SKILLEMALL.ai

AC wickworks

Stateless OHLC primitives service — candlestick bars in, technical indicators + Smart-Money-Concepts objects out. Single POST / takes a bars array + an indicators selection map and returns computed primitives; GET /metadata is the output-path catalog; GET /health. 67 primitives across trend (SMA/EMA + 15 more MAs, slope, Donchian, Ichimoku), momentum (RSI, MACD, Stoch, StochRSI, ADX, MFI, CCI, Williams %R, ROC, MOM, TSI, TRIX, UO, Fisher), volatility (ATR, NATR, Bollinger, Keltner, Squeeze), volume (VWAP, VWMA, OBV, AD, ADOSC, CMF, KVO), and SMC (order blocks, fair-value gaps, BOS/CHoCH, swing structure, S/R levels, liquidity, retracements, sessions, previous-period H/L) plus pre-baked summaries. camelCase, NaN-safe JSON. Unified REST + MCP (streamable-HTTP at /mcp — tools health / list_indicators / metadata / compute). Auth-less by default. Use when the user wants technical indicators or Smart-Money-Concepts primitives computed from OHLC candlestick bars.

ClawHub Agent Skills author: Ciprian Mandache v0.7.0 MIT-0 3 files body ≈ 1 982 tokens Open the sourceclawhub.ai analyzed 25 h ago

Stateless OHLC primitives service — candlestick bars in, technical indicators + Smart-Money-Concepts objects out.

As a process C 54/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

ProcedureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
82
Run on models
none yet
Process rating
C
54/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
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: 1. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "homepage"

    Process rating: all ten parameters 54/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 1 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 27 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1982 tokens
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Description length 970: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • -2localhost URLs: will not work for another user
    • +1No license
    • +2Single-language instructions
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 27 items
    • +4Has examples (5 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.

    External checks

    ClawHub: suspicious
    The skill appears to do what it claims, but its setup relies on a mutable third-party container image and an unauthenticated service that users must secure themselves.
    LLM: suspicious (high) · VirusTotal: · 5 Sept 2026