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/jmstar85/oh-my-githubcopilot/self-improvenpx skills add jmstar85/oh-my-githubcopilot --skill self-improvegit clone --depth 1 https://github.com/jmstar85/oh-my-githubcopilotWrote 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/jmstar85/oh-my-githubcopilot/self-improve)<a href="https://agentmods.dev/skills/jmstar85/oh-my-githubcopilot/self-improve"><img src="https://agentmods.dev/badge/skills/jmstar85/oh-my-githubcopilot/self-improve.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 | $0.00041 | $0.02170 |
| Opus 5 | $0.00020 | $0.01085 |
| Sonnet 5 | $0.00008 | $0.00434 |
| Haiku 4.5 | $0.00004 | $0.00217 |
Grade A, and why
self-improve 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.
This is a copy
88% identical to self-improve — 64 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 221 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Self-Improvement Orchestrator
Autonomous loop controller for evolutionary code improvement. Manages the full lifecycle: setup, research, planning, execution, tournament selection, history recording, and stop-condition evaluation.
When to Use
- You want to iteratively improve a codebase toward a measurable benchmark goal
- Optimization tasks: performance, bundle size, test coverage, accuracy
- Code quality improvement with measurable metrics
When NOT to Use
- No measurable benchmark available
- One-shot fix or feature request → use
/omg-autopilot - Manual, interactive coding → use
/ralph
Autonomous Execution Policy
NEVER stop or pause to ask the user during the improvement loop. Once the gate check passes and the loop begins, run fully autonomously until a stop condition is met.
- Do not ask for confirmation between iterations
- On agent failure: retry once, then skip and continue
- On all plans rejected: log it, continue to next iteration
- The only things that stop the loop are the stop conditions in Step 11
State Tracking
All state lives under .omg/self-improve/:
.omg/self-improve/
├── config/
│ ├── settings.json # agents, benchmark, thresholds, sealed_files
│ ├── goal.md # Improvement objective + target metric
│ ├── harness.md # Guardrail rules (H001/H002/H003)
│ └── idea.md # User experiment ideas
├── state/
│ ├── agent-settings.json # iterations, best_score, status, counters
│ ├── iteration_state.json # Within-iteration progress (resumability)
│ ├── research_briefs/ # Research output per round
│ ├── iteration_history/ # Full history per round
│ ├── merge_reports/ # Tournament results
│ └── plan_archive/ # Archived plans (permanent)
├── plans/ # Active plans (current round)
└── tracking/
├── raw_data.json # All candidate scores
├── baseline.json # Initial benchmark score
└── events.json # Config 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.
- 3d ago First seen · 221 lines · 41 tokens per session scan A 08b963558ec3
self-improve is a skill published in the GitHub repository jmstar85/oh-my-githubcopilot (153 stars, last pushed 3mo ago), licensed MIT. It adds 41 tokens to every session and 2,170 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to self-improve, differing in 64 lines, and is treated as a copy.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
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.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…