dc-analysis

dc-analysis is a skill for Claude Code from davidromeo/tradeblocks-skills. It costs 80 tokens per session (3,668 once invoked), scanned A, original, MIT.

A health-check process for double calendar trading strategies, which use option positions with different expiration dates. It examines performance, exits, market-volatility conditions, stop-loss settings, fading advantages, and fields used for prediction.

In plain words
What is it for?
Use it to evaluate or tune a double calendar backtest, review its strategy profile, study exit reasons, assess volatility-regime fit, and investigate changes in its trading edge.
Why use it?
It helps explain why a particular strategy is or is not working instead of judging results from a single backtest number. It also compares the strategy with market-volatility regimes and its configured rules.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the tradeblocks plugin — 9 skills shipped together

Good fit Use it to evaluate or tune a double calendar backtest, review its strategy profile, study exit reasons, assess volatility-regime fit, and investigate changes in its trading edge.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/davidromeo/tradeblocks-skills/dc-analysis
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 dc-analysis
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.

agentmods badge for dc-analysis

README.md
[![agentmods](https://agentmods.dev/badge/skills/davidromeo/tradeblocks-skills/dc-analysis/github.svg)](https://agentmods.dev/skills/davidromeo/tradeblocks-skills/dc-analysis)
Your own site
<a href="https://agentmods.dev/skills/davidromeo/tradeblocks-skills/dc-analysis"><img src="https://agentmods.dev/badge/skills/davidromeo/tradeblocks-skills/dc-analysis/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.

agentmods 80×15 button for dc-analysis

Your own site · 80×15
<a href="https://agentmods.dev/skills/davidromeo/tradeblocks-skills/dc-analysis"><img src="https://agentmods.dev/badge/skills/davidromeo/tradeblocks-skills/dc-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 80 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,668 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00080 $0.03668
Opus 5 $0.00040 $0.01834
Sonnet 5 $0.00016 $0.00734
Haiku 4.5 $0.00008 $0.00367

Measured 10d ago against content hash a79ddb71219e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

dc-analysis 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 10d 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/dc-analysis/SKILL.md · 310 lines

How it starts

The opening of the file, as written. The whole thing — 310 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Double Calendar Analysis

Comprehensive health check for double calendar strategies. Each DC responds differently to filters and exits depending on its DTE spread, delta selection, and underlying. This skill surfaces those differences.

Prerequisites

  • TradeBlocks MCP server running
  • Block with DC trade data loaded
  • Strategy profile recommended (will prompt to create if missing)
  • Market data (SPX daily + VIX context) for regime analysis

Process

Step 1: Select Block and Load Profile

  1. Ask which DC to analyze. Use list_blocks if needed.
  2. Check for a profile. Call get_strategy_profile with the block and strategy name.
    • If profile exists: load it and summarize the structure (DTE spread, deltas, entry/exit rules, underlying).
    • If no profile: ask the user for the OO settings (screenshots work) and create one via profile_strategy. Key fields needed:
      • Underlying, DTE spread (short/long), put/call deltas
      • Entry filters (day, time, S/L ratio min, VIX, RSI)
      • Exit rules (profit target, time exit, S/L ratio exit, delta exits)
      • Position sizing (allocation %)

Display the profile summary before continuing:

Structure: [underlying] [short DTE]/[long DTE] DC, [put delta]/[call delta] delta
Entry: [day], [time], [filters]
Exits: [list exit rules]
Sizing: [allocation]%

Step 2: Baseline Performance

Run get_statistics for the block.

Present the core metrics:

Metric Value Context
Win Rate >60% typical for DCs
Profit Factor >2.0 strong
Sharpe >3.0 strong for DCs
Max Drawdown <15% good
Avg Win / Avg Loss Payoff ratio
Trade Count <100 = thin data warning

Step 3: Exit Attribution

Run get_performance_charts with charts: ["exit_reason_breakdown"].

This is critical for DCs. Build a table:

Exit Type Count Avg P&L Total P&L Verdict
Time exit Money maker or money loser?
S/L ratio Primary stop or profit engine?
Delta exit (above) How much damage?
Delta exit (below) How much damage?
Profit target Capturing enough?
Expired Good or bad for this DC?

Read the full file on GitHub · 310 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.

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. 10d ago First seen · 310 lines · 80 tokens per session scan A a79ddb71219e

Subscribe to this mod's changes

dc-analysis is a skill published in the GitHub repository davidromeo/tradeblocks-skills (2 stars, last pushed 5mo ago), licensed MIT. It adds 80 tokens to every session and 3,668 once invoked, about $0.0004 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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