Chart pattern recognition, price action patterns, candlestick signal bars, pullback bar counting H1/H2/H3/H4, trend channels, micro channels, trading ranges, breakouts, major trend reversals 5-step…

Apache-2.0Auto-check passedBusiness, Finance & HR

Install Chart Patterns

skills CLI
$ npx skills add agentii-ai/agentii-investment-intelligence --skill chart-patterns -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install agentii-ai/agentii-investment-intelligence chart-patterns --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/agentii-ai/agentii-investment-intelligence.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/vertical-plugins/technical-analysis/skills/agentii/chart-patterns .claude/skills/chart-patterns && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
chart-patterns
GitHub stars
207
Token cost
~2k tokens
SKILL.md length
825 words
Files
4 (incl. references)
Skills in repo
79
Repo updated
First seen
Licence
Apache-2.0

At a glance

Chart pattern recognition, price action patterns, candlestick signal bars, pullback bar counting H1/H2/H3/H4, trend channels, micro channels, trading ranges, breakouts, major trend reversals 5-step…

  • Works in 5 steps: Macro Context (Mode C —… → Context from price-action Skill → Pattern Identification → …
  • Tasks that involve Trading and backtesting
  • SKILL.md covers Defaults, Preflight, Data Source Priority and Methodology, plus 7 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Chart Patterns is an agent skill from agentii-ai/agentii-investment-intelligence. Chart pattern recognition, price action patterns, candlestick signal bars, pullback bar counting H1/H2/H3/H4, trend channels, micro channels, trading ranges, breakouts, major trend reversals 5-step sequence, wedges, double tops and bottoms, triangles, head and shoulders, climaxes, measured moves, support and resistance

Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `references/chart-patterns-reference.md`, `references/knowledge-frameworks.md` and `references/modes.md`).

It sits in Business, Finance & HR, covering Trading and backtesting. The repository describes itself as: Claude-type skills for institutional equity research — 25 AI agent skills with SEC filings, XBRL financials, earnings calendars, DCF/comps/LBO models, and PPT generation. Powered… The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Trading and backtesting

Example prompts

  • “/chart-patterns”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Macro Context (Mode C — degrade-gracefully)
  2. Context from price-action Skill
  3. Pattern Identification
  4. Setup Matching via MCP
  5. Pattern Output and Handoff

What it can do on your machine

Read from SKILL.md and the folder at commit 86980e1. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Chart Patterns loads about 2k tokens when it runs, and up to ~5.9k if it reads all its reference files. Until then it costs about 84 tokens; SKILL.md has 825 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~84
When it runs · the whole SKILL.md, loaded when a task matches
~2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~5.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from agentii-ai/agentii-investment-intelligence at commit 86980e1, republished under its Apache-2.0 licence (© agentii-ai). 825 words, ~2,041 tokens.

Download SKILL.mdSave it as .claude/skills/chart-patterns/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
chart-patterns
description
Chart pattern recognition, price action patterns, candlestick signal bars, pullback bar counting H1/H2/H3/H4, trend channels, micro channels, trading ranges, breakouts, major trend reversals 5-step sequence, wedges, double tops and bottoms, triangles, head and shoulders, climaxes, measured moves, support and resistance
multi_ticker_semantics
single_target
temporal_scope.default_quarters
1
temporal_scope.max_quarters
4
temporal_scope.description
Technical analysis pattern recognition operates on price data; 1 quarter default.
retrieval_scope
structured_only
layer_tags
L4
min_tool_diversity
2
parameter_free
false

Methodology inspired by publicly taught price action trading frameworks; all text is an original paraphrase.

Defaults

ParameterDefault ValueRationale
bar_count_threshold20 barsPullback > 20 bars = full Trading Range
reversal_steps5All trend reversals follow the same 5-step mechanical sequence
wedge_legs3Wedge requires three pushes at a trend extreme
climax_aftermathTrading RangeAfter a climax, market enters TR before any reversal

Preflight

Run canonical pre-flight per contracts/preflight.md. Include the X-Agentii-Trace header on every tool call per contracts/x-agentii-trace-header.md — carry the _run_id from your first tool result and name yourself (and your parent, if you were spawned).

Data Source Priority

  1. Chart patterns framework — references/chart-patterns-reference.md (bundled full pattern methodology)
  2. Upstream context — market structure classification from price-action skill output
  3. Technical setups — search_technical_setups(pattern_type=..., market_condition=..., timeframe=...) for matching against gold.technical_setups

Methodology

Retrieval Scope

structured_only

Retrieval Strategy

This skill follows Branch (d) Simple Lookup from contracts/retrieval.md: the pattern recognition framework is bundled in references/chart-patterns-reference.md. Real-time price data via get_realtime_quote. Matched technical setups via search_technical_setups. No unstructured document retrieval.

Temporal Scope

See frontmatter temporal_scope block.

Tool Allowlist

See frontmatter allowed_tools.

Protocol

This skill implements the price action trading pattern recognition framework: 17 distinct chart pattern types, each with specific identification criteria, decision rules, and entry/exit parameters. The core architecture: Setup = Context + Signal Bar — context (from price-action skill) determines which patterns are valid. A perfect signal bar in the wrong context is a losing trade. Detailed methodology and pattern-specific rules are in references/chart-patterns-reference.md.

Step 1 — Macro Context (Mode C — degrade-gracefully)
  1. Assess VIX via get_realtime_quote for broad market proxy.
  2. VIX elevated (> 25) → tighten position sizing, favor defined-risk setups. Low VIX (< 15) → standard sizing.
  3. Degrade gracefully if unavailable: annotate coverage_gap and proceed.
Step 2 — Context from price-action Skill

Receive or derive market structure classification:

  1. market_condition: trending_up / trending_down / ranging
  2. trend_strength: strong / weak(channel) / none
  3. always_in_direction: long / short / neutral
  4. cycle_phase: breakout / channel / trading_range / reversal

Critical rule: Context determines which patterns are valid:

  • Strong bull trend + always_in_long → only long patterns (H1, H2, bull breakouts). All short patterns invalid.
  • Strong bear trend + always_in_short → only short patterns (L1, L2, bear breakouts).
  • Ranging → Buy Low/Sell High only near boundaries. Middle of range = no trade.
Step 3 — Pattern Identification

Apply the full 17-pattern recognition framework based on current context:

If in a Trend:

  1. Pullback depth → count legs: 1-leg = H1/L1 (strong trend), 2-leg = H2/L2 (channel), 3-leg = H3/L3 (broader), 4-leg = H4/L4 (near TR).
  2. Channel boundaries → identify trend line and channel line. Assess tight vs broad.
  3. Breakout signals → true vs false breakout assessment using bar characteristics.
  4. Reversal watch → check if 5-step reversal sequence is progressing (Steps 1-5).

If in a Trading Range:

  1. Range boundaries → identify support and resistance levels from prior swing points.
  2. Breakout preparation → monitor for breakout direction.
  3. TR size assessment → small TR (< 20 bars) = pullback, direction biased. Large TR (≥ 20 bars) = direction neutral.

If near a Trend Extreme:

  1. Climax check → consecutive strong bars → sudden large counter-bar → climax detected. After climax: expect TR, not immediate reversal.
  2. Wedge check → three pushes to same area, each push weaker → exhaustion signal.
  3. 5-step reversal → if Steps 1-4 are complete, watch for Step 5 confirmation.
  4. Double top/bottom → two tests of same level; neckline break for confirmation.
Show full SKILL.md (293 more words)Show less
Step 4 — Setup Matching via MCP

Match identified patterns against the gold.technical_setups database:

search_technical_setups(
  pattern_type=<pullback|breakout|reversal|trend_following|range_trading>,
  market_condition=<trending_up|trending_down|ranging>,
  timeframe=<derived from analysis>,
  instrument_scope=[<equity|option|futures>]
)
  1. Filter results by research_score (higher = more thoroughly researched).
  2. For each matched setup, load confirmation signals and compare against current market data.
  3. Rank by fit: exact match → similar match → partial match.
  4. If no match: proceed with manual pattern rules from references/chart-patterns-reference.md.
Step 5 — Pattern Output and Handoff

Produce structured pattern identification output:

  1. Primary pattern: The best-fit identified pattern with confidence level.
  2. Secondary patterns: Alternative patterns if primary is borderline.
  3. Invalid patterns: Patterns that appear but are invalidated by context (e.g., bearish engulfing in strong bull).
  4. Handoff to trade-execution: Pattern type + market condition + timeframe → for setup selection and trade plan generation.

Output File

{ticker}/{YYYY-MM-DD_HHMM}_chart-patterns_{affix}.md

Output Structure

  1. Executive Summary — Primary pattern identified, market context, confidence level
  2. Context Assessment — Market structure (from price-action), Always In direction, valid/invalid pattern directions
  3. Trend Analysis — Bar counting (H1/H2/H3/H4 status), channel classification (tight/broad), breakout quality
  4. Reversal Assessment — 5-step sequence status (which steps have completed), climax detection, wedge count
  5. Pattern Details — Primary pattern with specific entry/stop criteria, secondary patterns
  6. Setup Matches — Results from search_technical_setups ranked by fit; match quality assessment
  7. Handoff Parameters — pattern_type + market_condition + timeframe for trade-execution skill
  8. Coverage Gaps — Data limitations and degraded-mode annotations

Error Handling

ErrorFallback
No upstream context from price-actionSelf-derive market structure from raw price data; flag degraded
search_technical_setups unreachableProvide manual pattern rules from references/chart-patterns-reference.md; flag gap
Pattern ambiguousList all viable patterns; recommend waiting for confirmation bar
No matching pattern foundReport "no high-confidence pattern identified"; flag for manual review

Memory Load

See contracts/memory-load.md.

Snapshot

See contracts/snapshot-synthesis.md.

Final Summary (TUI)

Include ### Key Citations block with 0-10 clickable /v/ URLs.

References

  • references/chart-patterns-reference.md
  • contracts/citation-and-memory.md
  • contracts/output-frontmatter-schema.md
  • contracts/memory-load.md
  • contracts/snapshot-synthesis.md
  • contracts/preflight.md
  • contracts/retrieval.md

© agentii-ai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (references) in plugins/vertical-plugins/technical-analysis/skills/agentii/chart-patterns of agentii-ai/agentii-investment-intelligence.

  • SKILL.md
  • references/chart-patterns-reference.md
  • references/knowledge-frameworks.md
  • references/modes.md

Open the folder on GitHubat commit 86980e1

Compare with similar skills

Chart Patterns next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Chart Patterns compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Chart Patterns this skillagentii-ai/agentii-investment-intelligence207—~2kAutomated safety check: PassApache-2.0
Tushare Datazillionare/zillionare3192 repos~2.3kAutomated safety check: PassNone
Tradingview MCPatilaahmettaner/tradingview-mcp5k—~1.3kAutomated safety check: PassMIT
Digital Oraclekomako-workshop/digital-oracle870—~5.9kAutomated safety check: PassMIT
Fintoolsecond-state/fintool3161 repos~5.9kAutomated safety check: PassNone
Polyclawchainstacklabs/polyclaw3601 repos~2kAutomated safety check: PassApache-2.0

Similar skills

  • Tushare Data

    zillionare/zillionare

    面向中文自然语言的 Tushare 数据研究技能。用于把“看看这只股票最近怎么样”“帮我查财报趋势”“最近哪个板块最强”“北向资金在买什么”“给我导出一份行情数据”这类请求,转成可执行的数据获取、清洗、对比、筛选、导出与简要分析流程。适用于 A 股、指数、ETF/基金、财务、估值、资金流、公告新闻、板块概念与宏观数据等研究场景。

    319 GitHub starsUsed in 2 repos~2.3k tokens
    Business, Finance & HRAuto-check passed
  • Tradingview MCP

    atilaahmettaner/tradingview-mcp

    AI Trading Intelligence — live prices, 30+ technical indicators, backtesting (6 strategies), walk-forward overfitting detection, trade logs, equity curves, licensed news sentiment (Marketaux), and…

    5k GitHub stars~1.3k tokensUpdated today
    Business, Finance & HRAuto-check passed
  • Digital Oracle

    komako-workshop/digital-oracle

    Answer prediction questions using market trading data, not opinions.

    870 GitHub stars~5.9k tokensUpdated 2 mo ago
    Business, Finance & HRAuto-check passed
  • Fintool

    second-state/fintool

    Financial trading CLIs — spot and perp trading on Hyperliquid, Binance, Coinbase, OKX.

    316 GitHub starsUsed in 1 repo~5.9k tokens
    Business, Finance & HRAuto-check passed
  • Polyclaw

    chainstacklabs/polyclaw

    Trade on Polymarket via split + CLOB execution. An agent skill from chainstacklabs/polyclaw.

    360 GitHub starsUsed in 1 repo~2k tokens
    Business, Finance & HRAuto-check passed
  • Markdown

    facioquo/stock-indicators-dotnet

    Format and lint Markdown in this repository against GitHub Flavored Markdown and its markdownlint-cli2 configuration — headers, lists, code fences, callouts (VitePress containers on docs-site pages…

    1.2k GitHub stars~812 tokensUpdated today
    Business, Finance & HRAuto-check passed

More from agentii-ai/agentii-investment-intelligence

All 79 skills in this repo
  • Clarify

    agentii-ai/agentii-investment-intelligence

    The research-domain clarification skill — find underspecified items in a thesis spec.md (prose wrongif, universe rows without rationale, missing budget/expiry/pins, ambiguous pillars), ask the human…

    207 GitHub starsUsed in 1 repo~839 tokens
    Auto-check passed
  • Constitution

    agentii-ai/agentii-investment-intelligence

    Scaffold and amend the L1 Investment Constitution — [ALLCAPS] placeholder bootstrap, SemVer bump rules, Sync Impact Report, MINOR/MAJOR re-examination dispatch after the gate-5 budget confirm.

    207 GitHub starsUsed in 1 repo~596 tokens
    Auto-check passed
  • Implement

    agentii-ai/agentii-investment-intelligence

    Execute research tasks — checklist soft gate, phase dispatch with explicit thesisdir, budget enforcement (halt + approval card on overrun), skillpin recording (versionhash content-hashed per skill…

    207 GitHub starsUsed in 1 repo~583 tokens
    Auto-check passed
  • Tasks

    agentii-ai/agentii-investment-intelligence

    Decompose the plan into research tasks — one task per ticker × skill × mode, grouped by pillar, [P]-marked by the different-files-and-no-incomplete-deps rule, with source-refs.

    207 GitHub starsUsed in 1 repo~476 tokens
    Auto-check passed
  • Challenge

    agentii-ai/agentii-investment-intelligence

    Adversarial verification of research theses — cross-run/cross-thesis contradiction via the entity index, pre-mortem (Klarman/Kahneman: assume the loss already happened, reverse the path), inversion…

    207 GitHub stars~735 tokensUpdated 9 days ago
    Auto-check passed
  • Converge

    agentii-ai/agentii-investment-intelligence

    Append-only gap closure and the cadence engine for research theses.

    207 GitHub stars~789 tokensUpdated 9 days ago
    Auto-check passed

Questions about Chart Patterns

What does Chart Patterns do?

Chart pattern recognition, price action patterns, candlestick signal bars, pullback bar counting H1/H2/H3/H4, trend channels, micro channels, trading ranges, breakouts, major trend reversals 5-step…. Chart Patterns is an agent skill from agentii-ai/agentii-investment-intelligence.

When should I use Chart Patterns?

Chart Patterns fits situations like: tasks that involve Trading and backtesting.

How do I install Chart Patterns in Claude Code?

Run `npx skills add agentii-ai/agentii-investment-intelligence --skill chart-patterns -a claude-code`. Or copy the skill folder (plugins/vertical-plugins/technical-analysis/skills/agentii/chart-patterns in agentii-ai/agentii-investment-intelligence) into .claude/skills/chart-patterns in your project. Claude Code loads it when a task matches its description.

How do I install Chart Patterns in Codex?

Run `npx skills add agentii-ai/agentii-investment-intelligence --skill chart-patterns -a codex`. Or copy the skill folder (plugins/vertical-plugins/technical-analysis/skills/agentii/chart-patterns in agentii-ai/agentii-investment-intelligence) into .agents/skills/chart-patterns in your project. Codex loads it when a task matches its description.

Can I use Chart Patterns in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add agentii-ai/agentii-investment-intelligence --skill chart-patterns -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/chart-patterns, .gemini/skills/chart-patterns, .github/skills/chart-patterns and .opencode/skills/chart-patterns in your project.

What does Chart Patterns need to run?

SKILL.md names no scripts, command-line tools or credentials: Chart Patterns is instructions for the agent only.

Does Chart Patterns access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Chart Patterns safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Chart Patterns use?

Chart Patterns is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Chart Patterns use?

About 2k tokens (SKILL.md is roughly 8.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3.8k tokens, read only when the agent opens those files.

What are the alternatives to Chart Patterns?

Skills that share tags, products or a category with Chart Patterns: Tushare Data (zillionare/zillionare, 319 stars), Tradingview MCP (atilaahmettaner/tradingview-mcp, 5k stars), Digital Oracle (komako-workshop/digital-oracle, 870 stars) and Fintool (second-state/fintool, 316 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Chart Patterns?

agentii-ai (a GitHub user) maintains it in agentii-ai/agentii-investment-intelligence, which has 207 GitHub stars. The repository holds 79 skills in this directory. The repository was last updated on September 29, 2026.

Source: agentii-ai/agentii-investment-intelligence on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.