Mmr Loop Skill
9600dev/mmr
Autonomous trading loop for the MMR platform. An agent skill from 9600dev/mmr.
Optimize strategy parameters using VectorBT. An agent skill from marketcalls/vectorbt-backtesting-skills.
Install Optimize
$ npx skills add marketcalls/vectorbt-backtesting-skills --skill optimize -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install marketcalls/vectorbt-backtesting-skills optimize --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/marketcalls/vectorbt-backtesting-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/optimize .claude/skills/optimize && 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 "optimize" agent skill from https://github.com/marketcalls/vectorbt-backtesting-skills/tree/master/.claude/skills/optimize into .claude/skills/optimize/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "optimize", 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/marketcalls/vectorbt-backtesting-skills/tree/master/.claude/skills/optimizeType 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 marketcalls/vectorbt-backtesting-skills --skill optimize -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install marketcalls/vectorbt-backtesting-skills optimize --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/marketcalls/vectorbt-backtesting-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/optimize .agents/skills/optimize && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "optimize" agent skill from https://github.com/marketcalls/vectorbt-backtesting-skills/tree/master/.claude/skills/optimize into .agents/skills/optimize/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "optimize", 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 marketcalls/vectorbt-backtesting-skills --skill optimize -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install marketcalls/vectorbt-backtesting-skills optimize --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/marketcalls/vectorbt-backtesting-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/optimize .cursor/skills/optimize && 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 "optimize" agent skill from https://github.com/marketcalls/vectorbt-backtesting-skills/tree/master/.claude/skills/optimize into .cursor/skills/optimize/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "optimize", 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/marketcalls/vectorbt-backtesting-skills.git --path .claude/skills/optimize--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 marketcalls/vectorbt-backtesting-skills --skill optimize -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install marketcalls/vectorbt-backtesting-skills optimize --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/marketcalls/vectorbt-backtesting-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/optimize .gemini/skills/optimize && 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 "optimize" agent skill from https://github.com/marketcalls/vectorbt-backtesting-skills/tree/master/.claude/skills/optimize into .gemini/skills/optimize/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "optimize", 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 marketcalls/vectorbt-backtesting-skills optimizeInstalls 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 marketcalls/vectorbt-backtesting-skills --skill optimize -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/marketcalls/vectorbt-backtesting-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/optimize .github/skills/optimize && 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 "optimize" agent skill from https://github.com/marketcalls/vectorbt-backtesting-skills/tree/master/.claude/skills/optimize into .github/skills/optimize/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "optimize", 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 marketcalls/vectorbt-backtesting-skills --skill optimize -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install marketcalls/vectorbt-backtesting-skills optimize --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/marketcalls/vectorbt-backtesting-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/optimize .opencode/skills/optimize && 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 "optimize" agent skill from https://github.com/marketcalls/vectorbt-backtesting-skills/tree/master/.claude/skills/optimize into .opencode/skills/optimize/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "optimize", 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
optimize- GitHub stars
- 208
- Token cost
- ~758 tokens
- SKILL.md length
- 335 words
- Files
- 1
- Skills in repo
- 6
- Repo updated
- First seen
- Licence
- None found
At a glance
Optimize strategy parameters using VectorBT. An agent skill from marketcalls/vectorbt-backtesting-skills.
- Works in 6 steps: Read the vectorbt-expert skill rules for… → Create backtesting/{strategy_name}/… → Create a .py file in… → …
- Tasks that involve Trading and backtesting
- SKILL.md covers Arguments, Instructions, Default Parameter Ranges and Example Usage
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Optimize is an agent skill from marketcalls/vectorbt-backtesting-skills. Optimize strategy parameters using VectorBT. Tests parameter combinations and generates heatmaps.
Its SKILL.md is about 760 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Business, Finance & HR, covering Trading and backtesting. It works with DuckDB and Plotly. The repository describes itself as: Agentic coding skills for backtesting trading strategies using VectorBT. Supports Indian, US, and Crypto markets with realistic transaction cost modeling, TA-Lib indicators…
When your agent uses it
- Tasks that involve Trading and backtesting
Example prompts
- “/optimize”
Requirements
- Pre-approved tools (allowed-tools): Read, Write, Edit, Bash, Glob, Grep
Workflow steps
6 steps, taken from the first numbered list in SKILL.md.
- Read the vectorbt-expert skill rules for reference patterns
- Create backtesting/{strategy_name}/ directory if it doesn't exist (on-demand)
- Create a .py file in backtesting/{strategy_name}/ named {symbol}_{strategy}_optimize.py
- The script must
- Never use icons/emojis in code or logger output
- For futures symbols, use lot-size-aware sizing
What it can do on your machine
Read from SKILL.md and the folder at commit 05d9e8b. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves these tools, so the agent can use them without asking each time:
ReadWriteEditBashGlobGrep
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
No URLs in SKILL.md.
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
Optimize loads about 758 tokens when it runs. Until then it costs about 27 tokens; SKILL.md has 335 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: notes
The automated check noted patterns worth knowing about, such as sudo or a known installer.
- NoteMentions a .env fileSKILL.md:27
- Load `.env` from project root using `find_dotenv()` and fetch data via OpenAlgo `client.history()` - NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
allowed-tools: Read, Write, Edit, Bash, Glob, Grep
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
Without a licence we can't republish the file, so here is its outline and opening line. It has 335 words (~758 tokens).
“Create a parameter optimization script for a VectorBT strategy.”
- name
- optimize
- allowed-tools
- Read, Write, Edit, Bash, Glob, Grep
- argument-hint
- [strategy] [symbol] [exchange] [interval]
Files
Just SKILL.md in .claude/skills/optimize of marketcalls/vectorbt-backtesting-skills.
Open the folder on GitHubat commit 05d9e8b
Compare with similar skills
Optimize 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 |
|---|---|---|---|---|---|---|
| Optimize this skillmarketcalls/vectorbt-backtesting-skills | 208 | — | ~758 | Automated safety check: Notes | None | |
| Mmr Loop Skill9600dev/mmr | 131 | — | ~2.6k | Automated safety check: Pass | Custom licence | |
| DojoNecmttn/ax | 116 | — | ~1.7k | Automated safety check: Pass | AGPL-3.0 | |
| Tushare Datazillionare/zillionare | 319 | 2 repos | ~2.3k | Automated safety check: Pass | None | |
| Tradingview MCPatilaahmettaner/tradingview-mcp | 5k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Digital Oraclekomako-workshop/digital-oracle | 870 | — | ~5.9k | Automated safety check: Pass | MIT |
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Surplus-quota training loop over the ax graph - the agent burns the remaining 5h/7d plan-quota window on self-improvement: locking pending verdicts, filling briefs, backtesting routing classes…
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面向中文自然语言的 Tushare 数据研究技能。用于把“看看这只股票最近怎么样”“帮我查财报趋势”“最近哪个板块最强”“北向资金在买什么”“给我导出一份行情数据”这类请求，转成可执行的数据获取、清洗、对比、筛选、导出与简要分析流程。适用于 A 股、指数、ETF/基金、财务、估值、资金流、公告新闻、板块概念与宏观数据等研究场景。
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Categories
Questions about Optimize
What does Optimize do?
Optimize strategy parameters using VectorBT. An agent skill from marketcalls/vectorbt-backtesting-skills. Optimize is an agent skill from marketcalls/vectorbt-backtesting-skills. Optimize strategy parameters using VectorBT.
When should I use Optimize?
Optimize fits situations like: tasks that involve Trading and backtesting.
How do I install Optimize in Claude Code?
Run `npx skills add marketcalls/vectorbt-backtesting-skills --skill optimize -a claude-code`. Or copy the skill folder (.claude/skills/optimize in marketcalls/vectorbt-backtesting-skills) into .claude/skills/optimize in your project. Claude Code loads it when a task matches its description.
How do I install Optimize in Codex?
Run `npx skills add marketcalls/vectorbt-backtesting-skills --skill optimize -a codex`. Or copy the skill folder (.claude/skills/optimize in marketcalls/vectorbt-backtesting-skills) into .agents/skills/optimize in your project. Codex loads it when a task matches its description.
Can I use Optimize 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 marketcalls/vectorbt-backtesting-skills --skill optimize -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/optimize, .gemini/skills/optimize, .github/skills/optimize and .opencode/skills/optimize in your project.
What does Optimize need to run?
SKILL.md names no scripts, command-line tools or credentials: Optimize is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Write, Edit, Bash, Glob, Grep.
Does Optimize access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Optimize safe to install?
Our automated static check of SKILL.md found notes only (mentions a .env file; pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
What licence does Optimize use?
No licence was found for Optimize or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.
How many tokens does Optimize use?
About 758 tokens (SKILL.md is roughly 3k 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 Optimize?
Skills that share tags, products or a category with Optimize: Mmr Loop Skill (9600dev/mmr, 131 stars), Dojo (Necmttn/ax, 116 stars), Tushare Data (zillionare/zillionare, 319 stars) and Tradingview MCP (atilaahmettaner/tradingview-mcp, 5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Optimize?
marketcalls (a GitHub user) maintains it in marketcalls/vectorbt-backtesting-skills, which has 208 GitHub stars. The repository holds 6 skills in this directory. The repository was last updated on July 12, 2026.
Source: marketcalls/vectorbt-backtesting-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.