SKILLEMALL.ai

AD czsc-thinking

教导 AI 代理如何以缠论原文的思维方式分析交易机会。当需要分析股票买卖点、大盘行情、制定交易策略或进行市场研判时使用此技能。适用于:(1) 股票买卖点分析 (2) 大盘趋势研判 (3) 交易心理分析 (4) 操作策略制定 (5) 风险控制思考

ClawHub Agent Skills author: Chenghd511 v1.0.0 MIT-0 9 files body ≈ 536 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureInfrastructuretype 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
D
41/100
Unfinished process
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

  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 · 0

✓ No critical or high findings

Files scanned: 9. 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 41/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (czsc-thinking) differs from the folder (czsc)
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 46 steps
  • 100Execution cost. Instruction body is 536 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

  • +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 122: enough signal without eating the budget
  • +4Structure: 21 headings
  • +3Step-by-step instructions: 46 items
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)
  • +3All 3 scripts are documented

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

External checks

ClawHub: clean
This is a disclosed stock-analysis skill with optional market-data scripts; it does not execute trades or hide unrelated access, but users should treat its trading signals as informational only.
LLM: benign (high) · VirusTotal: · 29 May 2026