Trader Backtest
ruvnet/ruflo
Run a historical backtest using npx neural-trader with Rust/NAPI engine (8-19x faster) and walk-forward validation; Ed25519-sign the result for paper→live tamper evidence (ADR-126 Phase 4)
Runs a declarative strategy spec over OHLCV bars with the manifoldbt Rust engine, pairs the fill log into round trips, and emits the eight inputs the backtest-expert skill scores.
Install Manifoldbt Backtester
$ npx skills add tradermonty/claude-trading-skills --skill manifoldbt-backtester -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install tradermonty/claude-trading-skills manifoldbt-backtester --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/tradermonty/claude-trading-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/manifoldbt-backtester .claude/skills/manifoldbt-backtester && 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 "manifoldbt-backtester" agent skill from https://github.com/tradermonty/claude-trading-skills/tree/main/skills/manifoldbt-backtester into .claude/skills/manifoldbt-backtester/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "manifoldbt-backtester", 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/tradermonty/claude-trading-skills/tree/main/skills/manifoldbt-backtesterType 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 tradermonty/claude-trading-skills --skill manifoldbt-backtester -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install tradermonty/claude-trading-skills manifoldbt-backtester --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tradermonty/claude-trading-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/manifoldbt-backtester .agents/skills/manifoldbt-backtester && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "manifoldbt-backtester" agent skill from https://github.com/tradermonty/claude-trading-skills/tree/main/skills/manifoldbt-backtester into .agents/skills/manifoldbt-backtester/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "manifoldbt-backtester", 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 tradermonty/claude-trading-skills --skill manifoldbt-backtester -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install tradermonty/claude-trading-skills manifoldbt-backtester --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tradermonty/claude-trading-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/manifoldbt-backtester .cursor/skills/manifoldbt-backtester && 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 "manifoldbt-backtester" agent skill from https://github.com/tradermonty/claude-trading-skills/tree/main/skills/manifoldbt-backtester into .cursor/skills/manifoldbt-backtester/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "manifoldbt-backtester", 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/tradermonty/claude-trading-skills.git --path skills/manifoldbt-backtester--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 tradermonty/claude-trading-skills --skill manifoldbt-backtester -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install tradermonty/claude-trading-skills manifoldbt-backtester --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tradermonty/claude-trading-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/manifoldbt-backtester .gemini/skills/manifoldbt-backtester && 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 "manifoldbt-backtester" agent skill from https://github.com/tradermonty/claude-trading-skills/tree/main/skills/manifoldbt-backtester into .gemini/skills/manifoldbt-backtester/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "manifoldbt-backtester", 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 tradermonty/claude-trading-skills manifoldbt-backtesterInstalls 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 tradermonty/claude-trading-skills --skill manifoldbt-backtester -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/tradermonty/claude-trading-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/manifoldbt-backtester .github/skills/manifoldbt-backtester && 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 "manifoldbt-backtester" agent skill from https://github.com/tradermonty/claude-trading-skills/tree/main/skills/manifoldbt-backtester into .github/skills/manifoldbt-backtester/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "manifoldbt-backtester", 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 tradermonty/claude-trading-skills --skill manifoldbt-backtester -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install tradermonty/claude-trading-skills manifoldbt-backtester --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tradermonty/claude-trading-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/manifoldbt-backtester .opencode/skills/manifoldbt-backtester && 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 "manifoldbt-backtester" agent skill from https://github.com/tradermonty/claude-trading-skills/tree/main/skills/manifoldbt-backtester into .opencode/skills/manifoldbt-backtester/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "manifoldbt-backtester", 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
manifoldbt-backtester- GitHub stars
- 3k
- Token cost
- ~1.6k tokens
- SKILL.md length
- 785 words
- Files
- 13 (incl. scripts, references)
- Skills in repo
- 74
- Repo updated
- First seen
- Licence
- MIT
At a glance
Runs a declarative strategy spec over OHLCV bars with the manifoldbt Rust engine, pairs the fill log into round trips, and emits the eight inputs the backtest-expert skill scores.
- Works in 4 steps: Write the strategy spec → Run it → Read the warnings before the numbers → …
- The user wants to execute a backtest
- SKILL.md covers Purpose, When to Use This Skill, Prerequisites and Workflow, plus 4 more sections
- Runs Python scripts from its folder; calls python3 and pip
What it does
Manifoldbt Backtester is an agent skill from tradermonty/claude-trading-skills. Runs a declarative strategy spec over OHLCV bars with the manifoldbt Rust engine, pairs the fill log into round trips, and emits the eight inputs the backtest-expert skill scores. Use when the user wants to execute a backtest, measure a rule they have described, obtain win rate / average win / average loss / max drawdown from real bars, or feed backtest-expert with measured numbers instead of estimates.
Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 15 other files, including scripts and reference files (for example `references/metric_bridge.md`, `references/strategy_spec.md` and `scripts/bridge.py`).
It sits in Business, Finance & HR, covering Trading and backtesting. It works with Rust. The repository describes itself as: Claude Code skills for equity investors and traders — market analysis, technical charting, economic calendars, screeners, and trading strategy development. The licence is MIT.
When your agent uses it
- The user wants to execute a backtest
- Measure a rule they have described
- Obtain win rate / average win / average loss / max drawdown from real bars
- Feed backtest-expert with measured numbers instead of estimates
Example prompts
- “/manifoldbt-backtester”
Requirements
- Python 3
Workflow steps
4 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit c8d58f0. 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
Ships 9 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python3pip
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use pip, which can reach the network depending on how they are called.
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
Manifoldbt Backtester loads about 1.6k tokens when it runs, and up to ~3.6k if it reads all its reference files. Until then it costs about 107 tokens; SKILL.md has 785 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); the scripts in this folder are not scanned.
SKILL.md
The full file from tradermonty/claude-trading-skills at commit c8d58f0, republished under its MIT licence (© tradermonty). 785 words, ~1,559 tokens.
Download SKILL.mdSave it as
.claude/skills/manifoldbt-backtester/SKILL.md (or your agent's skills folder). This skill also uses 12 other files; get the full folder from GitHub.- name
- manifoldbt-backtester
- description
- Runs a declarative strategy spec over OHLCV bars with the manifoldbt Rust engine, pairs the fill log into round trips, and emits the eight inputs the backtest-expert skill scores. Use when the user wants to execute a backtest, measure a rule they have described, obtain win rate / average win / average loss / max drawdown from real bars, or feed backtest-expert with measured numbers instead of estimates.
manifoldbt Backtester Skill
Purpose
Execute what backtest-expert teaches. That skill grades a backtest on five
dimensions, and its prerequisites say "metrics are user-provided": it scores
numbers it never produces. This skill produces them. It runs a strategy over
real bars and returns the eight inputs its evaluator asks for.
The two chain in one direction: spec, run, evaluate.
When to Use This Skill
- A user describes a rule and wants it measured
backtest-expertis about to run and the numbers do not exist yet- A win rate, average winner, average loser or drawdown must come from bars
- A strategy's parameter count must be established for scoring
Leave the verdict to backtest-expert. It owns the thresholds and the red
flags, and this skill does not duplicate them.
Prerequisites
- Python 3.9+
pip install manifoldbt(Apache 2.0 with Commons Clause; the free tier covers everything this skill does)- OHLCV bars as CSV or Parquet with columns
timestamp, open, high, low, close, volume - No API key required
Workflow
1. Write the strategy spec
A spec names indicators and one entry condition. Keep it to the smallest rule that states the hypothesis. Every added knob makes an in-sample fit easier to reach by accident, and the evaluator penalises the count.
{
"name": "sma_cross_costed",
"indicators": {
"fast": { "type": "sma", "period": 20 },
"slow": { "type": "sma", "period": 60 }
},
"entry": { "left": "fast", "op": ">", "right": "slow" },
"size": 1.0,
"stop_loss_pct": 1.5,
"fees_bps": 5.0,
"slippage_bps": 2.0
}Field reference: references/strategy_spec.md.
Set fees_bps and slippage_bps to realistic values before you read any
result. A frictionless run scores 0 on execution realism, and over short holding
periods costs decide whether an edge survives.
2. Run it
python3 scripts/run_backtest.py \
--spec strategy.json \
--data bars.csv \
--symbol BTCUSDT \
--json-out result.jsonThe script validates the spec before it touches the data, so you see a spec mistake in a second instead of after a long load.
3. Read the warnings before the numbers
The run prints warnings that change how you should read the result: a sample under 30 trades, a span under a year, no friction modelled, or a gap between the engine's win rate and the paired one. Each one is a reason to fix the setup and run again.
Three conditions stop the handoff instead of producing a score: no completed round trips, missing or non-finite maximum drawdown, and scratch trades. The evaluator has no scratch input, so passing a population that contains them would make its derived expectancy disagree with the completed trades.
4. Hand off to backtest-expert
The run ends with a command you can paste. Run it, or invoke the
backtest-expert skill with the same figures:
python3 skills/backtest-expert/scripts/evaluate_backtest.py \
--total-trades 3854 --win-rate 20.24 \
--avg-win-pct 0.2917 --avg-loss-pct 0.2342 \
--max-drawdown-pct 99.2893 --years-tested 0 \
--num-parameters 3 --slippage-testedShow full SKILL.md (392 more words)Show less
Four conversions that fail without an error
Between an engine's output and the evaluator's inputs sit four conversions. Each one yields a plausible number and scores the strategy wrongly. None of them raises.
A fill is one execution, a round trip is two. The raw trade count runs at about twice the number of round trips. Feed fills to the sample-size dimension and you double the apparent sample, which can lift a thin backtest over a threshold it should not clear.
Buy and sell alternate only in the simplest case. That holds for a single-symbol long-only strategy that never scales a position. Shorting breaks it, because a sell can open. Scaling breaks it, because one exit answers several entries. A universe breaks it, because fills interleave. This skill tracks position per symbol and closes a trip when it crosses back through flat. Entry and exit quantities and cash values accumulate across that whole lifecycle; their weighted-average prices are display values, while PnL comes from the cash flows themselves.
Costs decide small trades. At 7 bps a side, a trade that gains 0.1% on price
loses money. Expectancy comes from the win rate and the average winner together,
so a gross win rate beside net averages misstates the edge. Percentages here are
net of fees, and gross_return_pct sits alongside for inspection.
The engine signs drawdown negative. The evaluator wants a positive magnitude. Pass the raw value and a 38% fall scores as a flawless run.
Scope
Supported: sma, ema, rsi over any OHLC column; one entry condition using
>, <, >=, <= against another indicator, a price column or a number;
optional stop-loss and take-profit; fees and slippage in basis points;
long-only.
Refused: multi-condition entries, shorting, multi-asset universes, and indicators outside the three above. The engine does all of these. This skill covers the shapes a one-sentence hypothesis produces, and rejects the rest instead of half-handling it.
Reference Files
references/strategy_spec.mdcovers every spec field, its default, and what validation refusesreferences/metric_bridge.mdcovers the eight inputs, how each is derived, and the trap in each conversion
Scripts
scripts/run_backtest.pyruns a spec against barsscripts/spec.pyvalidates a spec and counts its parametersscripts/round_trips.pypairs fills into round trips with net returnsscripts/bridge.pyassembles the evaluator's eight inputs
spec.py, round_trips.py and bridge.py carry no dependencies and import
without the engine, so you can test the logic without running a backtest.
© tradermonty, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 12 other files (scripts, references) in skills/manifoldbt-backtester of tradermonty/claude-trading-skills.
- SKILL.md
- references/metric_bridge.md
- references/strategy_spec.md
- requirements.txt
- scripts/bridge.py
- scripts/round_trips.py
- scripts/run_backtest.py
- scripts/spec.py
- scripts/tests/conftest.py
- scripts/tests/test_bridge.py
- scripts/tests/test_round_trips.py
- scripts/tests/test_run_backtest.py
- scripts/tests/test_spec.py
Open the folder on GitHubat commit c8d58f0
Compare with similar skills
Manifoldbt Backtester 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 |
|---|---|---|---|---|---|---|
| Manifoldbt Backtester this skilltradermonty/claude-trading-skills | 3k | — | ~1.6k | Automated safety check: Pass | MIT | |
| Trader Backtestruvnet/ruflo | 74k | — | ~1.4k | Automated safety check: Notes | MIT | |
| lo2cin4bt Backtesting Assistantlo2cin4/lo2cin4bt | 289 | — | ~2.6k | Automated safety check: Pass | Custom licence | |
| lo2cin4bt Backtestinglo2cin4/lo2cin4bt | 289 | — | ~1.8k | Automated safety check: Pass | Custom licence | |
| Tushare Datazillionare/zillionare | 322 | 2 repos | ~2.3k | Automated safety check: Pass | None | |
| Tradingview MCPatilaahmettaner/tradingview-mcp | 5k | — | ~1.3k | Automated safety check: Pass | MIT |
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Questions about Manifoldbt Backtester
What does Manifoldbt Backtester do?
Runs a declarative strategy spec over OHLCV bars with the manifoldbt Rust engine, pairs the fill log into round trips, and emits the eight inputs the backtest-expert skill scores. Manifoldbt Backtester is an agent skill from tradermonty/claude-trading-skills. Runs a declarative strategy spec over OHLCV bars with the manifoldbt Rust engine, pairs the fill log into round trips, and emits the eight inputs the backtest-expert skill scores.
When should I use Manifoldbt Backtester?
Manifoldbt Backtester fits situations like: the user wants to execute a backtest; measure a rule they have described; obtain win rate / average win / average loss / max drawdown from real bars; feed backtest-expert with measured numbers instead of estimates.
How do I install Manifoldbt Backtester in Claude Code?
Run `npx skills add tradermonty/claude-trading-skills --skill manifoldbt-backtester -a claude-code`. Or copy the skill folder (skills/manifoldbt-backtester in tradermonty/claude-trading-skills) into .claude/skills/manifoldbt-backtester in your project. Claude Code loads it when a task matches its description.
How do I install Manifoldbt Backtester in Codex?
Run `npx skills add tradermonty/claude-trading-skills --skill manifoldbt-backtester -a codex`. Or copy the skill folder (skills/manifoldbt-backtester in tradermonty/claude-trading-skills) into .agents/skills/manifoldbt-backtester in your project. Codex loads it when a task matches its description.
Can I use Manifoldbt Backtester 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 tradermonty/claude-trading-skills --skill manifoldbt-backtester -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/manifoldbt-backtester, .gemini/skills/manifoldbt-backtester, .github/skills/manifoldbt-backtester and .opencode/skills/manifoldbt-backtester in your project.
What does Manifoldbt Backtester need to run?
Going by SKILL.md and its folder, Manifoldbt Backtester needs Python for the scripts in its folder and the command-line tools its instructions call (python3 and pip). Our summary lists: Python 3.
Does Manifoldbt Backtester access the network?
SKILL.md contains no URLs. Its commands use pip, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is Manifoldbt Backtester 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Manifoldbt Backtester use?
Manifoldbt Backtester 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 Manifoldbt Backtester use?
About 1.6k tokens (SKILL.md is roughly 6.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.1k tokens, read only when the agent opens those files.
What are the alternatives to Manifoldbt Backtester?
Skills that share tags, products or a category with Manifoldbt Backtester: Trader Backtest (ruvnet/ruflo, 74k stars), lo2cin4bt Backtesting Assistant (lo2cin4/lo2cin4bt, 289 stars), lo2cin4bt Backtesting (lo2cin4/lo2cin4bt, 289 stars) and Tushare Data (zillionare/zillionare, 322 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Manifoldbt Backtester?
tradermonty (a GitHub user) maintains it in tradermonty/claude-trading-skills, which has 2,982 GitHub stars. The repository holds 74 skills in this directory. The repository was last updated on October 11, 2026.
Source: tradermonty/claude-trading-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.