SKILLEMALL.ai

BC hectorlee-daily-precision-picker

每日精选1-3只股票的四层漏斗策略系统。从量价形态初筛池出发,依次通过量价二次过滤、基本面安全排雷、资金流向打分、板块与形态质量打分,最终输出精选股票,选不出则空仓。触发词:精选、每日优选、深度筛选、资金确认、精筛、4层漏斗。

ClawHub Agent Skills author: HectorLee v2.2.1 MIT-0 6 files body ≈ 1 143 tokens Open the sourceclawhub.ai analyzed 2 d ago

每日精选1-3只股票的四层漏斗策略系统。从量价形态初筛池出发,依次通过量价二次过滤、基本面安全排雷、资金流向打分、板块与形态质量打分,最终输出精选股票,选不出则空仓。触发词:精选、每日优选、深度筛选、资金确认、精筛、4层漏斗。

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
100
Quality 40%
67
Run on models
none yet
Process rating
C
53/100
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

  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: 6. 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")
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "agent_created"

Process rating: all ten parameters 53/100

  • 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
  • 100Tools and files. No external tools needed
  • 100Steps. 32 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1143 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)
  • +3Description length 113: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -31 of 1 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +4Structure: 15 headings
  • +3Step-by-step instructions: 32 items
  • +4Has examples (6 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.

External checks

ClawHub: suspicious
The skill's stock-screening purpose is coherent, but its helper script can run shell commands built from unvalidated stock-code inputs, creating a real local command-execution risk.
LLM: suspicious (high) · 24 Aug 2026