Agent skill

Backtest Explain

by YicunAI in YicunAI/Pnlclaw-community

Analyzes backtest results in plain language, connecting metrics to what they mean for the strategy

AGPL-3.0Auto-check passedBusiness, Finance & HR

Install Backtest Explain

skills CLI
$ npx skills add YicunAI/Pnlclaw-community --skill backtest-explain -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install YicunAI/Pnlclaw-community backtest-explain --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/YicunAI/Pnlclaw-community.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/backtest-explain .claude/skills/backtest-explain && rm -rf skills-src

Use ~/.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/

Facts

Skill name
backtest-explain
GitHub stars
197
Token cost
~378 tokens
SKILL.md length
170 words
Files
1
Skills in repo
8
Repo updated
First seen
Licence
AGPL-3.0

At a glance

Analyzes backtest results in plain language, connecting metrics to what they mean for the strategy

  • Works in 4 steps: Obtain the backtest run id the user… → Call backtest_result to load metrics,… → Call explain_pnl when the discussion… → …
  • Tasks that involve Trading and backtesting
  • SKILL.md covers Description, Triggers, Steps and Tools Used, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Backtest Explain is an agent skill from YicunAI/Pnlclaw-community. Analyzes backtest results in plain language, connecting metrics to what they mean for the strategy

Its SKILL.md is about 380 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 and Plain language and style rules. The repository describes itself as: PnLClaw — local-first crypto and prediction market quant engine. The licence is AGPL-3.0.

When your agent uses it

  • Tasks that involve Trading and backtesting
  • Tasks that involve Plain language and style rules

Example prompts

  • “Use the backtest-explain skill to analyz backtest results in plain language, connecting metrics to what they mean for the strategy”
  • “/backtest-explain”

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Obtain the backtest run id the user cares about (or the latest completed run).
  2. Call backtest_result to load metrics, trade count, and equity context.
  3. Call explain_pnl when the discussion ties to PnL decomposition on paper accounts; otherwise focus on backtest metrics from step 2.
  4. Explain return, drawdown, Sharpe, win rate, and trade count in plain language with caveats.

What it can do on your machine

Read from SKILL.md and the folder at commit 933014f. 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

Backtest Explain loads about 378 tokens when it runs. Until then it costs about 29 tokens; SKILL.md has 170 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~29
When it runs · the whole SKILL.md, loaded when a task matches
~378

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 YicunAI/Pnlclaw-community at commit 933014f, republished under its AGPL-3.0 licence (© YicunAI). 170 words, ~378 tokens.

Download SKILL.mdSave it as .claude/skills/backtest-explain/SKILL.md (or your agent's skills folder).
name
backtest-explain
description
Analyzes backtest results in plain language, connecting metrics to what they mean for the strategy
version
0.1.0
tags
backtest, explanation, metrics
user_invocable
true
model_invocable
true
requires_tools
backtest_result, explain_pnl

Backtest Explanation

Description

Analyzes backtest results in plain language, connecting metrics to what they mean for the strategy.

Triggers

  • "Explain my backtest results"
  • "What does this backtest tell me?"
  • "Explain this backtest"
  • "帮我解释这个回测"

Steps

  1. Obtain the backtest run id the user cares about (or the latest completed run).
  2. Call backtest_result to load metrics, trade count, and equity context.
  3. Call explain_pnl when the discussion ties to PnL decomposition on paper accounts; otherwise focus on backtest metrics from step 2.
  4. Explain return, drawdown, Sharpe, win rate, and trade count in plain language with caveats.

Tools Used

  • backtest_result: Retrieve stored backtest output including metrics and identifiers.
  • explain_pnl: Relate profit/loss composition when comparing live paper performance to backtest expectations.

Example Interaction

User: I ran a backtest yesterday—can you explain if the drawdown is acceptable? Agent: I will pull the result with backtest_result, then walk through max drawdown, win rate, and trade count in context of your strategy goals.

Notes

  • Distinguish backtest metrics from live/paper PnL unless the user links them.

© YicunAI, AGPL-3.0. 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/backtest-explain of YicunAI/Pnlclaw-community.

Open the folder on GitHubat commit 933014f

Compare with similar skills

Backtest Explain 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.

Backtest Explain compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Backtest Explain this skillYicunAI/Pnlclaw-community197—~378Automated safety check: PassAGPL-3.0
ZoneinLeoYeAI/openclaw-master-skills2.2k—~5.1kAutomated safety check: PassMIT
Quant Blog Writingzillionare/zillionare319—~895Automated safety check: PassNone
Biz Corporate Governanceasgard-ai-platform/skills241—~2.5kAutomated safety check: PassMIT
Tushare Datazillionare/zillionare3192 repos~2.3kAutomated safety check: PassNone
Tradingview MCPatilaahmettaner/tradingview-mcp5k—~1.3kAutomated safety check: PassMIT

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Questions about Backtest Explain

What does Backtest Explain do?

Analyzes backtest results in plain language, connecting metrics to what they mean for the strategy. Backtest Explain is an agent skill from YicunAI/Pnlclaw-community.

When should I use Backtest Explain?

Backtest Explain fits situations like: tasks that involve Trading and backtesting; tasks that involve Plain language and style rules.

How do I install Backtest Explain in Claude Code?

Run `npx skills add YicunAI/Pnlclaw-community --skill backtest-explain -a claude-code`. Or copy the skill folder (skills/backtest-explain in YicunAI/Pnlclaw-community) into .claude/skills/backtest-explain in your project. Claude Code loads it when a task matches its description.

How do I install Backtest Explain in Codex?

Run `npx skills add YicunAI/Pnlclaw-community --skill backtest-explain -a codex`. Or copy the skill folder (skills/backtest-explain in YicunAI/Pnlclaw-community) into .agents/skills/backtest-explain in your project. Codex loads it when a task matches its description.

Can I use Backtest Explain 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 YicunAI/Pnlclaw-community --skill backtest-explain -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/backtest-explain, .gemini/skills/backtest-explain, .github/skills/backtest-explain and .opencode/skills/backtest-explain in your project.

What does Backtest Explain need to run?

SKILL.md names no scripts, command-line tools or credentials: Backtest Explain is instructions for the agent only.

Does Backtest Explain 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 Backtest Explain 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 Backtest Explain use?

Backtest Explain is published under the AGPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Backtest Explain use?

About 378 tokens (SKILL.md is roughly 1.5k 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 Backtest Explain?

Skills that share tags, products or a category with Backtest Explain: Zonein (LeoYeAI/openclaw-master-skills, 2.2k stars), Quant Blog Writing (zillionare/zillionare, 319 stars), Biz Corporate Governance (asgard-ai-platform/skills, 241 stars) and Tushare Data (zillionare/zillionare, 319 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Backtest Explain?

YicunAI (a GitHub user) maintains it in YicunAI/Pnlclaw-community, which has 197 GitHub stars. The repository holds 8 skills in this directory. The repository was last updated on April 8, 2026.

Source: YicunAI/Pnlclaw-community on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.