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/junghwayang/oh-my-codex/notenpx skills add junghwaYang/oh-my-codex --skill notegit clone --depth 1 https://github.com/junghwaYang/oh-my-codexWhat 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 | $0.00000 | $0.00529 |
| Opus 5 | $0.00000 | $0.00264 |
| Sonnet 5 | $0.00000 | $0.00106 |
| Haiku 4.5 | $0.00000 | $0.00053 |
Grade A, and why
note 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 2d 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.
What it actually says
Note Skill
In-session note taking and context preservation.
When to Use
- Recording decisions during development
- Tracking TODOs and ideas
- Preserving context for later
- Documenting discoveries
Note Types
Decision Notes
## Decision: {title}
Date: {date}
Status: Decided | Pending | Superseded
### Context
{Why did this come up?}
### Options Considered
1. {Option A} - {pros/cons}
2. {Option B} - {pros/cons}
### Decision
{What was decided and why}
### Consequences
- {impact 1}
- {impact 2}
TODO Notes
## TODO: {title}
Priority: High | Medium | Low
Status: Open | In Progress | Done
### Description
{What needs to be done}
### Context
{Why it matters}
### Acceptance Criteria
- [ ] {criterion 1}
- [ ] {criterion 2}
Discovery Notes
## Discovery: {title}
Date: {date}
### Finding
{What was discovered}
### Location
{Where in codebase}
### Implications
{What this means for the project}
### Action Items
- {action}
Context Notes
## Context: {topic}
Session: {session_id}
### Background
{Relevant background info}
### Current State
{Where we are now}
### Next Steps
{What comes next}
Storage
.codex/
├── notes/
│ ├── decisions/
│ ├── todos/
│ ├── discoveries/
│ └── context/
└── sessions/
└── {session_id}/
└── notes.md
Commands
note: we decided to use PostgreSQL over MongoDB for ACID compliance
note todo: add input validation to the user form
note discovery: found undocumented API endpoint at /internal/metrics
note context: auth system uses JWT with 15min expiry
Session Integration
Notes are automatically:
- Timestamped
- Linked to session
- Searchable
- Persistent across sessions
Quick Reference
| Command | Action |
|---|---|
note: |
General note |
note todo: |
Add TODO |
note decision: |
Record decision |
note discovery: |
Document finding |
note context: |
Save context |
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.
- 2d ago First seen · 127 lines · 0 tokens per session scan A 99754083aee0
note is a skill published in the GitHub repository junghwaYang/oh-my-codex (5 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 529 tokens. 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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cpu-profile-analysis
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agent-host-chat-contributions
Build and review cross-cutting agent-host chat behavior through lifecycle contributions. Use when adding turn lifecycle side effects, prompt or context injection, restored-history transformation, protocol-action observation, or when reviewing changes that add code to AgentSideEffects or AgentService.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.