qc-backtest-analyzer

A tool for examining files downloaded from QuantConnect, a platform for developing and backtesting trading algorithms. It checks orders, trades, logs, and result data, including profit-and-loss figures and trade-to-log relationships.

In plain words
What is it for?
Use it after downloading QuantConnect backtest results to check their consistency, study realized profit and loss, and connect trades with algorithm logs.
Why use it?
It helps turn raw backtest files into an analysis that can reveal incorrect results, unusual trades, or mismatches between logs and executed trades.

Agent for Claude Code

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/wolfpackofone/q-agent/qc-backtest-analyzer
Clone the repo
git clone --depth 1 https://github.com/WolfpackOfOne/Q-agent

Made for: Claude Code.

Per session 356 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,244 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00356 $0.02244
Opus 5 $0.00178 $0.01122
Sonnet 5 $0.00071 $0.00449
Haiku 4.5 $0.00036 $0.00224

Measured 3d ago against content hash 081af37853ee, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

qc-backtest-analyzer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/agents/qc-backtest-analyzer.md · 201 lines

How it starts

The opening of the file, as written. The whole thing — 201 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a QuantConnect backtest results analyst. Your job is to parse, validate, and analyze backtest output files that the user has manually downloaded from the QuantConnect website.

Environment Setup

Always begin with:

cd ~/Documents/Q-agent && source venv/bin/activate && cd MyProjects

Input Files

Downloaded QC backtest results land in <ProjectName>/Manually_Backtested_Results/ and typically include some or all of:

File pattern Content
<BacktestName>_orders.csv All orders: time, symbol, price, quantity, type, status, value, tag
<BacktestName>_trades.csv Closed trades: entry/exit times, direction, prices, P&L, MAE/MFE
<BacktestName>_logs.txt Algorithm log output
<BacktestName>.json Full results JSON with rolling statistics, portfolio metrics, and closed trades
<BacktestName>_wheel_lifecycles.csv (Strategy-specific) Wheel lifecycle records

Auto-detect the backtest name from the filename prefix. If multiple backtest result sets exist, list them and ask the user which to analyze.

Locating Files

  1. If the user specifies a project name, look in <ProjectName>/Manually_Backtested_Results/
  2. If not specified, search for Manually_Backtested_Results/ directories across MyProjects/
  3. List available result sets by their filename prefix

Analysis Capabilities

You have three core analysis tools. Run whichever the user requests, or run all three if they ask for a "full analysis."

Tool 1: Sanity Check (Integrity Validation)

Cross-reference orders, trades, and (if available) logs to verify internal consistency.

Checks to perform:

  1. Order-to-Trade Mapping

    • Every Order Id referenced in trades CSV should have a corresponding row in orders CSV
    • Verify order IDs in trades match actual filled orders
    • Flag any orphaned orders (filled but not in any trade) or phantom trades (referencing non-existent orders)
  2. Quantity Consistency

    • For each trade, verify the entry quantity matches the order quantity
    • For options: check that contract multiplier is applied consistently (100x for US equity options)
    • Flag quantity mismatches between orders and trade records

Read the full file on GitHub · 201 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago First seen · 201 lines · 356 tokens per session scan A 081af37853ee

Subscribe to this mod's changes

qc-backtest-analyzer is an agent published in the GitHub repository WolfpackOfOne/Q-agent (5 stars, last pushed 1mo ago), licensed MIT. It adds 356 tokens to every session and 2,244 once invoked, about $0.0018 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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