Tushare Data
zillionare/zillionare
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。
A skill your agent uses when running, interpreting, or designing backtests on Superior Trade — anything about backtest windows, trade-count thresholds, exit-reason mix, parameter sweeps…
Install Backtesting
$ npx skills add Superior-Trade/superior-skills --skill backtesting -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Superior-Trade/superior-skills backtesting --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/Superior-Trade/superior-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/backtesting .claude/skills/backtesting && 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 "backtesting" agent skill from https://github.com/Superior-Trade/superior-skills/tree/main/skills/backtesting into .claude/skills/backtesting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "backtesting", 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/Superior-Trade/superior-skills/tree/main/skills/backtestingType 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 Superior-Trade/superior-skills --skill backtesting -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Superior-Trade/superior-skills backtesting --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Superior-Trade/superior-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/backtesting .agents/skills/backtesting && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "backtesting" agent skill from https://github.com/Superior-Trade/superior-skills/tree/main/skills/backtesting into .agents/skills/backtesting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "backtesting", 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 Superior-Trade/superior-skills --skill backtesting -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Superior-Trade/superior-skills backtesting --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Superior-Trade/superior-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/backtesting .cursor/skills/backtesting && 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 "backtesting" agent skill from https://github.com/Superior-Trade/superior-skills/tree/main/skills/backtesting into .cursor/skills/backtesting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "backtesting", 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/Superior-Trade/superior-skills.git --path skills/backtesting--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 Superior-Trade/superior-skills --skill backtesting -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Superior-Trade/superior-skills backtesting --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Superior-Trade/superior-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/backtesting .gemini/skills/backtesting && 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 "backtesting" agent skill from https://github.com/Superior-Trade/superior-skills/tree/main/skills/backtesting into .gemini/skills/backtesting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "backtesting", 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 Superior-Trade/superior-skills backtestingInstalls 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 Superior-Trade/superior-skills --skill backtesting -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Superior-Trade/superior-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/backtesting .github/skills/backtesting && 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 "backtesting" agent skill from https://github.com/Superior-Trade/superior-skills/tree/main/skills/backtesting into .github/skills/backtesting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "backtesting", 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 Superior-Trade/superior-skills --skill backtesting -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Superior-Trade/superior-skills backtesting --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Superior-Trade/superior-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/backtesting .opencode/skills/backtesting && 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 "backtesting" agent skill from https://github.com/Superior-Trade/superior-skills/tree/main/skills/backtesting into .opencode/skills/backtesting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "backtesting", 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
backtesting- GitHub stars
- 214
- Used in
- 1 other repo
- Token cost
- ~2.9k tokens
- SKILL.md length
- 1,429 words
- Files
- 1
- Skills in repo
- 31
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when running, interpreting, or designing backtests on Superior Trade — anything about backtest windows, trade-count thresholds, exit-reason mix, parameter sweeps…
- Works in 2 steps: Walk-forward to a similar pair. Pick a… → Defer the deployment recommendation. A…
- Designing backtests on Superior Trade — anything about backtest windows
- SKILL.md covers The trade-count bar (sample…, Pick a backtest window that…, Don't optimize against the… and The 3-variant parameter sweep, plus 5 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Backtesting is an agent skill from Superior-Trade/superior-skills. Use when running, interpreting, or designing backtests on Superior Trade — anything about backtest windows, trade-count thresholds, exit-reason mix, parameter sweeps, walk-forward validation, zero-trade diagnosis, compute-cost estimation, or "is this backtest result trustworthy?". Pair with the relevant strategy skill, such as mean-reversion or breakout.
Its SKILL.md is about 2.9k 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. The repository describes itself as: Open agent skills and tool schemas for Superior Trade — build, backtest, and deploy trading strategies on Hyperliquid. The licence is MIT.
When your agent uses it
- Designing backtests on Superior Trade — anything about backtest windows
- Trade-count thresholds
- Exit-reason mix
- Parameter sweeps
Example prompts
- “is this backtest result trustworthy?”
- “/backtesting”
Workflow steps
2 steps, taken from the first numbered list in SKILL.md.
- Walk-forward to a similar pair. Pick a sibling perp with longer history (e.g. test the strategy on BTC if BTC-AAPL is too new), then…
- Defer the deployment recommendation. A 14-day backtest is too thin to recommend live capital, period. Tell the user that.
What it can do on your machine
Read from SKILL.md and the folder at commit 9d41db5. 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
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
Backtesting loads about 2.9k tokens when it runs. Until then it costs about 92 tokens; SKILL.md has 1,429 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 Superior-Trade/superior-skills at commit 9d41db5, republished under its MIT licence (© Superior-Trade). 1,429 words, ~2,907 tokens.
Download SKILL.mdSave it as
.claude/skills/backtesting/SKILL.md (or your agent's skills folder).- name
- backtesting
- description
- Use when running, interpreting, or designing backtests on Superior Trade — anything about backtest windows, trade-count thresholds, exit-reason mix, parameter sweeps, walk-forward validation, zero-trade diagnosis, compute-cost estimation, or "is this backtest result trustworthy?". Pair with the relevant strategy skill, such as mean-reversion or breakout.
- metadata.version
- 0.1.0
- metadata.updated
- 2026-05-07
Backtesting Best Practices
Read ../../references/unified-runtime.md
for the shared API lifecycle. Submit every run with POST /runtime/backtests;
creation queues it, so there is no separate start request. Use the framework and
venue fields defined by GET /openapi.json and the relevant venue skill. This
page is about the judgment calls — picking a window that means something,
telling signal from noise in the result, and knowing when to give up vs. iterate.
The trade-count bar (sample size first)
Trade count is the single most important number on a result page. Look at it before PnL, before Sharpe, before win rate.
| Trade count | Verdict |
|---|---|
| < 30 | Coincidence, not a strategy. Don't promise anything; widen entries or extend window. |
| 30-50 | Marginal. Sharpe is noisy. Treat results as directional, not numeric. |
| 50-200 | Useful. Sharpe / profit factor start to mean something. |
| 200+ | Statistical confidence. Now you can compare variants on micro-differences. |
Watch for the trap: backtests with 5-10 trades and a 100% win rate. They look like world-beaters and almost always disintegrate live. The strategy is too selective — every signal is a coin flip you've cherry-picked, not a repeatable edge. Widen the entry threshold, lengthen the window, or accept that there's no statistical signal here.
Pick a backtest window that means something
A great backtest over the wrong window is a great fiction.
The window should answer: "if I had deployed this strategy on day one of this window, what would have happened?" — not "what's the prettiest curve I can fit?"
Cover at least one regime change
Pure bull, pure bear, sideways chop — your window should include at least two of the three. A 90-day backtest in a one-direction market is a 90-day cherry-pick. A momentum strategy that prints +50% over a +60% trending window has told you nothing about itself; it's just measured beta.
Useful default windows
- 6 months of 1h data, or
- 18 months of 1d data
Less than that and you're really looking at noise. More than that and Hyperliquid's history may not cover the pair (HL was launched in 2023; many alts have < 12mo of data).
When you can't get a long window
Some HIP3 / new-listing pairs only have a few weeks of data. Two pragmatic responses:
- Walk-forward to a similar pair. Pick a sibling perp with longer history (e.g. test the strategy on
BTCifBTC-AAPLis too new), then assume the result transfers ±20%. - Defer the deployment recommendation. A 14-day backtest is too thin to recommend live capital, period. Tell the user that.
Don't optimize against the test set (the cardinal sin)
If you tune parameters and validate on the same window, your backtest is a souvenir, not a forecast. This is the single most common reason strategies that look brilliant on paper die in the first week of live trading.
The honest workflow:
- Pick parameters from theory or a single observation, NOT from a sweep.
- Run the backtest.
- If results are bad, change the idea, not the parameters.
If you do sweep, walk forward to a different period or pair before promoting the winner. A parameter that wins on Q1 BTC and also wins on Q1 ETH (out-of-sample for the second pair) is real. A parameter that wins on Q1 BTC and gets re-validated on Q1 BTC is theatre.
Red flag
If the user's "strategy" started as a 5-variant sweep and now they want to deploy the winner — the result on the test window is overstated. Tell them to either run an out-of-sample check or accept they're deploying on optimistic numbers.
The 3-variant parameter sweep
When the user wants to find the right parameter (e.g. RSI threshold, ATR multiplier, lookback length), run 3 variants in one batch, not iterative single backtests. The shape of the 3-result table tells you what to do:
| Variant | Config | PnL% | Trades | Sharpe | Max DD |
|---|---|---|---|---|---|
| A | RSI < 25 | … | … | … | … |
| B | RSI < 30 | … | … | … | … |
| C | RSI < 35 | … | … | … | … |
Read the shape:
- All 3 profitable → pick the best Sharpe (not best PnL — PnL rewards luck on small samples). Parameter is robust; proceed to walk-forward / deployment with confidence.
- 1-2 profitable → pick the winner, but flag that the param is sensitive. Either (a) walk-forward to a 2nd pair, or (b) one tighter sweep around the winner.
- All 3 unprofitable / < 10 trades each → the idea doesn't work on this pair. Don't sweep again. Switch pair or strategy.
- Monotonic edge (PnL strictly improves A → B → C) → the best variant is at the edge of the grid. Run one more variant past it (e.g. RSI < 40). Don't run another full 3-grid; just extend by one.
Read the exit-reason mix
After the backtest completes, look at the breakdown of how trades ended. A healthy strategy ends through a mix of:
- Take-profit /
minimal_roi - Signal-based exit (
populate_exit_trend) - Trailing stop
- Time-based timeout (
custom_exit)
Each one tells a different story. Distortions diagnose specific bugs:
| Distortion | Meaning |
|---|---|
| 90% stoploss hits | Stop is too tight relative to the strategy's natural noise. Widen, or accept this strategy is in the wrong volatility regime for this pair. |
| 90% time-based timeouts | Exit signal does nothing. Either the exit conditions are too restrictive, or there's no real edge — you're just holding until the timer rings. |
| 100% take-profit hits | minimal_roi is the strategy. The exit signal isn't earning its keep — could be removed or tightened. |
| 50/50 stop vs profit | Healthy. Strategy is choosing actively in both directions. |
Show full SKILL.md (546 more words)Show less
Zero-trade diagnosis
Zero trades from a backtest means the entry condition never fired. Five common causes, in order of likelihood:
- Indicator threshold too strict (e.g.
RSI < 30rarely triggers on BTC 15m). startup_candle_countlarger than available data — the indicator stays NaN forever.- Pair has no data for the requested timerange.
- Wrong pair format for trading mode (
BTC/USDCfor futures will silently produce no fills). - Multi-condition entry that's effectively
false AND false— each condition individually rare, joined byANDrarer still.
The escalation rule (don't burn cycles)
- 1st zero-trade backtest: Diagnose. Widen the threshold, drop one of the AND conditions, or extend the window. Next attempt should be a 3-variant sweep, not a single guess — gives sensitivity in one shot.
- 2nd consecutive all-zero result: STOP. Don't run a third. Tell the user: "Two consecutive attempts returned zero trades. The strategy needs a fundamentally different approach." Suggest a different signal (mean-reversion vs momentum, BB vs RSI), a different timeframe, or a different pair.
- Never run 3+ all-zero attempts in a row on the same idea. Wastes compute and user trust.
Compute cost (estimate before submitting)
Backtest run time scales with candle count. Estimate before submitting so you can set the user's expectations:
candles ≈ (days × 24) / timeframe_hours × number_of_pairs| Candle count | Behavior |
|---|---|
| < 100K | Submit normally, poll every 10s. |
| 100K–500K | Warn user "may take a few minutes", use exponential polling. |
| > 500K | Warn user "could take 10+ minutes", longer poll intervals. |
Reference points:
- 1 pair × 15m × 90 days = 8.6K candles (fast)
- 3 pairs × 5m × 90 days = 78K candles (fast)
- 12 pairs × 1m × 90 days = 1.5M candles (slow — warn upfront)
Always allow the user to proceed. Just set expectations. Don't block on size.
Exponential polling cadence
When polling backtest_status on long runs:
- Polls 1-3: every 10s
- Polls 4-6: every 20s
- Polls 7-9: every 30s
- Polls 10+: every 60s
This prevents hitting the 20-step tool limit on million-candle backtests.
What headline numbers to trust (and not)
| Metric | Trust at | Notes |
|---|---|---|
| Total trades | Always look first. | Below 30 = ignore everything else. |
| Total profit % | Useful for ranking, weak for forecasting. | Large windows + small per-trade edge can produce big PnL from luck. |
| Win rate | OK above 50 trades. | A 60% WR on 8 trades is one good week, not an edge. |
| Sharpe ratio | Above 1.0 = good, above 2.0 = excellent. | But fragile under 50 trades; don't quote "Sharpe 2.0" off a 12-trade run. |
| Profit factor | Gross gains / gross losses. > 1.3 is the practical floor. | Penalizes hidden tail losses better than Sharpe. |
| Max drawdown | > 20% is risky for retail-sized accounts. | A 5% Sharpe-1 strategy with 30% DD is unrunnable for most users. |
| Avg holding | Sanity check — does it match the strategy's intent? | A "scalp" with 12h avg holding is misnamed; a "swing" with 5min holding likewise. |
Walk-forward (the honest validation)
Before recommending live deployment, run the strategy on out-of-sample data at least once:
- Out-of-sample period: take the most recent 30 days that weren't in your tuning window. Re-run unchanged. Numbers should be in the same ballpark — not better, not dramatically worse.
- Out-of-sample pair: run on a sibling pair (
ETHif you tuned onBTC). Allow ±30% degradation; anything beyond that means the parameters were pair-specific not regime-specific.
If both walk-forwards survive, you have a defensible recommendation. If either falls apart, you have a backtest, not a strategy.
© Superior-Trade, 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/backtesting of Superior-Trade/superior-skills.
Open the folder on GitHubat commit 9d41db5
Used in 1 other repository
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in Superior-Trade/superior-skills, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Backtesting 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 |
|---|---|---|---|---|---|---|
| Backtesting this skillSuperior-Trade/superior-skills | 214 | 1 repos | ~2.9k | Automated safety check: Pass | MIT | |
| 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 | |
| Fintoolsecond-state/fintool | 316 | 1 repos | ~5.9k | Automated safety check: Pass | None | |
| Polyclawchainstacklabs/polyclaw | 360 | 1 repos | ~2k | Automated safety check: Pass | Apache-2.0 |
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Questions about Backtesting
What does Backtesting do?
A skill your agent uses when running, interpreting, or designing backtests on Superior Trade — anything about backtest windows, trade-count thresholds, exit-reason mix, parameter sweeps…. Backtesting is an agent skill from Superior-Trade/superior-skills.".
When should I use Backtesting?
Backtesting fits situations like: designing backtests on Superior Trade — anything about backtest windows; trade-count thresholds; exit-reason mix; parameter sweeps.
How do I install Backtesting in Claude Code?
Run `npx skills add Superior-Trade/superior-skills --skill backtesting -a claude-code`. Or copy the skill folder (skills/backtesting in Superior-Trade/superior-skills) into .claude/skills/backtesting in your project. Claude Code loads it when a task matches its description.
How do I install Backtesting in Codex?
Run `npx skills add Superior-Trade/superior-skills --skill backtesting -a codex`. Or copy the skill folder (skills/backtesting in Superior-Trade/superior-skills) into .agents/skills/backtesting in your project. Codex loads it when a task matches its description.
Can I use Backtesting 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 Superior-Trade/superior-skills --skill backtesting -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/backtesting, .gemini/skills/backtesting, .github/skills/backtesting and .opencode/skills/backtesting in your project.
What does Backtesting need to run?
SKILL.md names no scripts, command-line tools or credentials: Backtesting is instructions for the agent only.
Does Backtesting 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 Backtesting 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 Backtesting use?
Backtesting is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Backtesting use?
About 2.9k tokens (SKILL.md is roughly 12k 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 Backtesting?
Skills that share tags, products or a category with Backtesting: Tushare Data (zillionare/zillionare, 319 stars), Tradingview MCP (atilaahmettaner/tradingview-mcp, 5k stars), Digital Oracle (komako-workshop/digital-oracle, 870 stars) and Fintool (second-state/fintool, 316 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Backtesting?
Superior-Trade (a GitHub organization) maintains it in Superior-Trade/superior-skills, which has 214 GitHub stars. The repository holds 31 skills in this directory. The repository was last updated on September 10, 2026.
Source: Superior-Trade/superior-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.