ftd-detector

ftd-detector is a skill for Claude Code from mphinance/alpha-skills. It costs 110 tokens per session (1,413 once invoked), scanned A, a copy of ftd-detector, MIT.

A market-bottom monitor that looks for Follow-Through Days, a trading signal used in William O'Neil's method to support a possible recovery after a market decline. It tracks the S&P 500 and Nasdaq through rally and post-signal states.

In plain words
What is it for?
Use it after a correction to assess whether a market rebound has met the method's Follow-Through Day conditions. It produces a signal quality score and guidance about re-entering or increasing market exposure.
Why use it?
It gives a structured way to distinguish an early rally attempt from a rally with stronger confirmation. This can reduce reliance on a single day's price move when considering a return to the market.

Skill for Claude Code

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

Part of the quant-skills plugin — 60 skills shipped together

Good fit Use it after a correction to assess whether a market rebound has met the method's Follow-Through Day conditions. It produces a signal quality score and guidance about re-entering or increasing market exposure.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/mphinance/alpha-skills/ftd-detector
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 mphinance/alpha-skills --skill ftd-detector
Clone the repo
git clone --depth 1 https://github.com/mphinance/alpha-skills

Made for: Claude Code.

Or install quant-skills, the plugin that ships this one along with the rest of its 60 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 ftd-detector

README.md
[![agentmods](https://agentmods.dev/badge/skills/mphinance/alpha-skills/ftd-detector/github.svg)](https://agentmods.dev/skills/mphinance/alpha-skills/ftd-detector)
Your own site
<a href="https://agentmods.dev/skills/mphinance/alpha-skills/ftd-detector"><img src="https://agentmods.dev/badge/skills/mphinance/alpha-skills/ftd-detector/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 ftd-detector

Your own site · 80×15
<a href="https://agentmods.dev/skills/mphinance/alpha-skills/ftd-detector"><img src="https://agentmods.dev/badge/skills/mphinance/alpha-skills/ftd-detector.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 110 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,413 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 100% copy Near-identical to another mod 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 $0.00110 $0.01413
Opus 5.5 $0.00044 $0.00565
Sonnet 5.5 $0.00022 $0.00283
Haiku 4.5 $0.00011 $0.00141

Measured 1mo ago against content hash 285a8332ee88, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ftd-detector 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 1mo ago.

The scan reads SKILL.md. This mod also ships 10 executable files (scripts/fmp_client.py, scripts/ftd_detector.py, scripts/post_ftd_monitor.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Origin

This is a copy

100% identical to ftd-detector — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

plugins/quant-skills/skills/ftd-detector/SKILL.md · 150 lines

How it starts

The opening of the file, as written. The whole thing — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.

FTD Detector Skill

Purpose

Detect Follow-Through Day (FTD) signals that confirm a market bottom, using William O'Neil's proven methodology. Generates a quality score (0-100) with exposure guidance for re-entering the market after corrections.

Complementary to Market Top Detector:

  • Market Top Detector = defensive (detects distribution, rotation, deterioration)
  • FTD Detector = offensive (detects rally attempts, bottom confirmation)

When to Use This Skill

English:

  • User asks "Is the market bottoming?" or "Is it safe to buy again?"
  • User observes a market correction (3%+ decline) and wants re-entry timing
  • User asks about Follow-Through Days or rally attempts
  • User wants to assess if a recent bounce is sustainable
  • User asks about increasing equity exposure after a correction
  • Market Top Detector shows elevated risk and user wants bottom signals

Japanese:

  • 「底打ちした?」「買い戻して良い?」
  • 調整局面(3%以上の下落)からのエントリータイミング
  • フォロースルーデーやラリーアテンプトについて
  • 直近の反発が持続可能か評価したい
  • 調整後のエクスポージャー拡大の判断
  • Market Top Detectorが高リスク表示の後の底打ちシグナル確認

Difference from Market Top Detector

Aspect FTD Detector Market Top Detector
Focus Bottom confirmation (offensive) Top detection (defensive)
Trigger Market correction (3%+ decline) Market at/near highs
Signal Rally attempt → FTD → Re-entry Distribution → Deterioration → Exit
Score 0-100 FTD quality 0-100 top probability
Action When to increase exposure When to reduce exposure

Execution Workflow

Phase 1: Execute Python Script

Run the FTD detector script:

python3 skills/ftd-detector/scripts/ftd_detector.py --api-key $FMP_API_KEY

The script will:

  1. Fetch S&P 500 and QQQ historical data (60+ trading days) from FMP API
  2. Fetch current quotes for both indices
  3. Run dual-index state machine (correction → rally → FTD detection)
  4. Assess post-FTD health (distribution days, invalidation, power trend)
  5. Calculate quality score (0-100)
  6. Generate JSON and Markdown reports

Read the full file on GitHub · 150 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. 1mo ago First seen · 150 lines · 110 tokens per session scan A 285a8332ee88

Subscribe to this mod's changes

ftd-detector is a skill published in the GitHub repository mphinance/alpha-skills (28 stars, last pushed 10d ago), licensed MIT. It adds 110 tokens to every session and 1,413 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to ftd-detector, differing in 2 lines, and is treated as a copy.

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