Skills longbridge-technical
📦

longbridge-technical

v1.0.0 Content revision r3 High Risk 📁 Filesystem access🔑 Env variables⚙️ External commands

Analyze Markets with Technical Frameworks

Technical analysis often requires several methods and consistent data preparation. This skill applies nine structured frameworks to Longbridge OHLCV data and explains each result.

Supports: Claude Codex Code(CC)
⚠️ 38 Poor

Install with my Agent

Copy this request to your Agent. It includes the canonical Skill page and manifest.

Agent request
Review the Skillstore skill "longbridge-technical" from https://skillstore.io/skills/longbridge-longbridge-technical.md and its manifest at https://skillstore.io/api/skills/longbridge-longbridge-technical/manifest. Verify the artifact. Stop and obtain explicit user consent before installing or changing files.

Your Agent should still show its plan and request any confirmation required by the security policy.

Test it

Using "longbridge-technical". Analyze AAPL.US with technical indicators.

Expected outcome:

Trend: bullish but extended. MACD supports momentum, RSI is near overbought, and price is above both major moving averages.

Using "longbridge-technical". Calculate a Turtle Unit for a $100,000 account when N is $2.50.

Expected outcome:

One Unit is 400 shares. A stop placed 2N from entry risks about $2,000, or 2% of account value.

Using "longbridge-technical". Compare two possible Elliott Wave counts.

Expected outcome:

The primary count suggests a late impulse, while the alternate count remains corrective. Conflicting momentum keeps the structure unconfirmed.

Security Audit

High Risk
v6 • 8/8/2026 Open versioned report

Most alerts are false positives from Markdown backticks, calculations, multilingual text, and conventional device redirection. Package installation and predictable temporary paths present genuine risks. Missing relative scripts and unquoted symbol placeholders add command-execution exposure.

10
Files scanned
1,737
Lines analyzed
7
Review items
0
False positives ignored

Confirmed security concerns (2)

High
Unvalidated Symbol Interpolation in Shell Commands
Shell examples place user-supplied symbols directly into commands without validation or quoting. Metacharacters could alter commands when substituted verbatim.
The command templates visibly interpolate symbol placeholders without quoting or an allowlist. Exploitation depends on verbatim shell construction from untrusted input.
High
Missing Relative Script Creates Path-Hijack Risk
The skill directs execution of scripts/signal_engine.py, but the package contains no script. A same-named working-directory file could execute without provenance.
The documented command executes a relative Python path, while the complete package tree has no scripts directory. This directly enables unintended local code execution.
Capability review items (7)

These are real local capabilities that may be expected for this skill, so they require review but are not counted as confirmed malicious behavior.

Medium
Temp directory access
- Always redirect CLI output to a temp file (e.g. `/tmp/kline_day.json`) — the CLI may
The skill mandates a predictable shared temporary path. Another local process could replace or read this file before analysis.
Medium
Temp directory access
python3 scripts/signal_engine.py --kline /tmp/kline_day.json --symbol SYMBOL
The analysis script reads a fixed file under /tmp. Predictable names permit input tampering and symlink attacks.
Medium
Temp directory access
python3 scripts/signal_engine.py --kline /tmp/kline_day.json --symbol AAPL.US
This command reads market data from the same predictable shared path. The file lacks uniqueness, ownership checks, and integrity validation.
Medium
Ruby/shell backtick execution
Auto-detect fractal (分型), bi (笔), zhongshu (中枢), buy/sell signals (1/2/3 buy). Requires `pip install
The skill directs users to install czsc with pip. Package installation can execute build hooks and introduces supply-chain risk.
Medium
Ruby/shell backtick execution
BOS (Break of Structure), ChoCH, FVG (Fair Value Gap), Order Block detection. Requires `pip install
The skill directs installation of smartmoneyconcepts. Unpinned Python packages can execute installation code and change the environment.
Medium
Ruby/shell backtick execution
| `ModuleNotFoundError: czsc` | Run `pip install czsc` before using Chan Theory |
This line explicitly instructs pip to install an unpinned third-party package. Installation may execute package-controlled code.
Medium
Ruby/shell backtick execution
| `ModuleNotFoundError: smartmoneyconcepts` | Run `pip install smartmoneyconcepts` before using SMC
This line explicitly instructs pip to install smartmoneyconcepts without a version or hash. That creates supply-chain exposure.
Audited by: codex View Audit History →
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Open versioned report
Security Assessment

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Academic citations (APA · BibTeX · CFF)

APA citation

longbridge. (2026). longbridge-technical security audit report (audit version 6) [Author version 1.0.0]. Skillstore. https://skillstore.io/skills/longbridge-longbridge-technical/audits/6

BibTeX citation

@techreport{longbridge-longbridge-longbridge-technical-2026, author = {longbridge}, title = {longbridge-technical security audit report (audit version 6)}, institution = {Skillstore}, year = {2026}, number = {6}, url = {https://skillstore.io/skills/longbridge-longbridge-technical/audits/6}, note = {Author version 1.0.0} }

CITATION.cff

cff-version: 1.2.0 message: "If you use this Skill, cite its author and this versioned security audit report." title: "longbridge-technical security audit report (audit version 6)" version: "1.0.0" type: report authors: - name: "longbridge" date-released: "2026-08-08" url: "https://skillstore.io/skills/longbridge-longbridge-technical/audits/6" identifiers: - type: other value: "skillstore:longbridge-longbridge-technical:audit:6" description: "Skillstore immutable audit report identifier"

Skillstore Score

Why this score Evidence Confidence: Medium
45
Architecture
100
Maintainability
87
Content
67
Community
83
Spec Compliance

What You Can Build

Review a Stock

Combine indicators and chart structures into one dated analysis with clear support, resistance, and invalidation conditions.

Compare Technical Methods

Check whether candlestick, Ichimoku, Elliott Wave, and momentum signals agree or conflict.

Teach Rule-Based Trading

Demonstrate Turtle breakouts, ATR risk, Unit sizing, stops, and market-specific constraints with worked examples.

Try These Prompts

Explain Core Indicators
Analyze AAPL.US with RSI, MACD, EMA, and Bollinger Bands using 200 daily candles. Explain every signal in plain English.
Compare Two Frameworks
Analyze 700.HK with candlestick and Ichimoku methods. Identify agreement, conflicts, invalidation levels, and the data date.
Validate Market Structure
Evaluate NVDA.US with Elliott Wave and Smart Money Concepts. Present alternate counts, momentum confirmation, key zones, and uncertainty.
Build a Turtle Plan
Scan my authorized watchlist for Turtle System 1 and System 2 signals. Calculate ATR and Unit sizing from a $100,000 account value.

Best Practices

  • Confirm the symbol and market suffix before requesting data.
  • State the timeframe, bar count, and data cutoff in every analysis.
  • Compare independent signals and preserve uncertainty when frameworks disagree.

Avoid

  • Do not treat a single indicator as a guaranteed trade signal.
  • Do not install packages or read account data without explicit user approval.
  • Do not provide position sizes when account value or ATR data is missing.

Frequently Asked Questions

What data does this skill need?
It needs OHLCV history from Longbridge. Required history varies by framework and can reach 300 daily bars.
Can this skill place trades?
No. It analyzes data and produces signals, levels, and position-sizing references.
Which frameworks are supported?
It covers candlesticks, Ichimoku, indicators, harmonics, Elliott Wave, Chan Theory, Smart Money Concepts, and Turtle Trading.
Does it access my account?
Only Turtle sizing workflows may request authorized assets, positions, watchlists, or order history. You can provide account values manually.
Are extra packages required?
Chan Theory and Smart Money workflows require third-party Python packages. Review and approve dependencies before installation.
Are the signals reliable?
Signals depend on historical data and model assumptions. They can conflict, fail in changing markets, and do not guarantee returns.

Developer Details

Author

longbridge

License

MIT

Author version

v1.0.0

Skillstore revision

r3

Version notice

The installable content changed, but the author did not update the declared version.

Ref

656be3040aef5c047555a908cd5c695d22a4a548

Maintenance freshness

8/8/2026

Usage

7 downloads · 0 views

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