A tool for exploring how trading backtest results vary with settings such as time of day, days to expiration, option delta, and market conditions. A backtest evaluates a strategy against historical data.

Finding fields related to profit and loss, inspecting value distributions, testing filter thresholds, and suggesting market-based filters when the required trade and market data is available.

It reveals patterns in historical trades, helping explain strategy behavior and compare filters or thresholds, while past patterns may not continue.

optimize — Skill for Claude Code by davidromeo

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.

Any agent

npx skills add davidromeo/tradeblocks-skills --skill optimize

Clone the repo

git clone --depth 1 https://github.com/davidromeo/tradeblocks-skills

Made for: Claude Code.

Or install tradeblocks, the plugin that ships this one along with the rest of its 9 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/davidromeo/tradeblocks-skills/optimize/github.svg)](https://agentmods.dev/skills/davidromeo/tradeblocks-skills/optimize)

Your own site

<a href="https://agentmods.dev/skills/davidromeo/tradeblocks-skills/optimize"><img src="https://agentmods.dev/badge/skills/davidromeo/tradeblocks-skills/optimize/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/davidromeo/tradeblocks-skills/optimize"><img src="https://agentmods.dev/badge/skills/davidromeo/tradeblocks-skills/optimize.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 49 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 2,314 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

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.

Model	Per session	Once invoked
Fable 5.1	$0.00049	$0.02314
Opus 5	$0.00024	$0.01157
Sonnet 5	$0.00010	$0.00463
Haiku 4.5	$0.00005	$0.00231

Measured 8d ago against content hash 9dfd67cbef57, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

optimize 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 8d 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.

skills/optimize/SKILL.md · 251 lines

How it starts

The opening of the file, as written. The whole thing — 251 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Parameter Exploration

Explore trade data to understand how performance varies across different parameters.

What This Skill Does

Uses predictive field analysis, field statistics, filter curves, and market-based filter suggestions to answer questions like:

"Which fields correlate with P&L?"
"What does the VIX distribution look like for my trades?"
"Is there an S/L ratio threshold that improves results?"
"What market-based filters would have helped?"

Important: This skill helps surface patterns in historical data. Past patterns may not persist. See references/optimization.md for overfitting context.

Prerequisites

TradeBlocks MCP server running
Block with trade data loaded
Market data imported for market-based filter suggestions (daily OHLCV + VIX context)
Sufficient trade count for meaningful analysis (50+ trades for better signal)

Process

Step 1: Identify Exploration Goal

Ask what the user wants to explore:

Goal	Primary Tool
Find which fields predict P&L	`find_predictive_fields`
Understand a specific field's distribution	`get_field_statistics`
Test filter thresholds on a field	`filter_curve`
Get market-based filter suggestions	`suggest_filters`
Validate existing entry filters	`validate_entry_filters`

Ask: "What aspect of your strategy would you like to explore?"

Use list_blocks to identify the target block.

Step 2: Discover Predictive Fields

Run find_predictive_fields to rank all numeric fields by correlation with P&L.

Key parameters:

blockId: Block folder name
strategy: Optional filter to specific strategy
strategyName: Strategy profile name (auto-filters to that strategy's trades, adds profile context)
targetField: Field to correlate against (default: "pl")
minSamples: Minimum trades with valid values (default: 30)

Tool returns:

All numeric fields ranked by absolute correlation with P&L
Correlation direction (positive/negative)
Sample size per field
Fields skipped due to insufficient data

Read the full file on GitHub · 251 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

references/optimization.md 6.4 KB

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.

8d ago First seen · 251 lines · 49 tokens per session scan A 9dfd67cbef57

Subscribe to this mod's changes

optimize is a skill published in the GitHub repository davidromeo/tradeblocks-skills (2 stars, last pushed 5mo ago), licensed MIT. It adds 49 tokens to every session and 2,314 once invoked, about $0.0002 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.

Analytics and metrics Finance and fintech

sector-rotation

An analysis framework for comparing industries in the Chinese A-share stock market, using business conditions, price momentum, valuation, and money flows. It produces rankings and higher- or lower-allocation suggestions.

HKUDS/Vibe-Trading · 39 tokens

strategy-pivot-designer

Detect backtest iteration stagnation and generate structurally different strategy pivot proposals when parameter tuning reaches a local optimum.

tradermonty/claude-trading-skills · 28 tokens

twitter-reader

Read Twitter/X for financial research using opencli (read-only). Use this skill whenever the user wants to read their Twitter feed, search for financial tweets, view bookmarks, look up user profiles, or gather market sentiment from Twitter/X. Triggers include: "check my feed", "search Twitter for", "show my…

himself65/finance-skills · 161 tokens

optimize