Measured Optimization Loop
EveryInc/compound-engineering-plugin
Optimizes a named target with a measured loop, attributing a workload's cost or scoring variants and keeping winners, on a dedicated branch with a disk log.
Guide agent-driven parameter optimization for configurable systems with measurable objectives.
MITAuto-check passed
Install Optim Agent
$ npx skills add sickn33/agentic-awesome-skills --skill optim-agent -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install sickn33/agentic-awesome-skills optim-agent --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/optim-agent .claude/skills/optim-agent && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "optim-agent" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/optim-agent into .claude/skills/optim-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "optim-agent", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/optim-agentType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add sickn33/agentic-awesome-skills --skill optim-agent -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install sickn33/agentic-awesome-skills optim-agent --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/optim-agent .agents/skills/optim-agent && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "optim-agent" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/optim-agent into .agents/skills/optim-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "optim-agent", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add sickn33/agentic-awesome-skills --skill optim-agent -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install sickn33/agentic-awesome-skills optim-agent --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/optim-agent .cursor/skills/optim-agent && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "optim-agent" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/optim-agent into .cursor/skills/optim-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "optim-agent", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/sickn33/agentic-awesome-skills.git --path skills/optim-agent--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add sickn33/agentic-awesome-skills --skill optim-agent -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install sickn33/agentic-awesome-skills optim-agent --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/optim-agent .gemini/skills/optim-agent && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "optim-agent" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/optim-agent into .gemini/skills/optim-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "optim-agent", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install sickn33/agentic-awesome-skills optim-agentInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add sickn33/agentic-awesome-skills --skill optim-agent -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/optim-agent .github/skills/optim-agent && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "optim-agent" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/optim-agent into .github/skills/optim-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "optim-agent", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add sickn33/agentic-awesome-skills --skill optim-agent -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install sickn33/agentic-awesome-skills optim-agent --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/optim-agent .opencode/skills/optim-agent && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "optim-agent" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/optim-agent into .opencode/skills/optim-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "optim-agent", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
optim-agent- GitHub stars
- 47k
- Used in
- 1 other repo
- Token cost
- ~1k tokens
- SKILL.md length
- 476 words
- Files
- 1
- Skills in repo
- 1,394
- Repo updated
- First seen
- Licence
- MIT
At a glance
Guide agent-driven parameter optimization for configurable systems with measurable objectives.
- Works in 9 steps: Define the optimization target in one… → List the tunable parameters, valid… → Establish at least one baseline before… → …
- Inference tuning
- SKILL.md covers Overview, When to Use This Skill, Do not use this skill when and Instructions, plus 4 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Optim Agent is an agent skill from sickn33/agentic-awesome-skills. Guide agent-driven parameter optimization for configurable systems with measurable objectives. Use for HPO, inference tuning, simulations, or RL/control experiments.
Its SKILL.md is about 1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
The repository describes itself as: AAS Core is the local, agent-first control plane for complete catalog discovery, agent-owned selection, stack validation, and planning, backed by 2,400+ agentic skills. Includes… The licence is MIT.
When your agent uses it
- Inference tuning
- RL/control experiments
Example prompts
- “/optim-agent”
Workflow steps
9 steps, taken from the first numbered list in SKILL.md.
- Define the optimization target in one sentence: maximize or minimize one scalar metric.
- List the tunable parameters, valid ranges, types, defaults, and any forbidden combinations.
- Establish at least one baseline before proposing agent-guided trials.
- Set the budget up front: number of trials, time, compute, money, or dataset subsample.
- Run or request trials one at a time unless the user explicitly approves parallel execution.
- Record every trial with parameters, metric value, notes, and failure status.
- Compare the best result against the baseline and a simple search strategy when possible.
- Stop when the budget is exhausted, the improvement plateaus, or the next trial cannot be justified from evidence.
- Report the recommended configuration, measured gain, tradeoffs, and any validation still needed before production use.
What it can do on your machine
Read from SKILL.md and the folder at commit 1e53ce2. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
github.comoptim-agent.github.io
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Optim Agent loads about 1k tokens when it runs. Until then it costs about 44 tokens; SKILL.md has 476 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from sickn33/agentic-awesome-skills at commit 1e53ce2, republished under its MIT licence (© sickn33). 476 words, ~1,018 tokens.
Download SKILL.mdSave it as
.claude/skills/optim-agent/SKILL.md (or your agent's skills folder).- name
- optim-agent
- description
- Guide agent-driven parameter optimization for configurable systems with measurable objectives. Use for HPO, inference tuning, simulations, or RL/control experiments.
- category
- data
- risk
- safe
- source
- community
- source_repo
- Optim-Agent/optim-agent
- source_type
- community
- date_added
- 2026-07-15
- author
- Optim-Agent
- tags
- optimization, hyperparameter-optimization, experiments, tuning
- tools
- claude, cursor, gemini, codex
- license
- MIT
Optim Agent
Overview
Use this skill to optimize configurable systems against a measurable scalar objective. It helps an agent turn vague tuning requests into bounded experiments with a defined search space, budget, baseline, and evidence-backed recommendation.
When to Use This Skill
- Use when tuning hyperparameters, prompts, inference settings, simulation parameters, quantitative strategies, or RL/control policies.
- Use when the objective can be measured as a scalar score, loss, accuracy, cost, latency, reward, or risk-adjusted metric.
- Use when the user needs a small-budget optimization loop with trial history, comparisons, and stop criteria.
Do not use this skill when
- The objective is purely subjective and cannot be scored consistently.
- The user has not provided permission to run experiments or consume compute/API budget.
- The task is a one-shot implementation, debugging, or code review request with no configurable search space.
Instructions
- Define the optimization target in one sentence: maximize or minimize one scalar metric.
- List the tunable parameters, valid ranges, types, defaults, and any forbidden combinations.
- Establish at least one baseline before proposing agent-guided trials.
- Set the budget up front: number of trials, time, compute, money, or dataset subsample.
- Run or request trials one at a time unless the user explicitly approves parallel execution.
- Record every trial with parameters, metric value, notes, and failure status.
- Compare the best result against the baseline and a simple search strategy when possible.
- Stop when the budget is exhausted, the improvement plateaus, or the next trial cannot be justified from evidence.
- Report the recommended configuration, measured gain, tradeoffs, and any validation still needed before production use.
Examples
Show full SKILL.md (209 more words)Show less
Example 1: Hyperparameter optimization
Tune learning rate, regularization, and tree depth for a credit-default model. Track validation AUC for each trial, compare against the default configuration, and recommend the best setting only if it improves the baseline under the agreed trial budget.
Example 2: Inference tuning
Tune retrieval depth, temperature, and reranker threshold for a RAG workflow. Optimize answer quality under a latency or cost ceiling, then report the best configuration with quality, latency, and cost tradeoffs.
Example 3: Simulation or control
Tune controller gains or environment parameters for a simulator. Optimize reward or error while logging failed trials separately so unstable configurations do not bias the recommendation.
Best Practices
- Keep the first run small; expand only after the loop produces useful signal.
- Prefer parameters with clear operational meaning over arbitrary knobs.
- Treat failed trials as data and record why they failed.
- Validate the final configuration on held-out data, a fresh seed, or a separate scenario before calling it robust.
- Ask before running expensive, long, or externally billed experiments.
Limitations
- This skill does not guarantee a global optimum.
- Results depend on objective quality, noise, search-space design, and experiment reproducibility.
- Use domain review before applying tuned configurations to production, financial, safety-critical, or user-impacting systems.
Additional Resources
© sickn33, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in skills/optim-agent of sickn33/agentic-awesome-skills.
Open the folder on GitHubat commit 1e53ce2
Used in 1 other repository
We found 5 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in sickn33/agentic-awesome-skills, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Optim Agent next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Optim Agent this skillsickn33/agentic-awesome-skills | 47k | 1 repos | ~1k | Automated safety check: Pass | MIT | |
| Measured Optimization LoopEveryInc/compound-engineering-plugin | 25k | — | ~2k | Automated safety check: Pass | MIT | |
| SQL Optimizationgithub/awesome-copilot | 40k | 2 repos | ~2.3k | Automated safety check: Pass | MIT | |
| Parametersthedaviddias/Front-End-Checklist | 74k | — | ~638 | Automated safety check: Pass | MIT | |
| Parameter Optimizationmajiayu000/claude-skill-registry | 666 | 2 repos | ~1.6k | Automated safety check: Pass | MIT | |
| Agent Performance Optimizerruvnet/ruflo | 74k | 2 repos | ~3.6k | Automated safety check: Pass | MIT |
Similar skills
- Official
SQL Optimization
github/awesome-copilot
Universal SQL performance optimization assistant for comprehensive query tuning, indexing strategies, and database performance analysis across all SQL databases (MySQL, PostgreSQL, SQL Server…
Parameters
thedaviddias/Front-End-Checklist
A skill your agent uses when auditing URL structure or configuring search engine handling of filtered, sorted, or tracked URLs.
Parameter Optimization
majiayu000/claude-skill-registry
Explore and optimize simulation parameters via design of experiments (DOE), sensitivity analysis, and optimizer selection.
Agent Performance Optimizer
ruvnet/ruflo
Agent skill for performance-optimizer - invoke with $agent-performance-optimizer
Database Optimizer
davila7/claude-code-templates
Expert database optimizer specializing in modern performance tuning, query optimization, and scalable architectures.
More from sickn33/agentic-awesome-skills
All 1,394 skills in this repoLiuguang Banlan UI
sickn33/agentic-awesome-skills
Implements an interface in one of two named color modes, iridescent white or colorful black, from a parameterized starter that reports measured color intensity.
User Thoughts Memory
sickn33/agentic-awesome-skills
Saves a user's project decisions, rules and preferences into a project-local mdbase so later sessions and other agents can recover the intent.
Using LWC Memory and Graphs
sickn33/agentic-awesome-skills
Keeps project decisions, research and verified results available across coding-agent sessions through LWC memory, a document Wiki graph and a CodeGraph code index.
Find Complementary Founders
sickn33/agentic-awesome-skills
Guides an agent through assessing its own owner for cofounder fit, publishing an approved profile, and ranking complementary profiles other agents published for their owners.
Whatsapp Cloud API
sickn33/agentic-awesome-skills
Integracao com WhatsApp Business Cloud API (Meta). An agent skill from sickn33/agentic-awesome-skills.
Cline Pilot
sickn33/agentic-awesome-skills
Acts as a proxy for the Cline CLI, dispatching coding tasks one at a time, monitoring runs by hard evidence, relaying decisions to you and learning per-project preferences.
Questions about Optim Agent
What does Optim Agent do?
Guide agent-driven parameter optimization for configurable systems with measurable objectives. Optim Agent is an agent skill from sickn33/agentic-awesome-skills. Guide agent-driven parameter optimization for configurable systems with measurable objectives.
When should I use Optim Agent?
Optim Agent fits situations like: inference tuning; RL/control experiments.
How do I install Optim Agent in Claude Code?
Run `npx skills add sickn33/agentic-awesome-skills --skill optim-agent -a claude-code`. Or copy the skill folder (skills/optim-agent in sickn33/agentic-awesome-skills) into .claude/skills/optim-agent in your project. Claude Code loads it when a task matches its description.
How do I install Optim Agent in Codex?
Run `npx skills add sickn33/agentic-awesome-skills --skill optim-agent -a codex`. Or copy the skill folder (skills/optim-agent in sickn33/agentic-awesome-skills) into .agents/skills/optim-agent in your project. Codex loads it when a task matches its description.
Can I use Optim Agent in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add sickn33/agentic-awesome-skills --skill optim-agent -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/optim-agent, .gemini/skills/optim-agent, .github/skills/optim-agent and .opencode/skills/optim-agent in your project.
What does Optim Agent need to run?
SKILL.md names no scripts, command-line tools or credentials: Optim Agent is instructions for the agent only.
Does Optim Agent access the network?
SKILL.md names 2 domains. As links in the text: github.com and optim-agent.github.io. This is read from the text; nothing was executed.
Is Optim Agent safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Optim Agent use?
Optim Agent is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Optim Agent use?
About 1k tokens (SKILL.md is roughly 4.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Optim Agent?
Skills that share tags, products or a category with Optim Agent: Measured Optimization Loop (EveryInc/compound-engineering-plugin, 25k stars), SQL Optimization (github/awesome-copilot, 40k stars), Parameters (thedaviddias/Front-End-Checklist, 74k stars) and Parameter Optimization (majiayu000/claude-skill-registry, 666 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Optim Agent?
sickn33 (a GitHub user) maintains it in sickn33/agentic-awesome-skills, which has 47,304 GitHub stars. The repository holds 1,394 skills in this directory. The repository was last updated on October 6, 2026.
Source: sickn33/agentic-awesome-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.