SKILLEMALL.ai

BC wyckoff

Wyckoff A-share analysis agent with full CLI + MCP integration. Detects local CLI installation, guides users through setup (install → register → configure data sources → configure model → optional MCP server), then executes Wyckoff-style volume-price analysis with auditable portfolio decisions. Supports first-time onboarding, daily operational workflows (portfolio management, signal queries, recommendations) via the wyckoff CLI, and 14-tool MCP server for Claude Code / Cursor integration.

ClawHub Agent Skills author: YoungCan-Wang v1.0.2 MIT-0 7 files body ≈ 2 225 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 62/100 · Has gaps — weak spots: result and completion, consistency, running it twice

IntegrationAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
97
Quality 40%
76
Run on models
none yet
Process rating
C
62/100
Has gaps
Result and completion w 14
0
Running it twice w 4
30
Consistency w 8
40
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 3

✓ No critical or high findings

Medium and low: 3
  • low Dangerous commands cmd-pipe-to-shell-known-host rules/cli-setup-guide.md:12
    Pipe-to-shell installer from a well-known host (still executes remote code) (documentation of a security skill)
    curl -fsSL https://raw.githubusercontent.com/YoungCan-Wang/Wyckoff-Analysis/main/install.sh | bash
    security skill
  • low Dangerous commands cmd-pipe-to-shell-known-host SKILL.md:25
    Pipe-to-shell installer from a well-known host (still executes remote code) (documentation of a security skill)
    curl -fsSL https://raw.githubusercontent.com/YoungCan-Wang/Wyckoff-Analysis/main/install.sh | bash
    security skill

A further 1 matches are quotations in this security skill's documentation and are not counted as findings.

Files scanned: 7. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 62/100

  • 0Result and completion. Does not say what the result is
  • 30Running it twice. 3 mutating operations with no state check
  • 40Consistency. Frontmatter name (wyckoff) differs from the folder (wyckoff-agent-skill)
  • 50When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 82 steps
  • 100Failures and branches. 8 branches, has a failure section
  • 100Execution cost. Instruction body is 2225 tokens
  • 100Progress reporting. Reports progress
  • low The response is described with custom markup (5 tags): a typed call is more reliable

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)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 493: enough signal without eating the budget
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 82 items
  • +4Has examples (4 code blocks)
  • +4Reference files are cited in the instructions (4 of 4)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.

External checks

ClawHub: suspicious
This finance-analysis skill is coherent, but it needs Review because it encourages risky installation, credential handling, and broad CLI/MCP actions around portfolio and API data.
LLM: suspicious (high) · VirusTotal: · 29 May 2026