self-improve

self-improve is a skill for Claude Code, Codex from zereight/gitlab-mcp. It costs 41 tokens per session (1,653 once invoked), scanned A, original, MIT.

An automated process for repeatedly improving code against a measurable benchmark, such as speed, bundle size, accuracy, or test coverage.

In plain words
What is it for?
Use it for benchmark-driven optimization and code-quality improvements where progress can be measured.
Why use it?
It lets improvements be compared across iterations and uses stop conditions instead of relying only on one-time judgment.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/zereight/gitlab-mcp/self-improve
Any agent
npx skills add zereight/gitlab-mcp --skill self-improve
Clone the repo
git clone --depth 1 https://github.com/zereight/gitlab-mcp

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 self-improve

README.md
[![agentmods](https://agentmods.dev/badge/skills/zereight/gitlab-mcp/self-improve.svg)](https://agentmods.dev/skills/zereight/gitlab-mcp/self-improve)
Your own site
<a href="https://agentmods.dev/skills/zereight/gitlab-mcp/self-improve"><img src="https://agentmods.dev/badge/skills/zereight/gitlab-mcp/self-improve.svg" alt="Measured on agentmods" height="20"></a>
Per session 41 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,653 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00041 $0.01653
Opus 5 $0.00020 $0.00826
Sonnet 5 $0.00008 $0.00331
Haiku 4.5 $0.00004 $0.00165

Measured 3d ago against content hash dc14a44a123b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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.

Origin

Copies of this mod

2 near-identical copies found in the catalogue:

.github/skills/self-improve/SKILL.md · 175 lines

How it starts

The opening of the file, as written. The whole thing — 175 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 .omc/self-improve/:

.omc/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

Read the full file on GitHub · 175 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. 3d ago First seen · 175 lines · 41 tokens per session scan A dc14a44a123b

Subscribe to this mod's changes

self-improve is a skill published in the GitHub repository zereight/gitlab-mcp (1,939 stars, last pushed yesterday), licensed MIT. It adds 41 tokens to every session and 1,653 once invoked, about $0.0002 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 2026-08-30.

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