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BC raiffeisen-elba

Automate Raiffeisen ELBA online banking: login/logout, list accounts, and fetch transactions via Playwright.

ClawHub Agent Skills author: Oliver Drobnik v1.4.5 MIT-0 10 files body ≈ 552 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 55/100 · Has gaps — weak spots: result and completion, failures and branches, running it twice

ProcedurePlaywrightInfrastructureDesigntype 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
84/100
safety, quality, tests
Safety 60%
97
Quality 40%
64
Run on models
none yet
Process rating
C
55/100
Has gaps
Result and completion w 14
0
Failures and branches w 10
0
Progress reporting w 2
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 · 3

✓ No critical or high findings

Medium and low: 3
  • low Secrets in code secret-high-entropy-token scripts/download_transactions.py:268
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    'transaktionsteilnehmer': tx.get('tran…le1', ''),
    quoted
  • low Secrets in code secret-high-entropy-token scripts/elba.py:1667
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    tx.get("tran…le1"),
    quoted
  • low Secrets in code secret-high-entropy-token scripts/elba.py:1668
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    tx.get("tran…2u3"),
    quoted

Files scanned: 10. 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 "summary"
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 55/100

  • 0Result and completion. Does not say what the result is
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 3 mutating operations with no state check
  • 50When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 4 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 552 tokens

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 108: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -33 of 4 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +4Structure: 5 headings
  • +3Step-by-step instructions: 4 items
  • +4Has examples (2 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.

External checks

ClawHub: suspicious
This looks like a real local banking automation skill, but it needs Review because it stores banking credentials/session material and includes under-documented document-download capabilities.
LLM: suspicious (high) · VirusTotal: · 9 Jul 2026