SKILLEMALL.ai

AC continuation-patterns

当用户在图中看到三角形、旗形、三角旗形、楔形、矩形等"价格中途歇脚"的图案,想判断趋势是否会延续时激活。 持续形态与反转形态相反:它代表趋势暂停后**沿原方向突破**。也涵盖喇叭形(常是反转预警)与钻石形态。 不适用于:头肩/双顶等反转图案(转 reversal-patterns)、通用支撑阻挡(转 trend-tools)。 关键 trigger 词:三角形整理、旗形、楔形、矩形、箱体、持续形态、整理后继续涨、喇叭形。 Activate when the user spots triangle, flag, pennant, wedge, rectangle, or similar "mid-trend resting" patterns and wants to judge whether the trend will continue. Continuation patterns are the opposite of reversal patterns: they represent a pause after which price **breaks out in the original direction**. Also covers broadening formations (often a reversal warning) and diamonds. Not applicable: head-and-shoulders / double-top reversal patterns (-> reversal-patterns), or generic support/resistance (-> trend-tools). Key trigger words: triangle consolidation, flag, wedge, rectangle, box range, continuation pattern, resume-after-consolidation, broadening formation.

ClawHub Agent Skills author: bianchunhui v0.1.0 MIT-0 3 files body ≈ 541 tokens Open the sourceclawhub.ai analyzed 2 d ago

当用户在图中看到三角形、旗形、三角旗形、楔形、矩形等"价格中途歇脚"的图案,想判断趋势是否会延续时激活。 持续形态与反转形态相反:它代表趋势暂停后沿原方向突破。也涵盖喇叭形(常是反转预警)与钻石形态。 不适用于:头肩/双顶等反转图案(转 reversal-patterns)、通用支撑阻挡(转…

As a process C 59/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

Proceduretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
79
Run on models
none yet
Process rating
C
59/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 0

    ✓ No critical or high findings

    Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "source_book"
    • note frontmatter-key unknown frontmatter key "source_chapter"
    • note frontmatter-key unknown frontmatter key "related_skills"

    Process rating: all ten parameters 59/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 42 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 541 tokens
    • 100Running it twice. No mutating operations

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +4Description does not say when NOT to use the skill (false activations)
    • +3Description length 884: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 2 example trigger phrases
    • +4Structure: 18 headings
    • +3Step-by-step instructions: 42 items

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.

    External checks

    ClawHub: clean
    This is a static educational chart-analysis skill with no install hooks, code execution, data access, or persistence.
    LLM: benign (high) · VirusTotal: · 3 Aug 2026