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Contrarian Setup Gate

CommunityPopular
tradermonty
contrarian-setup-gate

Synthesize the three Jason Shapiro contrarian-pipeline verdicts (COT crowding, news-reaction failure, weekly price-action confirmation) into one actionable setup_status via a fail-closed precedence state machine. Pure, offline synthesis -- no network, no API keys, no computation beyond validation and precedence.

Overview

Publishertradermonty
Repositoryclaude-trading-skills
Skill namecontrarian-setup-gate
Stars
2.8K
Forks
647
Bundled files
7
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 7 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by tradermonty on GitHub. Read the source before you install it.

Installation

Install the Contrarian Setup Gate AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/tradermonty/claude-trading-skills.git /tmp/claude-trading-skills
mkdir -p .claude/skills
cp -r /tmp/claude-trading-skills/skills/contrarian-setup-gate .claude/skills/contrarian-setup-gate
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Contrarian Setup Gate in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Contrarian Setup Gate on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Contrarian Setup Gate is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Contrarian Setup Gate

Overview

Synthesize the outputs of Jason Shapiro's 3-step contrarian process into one actionable state. cot-contrarian-detector (step 1) flags crowded positioning, news-reaction-failure-analyzer (step 2) tests whether the market failed to react to news favorable to the crowd, and technical-analyst's contrarian-confirmation mode (step 3) confirms weekly price-action evidence of a reversal. This gate reads those three report JSONs and applies an explicit, exhaustively-tested precedence rule set to produce one setup_status, with a fail-closed reason attached to every input that could not be confirmed.

The gate does no fetching, no API calls, and no computation beyond validating and combining the three inputs it is given. It is the pipeline's synthesis center, not a data source.

When to Use

  • After running cot-contrarian-detector (always required -- this is the pipeline's entry point)
  • Mid-pipeline, with only the detector report, to see the CROWDED state and what steps remain
  • After running news-reaction-failure-analyzer, to see whether the setup advances to WATCHING_PRICE or is REJECTED
  • After running technical-analyst's contrarian-confirmation mode, to see whether the setup reaches READY_FOR_PLAN
  • Before handing a symbol's direction and stop level to a position-sizing skill

Prerequisites

  • Python 3.9+
  • No API keys -- this skill is fully offline
  • A cot-contrarian-detector JSON report for the symbol under evaluation (required)
  • Optionally, a news-reaction-failure-analyzer JSON report for the same symbol (step 2)
  • Optionally, a technical-analyst contrarian-confirmation JSON report for the same symbol (step 3)

Workflow

Step 1: Run the Gate

bash
python3 skills/contrarian-setup-gate/scripts/run_contrarian_setup_gate.py \
  --symbol B6 \
  --detector-json reports/cot_crowding_2026-07-12.json \
  --news-json reports/nrf_B6_2026-07-12.json \
  --price-action-json reports/ta_confirmation_B6_2026-07-12.json \
  --as-of 2026-07-15 \
  --output-dir reports/

--symbol and --detector-json are required; --news-json and --price-action-json are optional -- omit either to see the state at that pipeline stage. --as-of is required (no implicit "today"): staleness is always evaluated against an explicit reference date so reruns are deterministic.

Exit behavior is intentionally asymmetric: a missing or malformed --as-of (or any other CLI usage error) is an operator config mistake, so the CLI exits 2 with usage text and writes no report. A problem with one of the three untrusted report files -- unreadable, malformed, stale, inconsistent -- is always handled fail-closed instead: the CLI exits 0 and writes a report naming the reason, exactly like every other skill in this pipeline.

Step 2: Read the Setup Status

StatusMeaningNext Step
READY_FOR_PLANAll three steps confirmed; direction, entry_trigger, and invalidation_level are populatedHand direction and invalidation_level to a position-sizing skill
WATCHING_PRICECrowding + news confirmed; price action still pendingRun technical-analyst's contrarian-confirmation mode
CROWDEDCrowding confirmed; news and/or price still pendingRun news-reaction-failure-analyzer
REJECTEDCrowding is NOT_CONFIRMED (classification NEUTRAL), or news/price came back NOT_CONFIRMEDStop -- do not run further steps for this symbol/direction
INSUFFICIENT_EVIDENCEA required input is missing, unreadable, stale, inconsistent, or could not itself reach a verdictStop -- fix or regenerate the named input before rerunning

missing_confirmations lists every step still blocking, with its state and reason. warnings never change the status -- they flag audit-worthy conditions such as a MEDIUM-confidence confirming signal or a near-stale input.

Step 3: Act on READY_FOR_PLAN Only

At READY_FOR_PLAN, direction (SHORT/LONG, the fade side of the crowd), entry_trigger (a factual echo of the confirming weekly signal), and invalidation_level (the stop reference from the price-action report) are populated. gate_confidence is the weaker of the news and price-action confidences (HIGH/MEDIUM/LOW -- LOW is a token both upstream skills document as reserved but never actually emit; the gate accepts it and ranks it weakest rather than rejecting it as unknown). Position sizing is the next pipeline stage (not yet built as of this skill's release -- see the roadmap in the repository's workflow docs); this gate never places or recommends an order.

Precedence (Summary)

Each step is evaluated in strict pipeline order -- crowding, then news, then price-action -- and each step fully settles before the next step's file is even consulted. An earlier step's definitive verdict is never softened by a later step's problem.

  1. Crowding is evaluated first and exclusively: INVALID/INSUFFICIENT crowding is always INSUFFICIENT_EVIDENCE; a NOT_CONFIRMED (NEUTRAL) classification is always REJECTED, regardless of any downstream file's state or corruption.
  2. With crowding CONFIRMED, news is evaluated next, on its own: INVALID (unreadable, malformed, stale, symbol mismatch, direction mismatch, unsupported schema) forces INSUFFICIENT_EVIDENCE; NOT_CONFIRMED forces REJECTED; INSUFFICIENT forces INSUFFICIENT_EVIDENCE -- in every one of these cases, price-action is never even inspected for the decision.
  3. Once news is CONFIRMED (or PENDING, for out-of-order use), price-action is evaluated last, with the same four-way settlement. Running price-action before news (out-of-order pipeline use) caps the status at CROWDED with a warning -- a NOT_CONFIRMED price-action verdict still REJECTs even out of order, since price-action is still fully evaluated in that branch.
  4. Crowding confirmed, both downstream steps pending -> CROWDED.
  5. Crowding + news confirmed, price-action pending -> WATCHING_PRICE.
  6. All three confirmed -> READY_FOR_PLAN.

See references/gate-decision-table.md for the full decision table (every reachable {crowding} x {news} x {price-action} state combination), the reason-token glossary, and worked examples.

Output Contract

The script writes contrarian_setup_gate_<SYMBOL>_<as-of>.json and .md to --output-dir:

yaml
symbol: B6
setup_status: READY_FOR_PLAN | WATCHING_PRICE | CROWDED | REJECTED | INSUFFICIENT_EVIDENCE
direction: SHORT | LONG | null
gate_confidence: HIGH | MEDIUM | LOW | null
entry_trigger: string | null
invalidation_level: number | null
missing_confirmations: [{step, state, reason}, ...]
warnings: [string, ...]
inputs:
  crowding: {state, classification, data_date, age_days, report_path}
  news_failure: {state, verdict, confidence, verdict_reason, as_of, age_days, report_path}
  price_action: {state, verdict, confidence, verdict_reason, stop_reference, as_of, age_days, report_path}
run_context: {symbol, as_of, max_detector_age_days, max_report_age_days, schema_version, skill}

Every input's state is one of CONFIRMED, NOT_CONFIRMED, INSUFFICIENT, PENDING (report not provided), or INVALID (a report was provided but is unusable -- unreadable, malformed, stale, or inconsistent with the other inputs; always carries a named reason).

Guardrails

  1. Never places or recommends orders. READY_FOR_PLAN is the furthest state this skill reaches. Order entry and position sizing are separate, downstream decisions.
  2. INSUFFICIENT_EVIDENCE and REJECTED never advance. No warning, confidence, or partial input ever pushes the status past what the precedence rules allow.
  3. Fail closed on every input, always. An unreadable, malformed, stale, symbol-mismatched, or unknown-enum report is never treated as a pass -- it is named and blocks or downgrades the status. This includes the price-action report's verdict_reason (allowlisted against technical-analyst's actual confirming-signal vocabulary, not merely type-checked) and its stop_reference (must be a finite, positive number -- never non-finite, zero, negative, or a boolean). Before any of the three report files reaches this validation, the CLI also rejects a file outright (reason <input>_non_finite) if it contains a non-finite number (Infinity/-Infinity/NaN, including an ordinary-looking number like 1e309 that overflows on parse) ANYWHERE in it, not just in a field the gate reads -- this is what keeps every report a valid, complete JSON file even under adversarial input.
  4. READY_FOR_PLAN always carries a usable plan. entry_trigger is guaranteed non-empty and invalidation_level is guaranteed a finite positive number whenever the status is READY_FOR_PLAN -- enforced both by input validation and by a defensive invariant check.
  5. Not investment advice. entry_trigger and invalidation_level are factual echoes of the upstream price-action report, not recommendations.

Resources

  • scripts/run_contrarian_setup_gate.py -- CLI: hardened JSON loading (unreadable / parse_error incl. RecursionError / non_finite via an iterative whole-file scan), report generation
  • scripts/gate_logic.py -- Pure synthesis core: normalization (incl. malformed-shape detection), consistency checks, the precedence state machine
  • references/gate-decision-table.md -- Full decision table, reason-token glossary, worked examples (including the real B6 REJECTED case)

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Contrarian Setup Gate AI skill do?

Synthesize the three Jason Shapiro contrarian-pipeline verdicts (COT crowding, news-reaction failure, weekly price-action confirmation) into one actionable setup_status via a fail-closed precedence state machine. Pure, offline synthesis -- no network, no API keys, no computation beyond validation and precedence.

Why use Contrarian Setup Gate on TypingMind?

Because you install it once and use it with any model. Contrarian Setup Gate is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Contrarian Setup Gate in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/tradermonty/claude-trading-skills/tree/main/skills/contrarian-setup-gate. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Contrarian Setup Gate?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Contrarian Setup Gate?

As many as you like. As long as a model supports skills, you can use Contrarian Setup Gate with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Contrarian Setup Gate AI skill free?

Yes. It is published on GitHub by tradermonty under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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