SKILLEMALL.ai

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东方财富自选股公告追踪。三级过滤 + LLM分类摘要 + Web仪表盘,支持 agent 定时推送。

Not recommendedcritical or high security findings
ClawHub Agent Skills author: 54Lynnn v2.2.0 MIT-0 40 files · 3 scripts body ≈ 756 tokens Open the sourceclawhub.ai analyzed 28 h ago

东方财富自选股公告追踪。三级过滤 + LLM分类摘要 + Web仪表盘,支持 agent 定时推送。

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureGitHubAI and agentsData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
C
62/100
safety, quality, tests
Safety 60%
63
Quality 40%
60
Run on models
none yet
Process rating
D
46/100
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

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Dangerous commands
If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
  2. 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

  • high Dangerous commands cmd-persistence scripts/setup.sh:109
    Persistence mechanism (cron / launchd / scheduled task / autorun registry)
    EXISTING=$(crontab -l 2>/dev/null || true)
  • high Dangerous commands cmd-persistence scripts/setup.sh:120
    Persistence mechanism (cron / launchd / scheduled task / autorun registry)
    ) | crontab -
Medium and low: 1
  • low Dangerous commands cmd-cron-mention scripts/setup.sh:109
    Mentions editing / listing crontab
    EXISTING=$(crontab -l 2>/dev/null || true)

Files scanned: 32. 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 46/100

  • 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
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 100Steps. 25 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 756 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 50: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -2localhost URLs: will not work for another user
  • -44 reference files, but SKILL.md never points to them: the model will not open them
  • -314 of 17 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 25 items
  • +4Has examples (10 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 60.

External checks

ClawHub: suspicious
The skill appears purpose-aligned, but it handles live account cookies, sends announcement data to configurable external services, and includes automatic scheduling behavior that users should review first.
LLM: suspicious (high) · 1 Jul 2026