licensed MIT. It adds 27 tokens to every session and 789 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.

Related

performance-goal compared with skills from other repositories

performance-goal next to 6 skills from other repositories
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