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BC investment-buddy-pet

［何时使用］当用户需要宠物陪伴式投资助手时；当用户说"帮我找个投资宠物"时；当检测到"投资性格测试""领宠物""持仓跟踪""定投提醒"等关键词时

ClawHub Agent Skills author: lj22503 v1.1.4 MIT-0 76 files body ≈ 2 026 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

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

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
85/100
safety, quality, tests
Safety 60%
95
Quality 40%
70
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

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

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 · 1

✓ No critical or high findings

Medium and low: 1
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash
    allowed-tools: Bash Read Write Exec Message

Files scanned: 76. 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 "created"
  • note frontmatter-key unknown frontmatter key "skill_type"
  • note frontmatter-key unknown frontmatter key "related_skills"

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. Tools declared in frontmatter
  • 100Steps. 39 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2026 tokens
  • 100Running it twice. No mutating operations
  • low 11 top-level sections: this looks like several domains in one skill

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

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Description length 72: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -235 emoji in the instructions: noise for the model
  • -314 of 16 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 2 example trigger phrases
  • +4Structure: 27 headings
  • +3Step-by-step instructions: 39 items
  • +4Has examples (27 code blocks)
  • +4Reference files are cited in the instructions (1 of 8)

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

External checks

ClawHub: suspicious
This finance companion is not clearly malicious, but it combines broad execution, persistent financial profiling, proactive messaging, sync/share features, and contradictory investment-advice safeguards that deserve Review before installation.
LLM: suspicious (high) · VirusTotal: · 29 May 2026