ds-tune

ds-tune is a skill for Claude Code, Codex from sungurerdim/dev-skills. It costs 34 tokens per session (4,298 once invoked), scanned A, original, MIT.

An automated experiment loop for improving a project against a measurable target. It repeatedly changes the project, measures the result, and keeps improvements that can be verified.

In plain words
What is it for?
Use it to optimize measurable outcomes such as speed, accuracy, or bundle size, or to set up a self-improving experiment process.
Why use it?
Manual optimization is slow and can leave no clear record of which changes helped. This provides repeated experiments with machine-checkable evidence and an audit trail.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to optimize measurable outcomes such as speed, accuracy, or bundle size, or to set up a self-improving experiment process.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/sungurerdim/dev-skills/ds-tune
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 sungurerdim/dev-skills --skill ds-tune
Clone the repo
git clone --depth 1 https://github.com/sungurerdim/dev-skills

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 ds-tune

README.md
[![agentmods](https://agentmods.dev/badge/skills/sungurerdim/dev-skills/ds-tune.svg)](https://agentmods.dev/skills/sungurerdim/dev-skills/ds-tune)
Your own site
<a href="https://agentmods.dev/skills/sungurerdim/dev-skills/ds-tune"><img src="https://agentmods.dev/badge/skills/sungurerdim/dev-skills/ds-tune.svg" alt="Measured on agentmods" height="20"></a>
Per session 34 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,298 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.
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 $0.00034 $0.04298
Opus 5 $0.00017 $0.02149
Sonnet 5 $0.00007 $0.00860
Haiku 4.5 $0.00003 $0.00430

Measured 4d ago against content hash 4dc3331a684b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

ds-tune 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 4d 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.

ds-tune/SKILL.md · 208 lines

How it starts

The opening of the file, as written. The whole thing — 208 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/ds-tune

Manual optimization is slow — 8-10 experiments per day, subjective judgment, no audit trail. Skill runs 100+ experiments autonomously, keeping only what measurably improves.

Autonomous OptimizationKarpathy's autoresearch pattern generalized for any project with a measurable metric. Thanks to Andrej Karpathy for open-sourcing the core idea.

Completion Evidence — applies to every phase: Report done/OK only with the machine-checkable evidence the gates name — the exact command run and its observed output (or file:line diff). Missing evidence → report INCOMPLETE plus what is missing. Self-assessment is never evidence. (This band repeats at file end by design — both copies are normative.)

Triggers

  • User runs /ds-tune
  • User asks to optimize, tune, or improve a measurable aspect of their project
  • User asks "make this faster", "improve accuracy", "reduce bundle size", or similar
  • User asks to set up a self-improving loop

Triggers — INVOKE / DON'T INVOKE

INVOKE DON'T INVOKE
"make this faster", "optimize bundle size", "self-improving loop" "audit performance once (no loop)" (→ ds-review --perf)
"100+ experiments for one metric" "set performance budget + CI gate" (→ ds-launch --perf-budget)
"Karpathy-style autoresearch loop" "research optimization techniques abstractly" (→ ds-research)
"git-ratchet: keep only improvements" "manual optimization decisions" (→ user owns the choice)

Contract

Dimensions: D1

  • One file, one metric, one loop — Karpathy's core constraint. Skill generates optimization infrastructure (ds/tune/), then runs the loop under the git ratchet defined in Quality Gates (only measured improvements survive; every experiment committed before mechanical evaluation).
  • Standalone: use blueprint when available; own analysis when absent.
  • Full accounting enforced: every finding and planned check ends in an explicit disposition (fixed / skipped + reason / only you can do); summary totals balance.
  • Pre-existing / out-of-scope errors detected during work are NOT skipped — fixed inline or escalated with concrete blocker.

Read the full file on GitHub · 208 lines

Files

What ships with it

5 files 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. 4d ago Changed · -43 lines 4dc3331a684b
  2. 7d ago First seen · 251 lines · 34 tokens per session scan A 90c334758ee7

Subscribe to this mod's changes

ds-tune is a skill published in the GitHub repository sungurerdim/dev-skills (1 stars, last pushed 2d ago), licensed MIT. It adds 34 tokens to every session and 4,298 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 2026-08-31.

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