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AC bizcard

Business card scanner + Google Contacts manager. Auto-detects business card images, extracts contact info via OCR (imageModel), confirms with user, saves to Google Contacts with configurable name format and card photo. Trigger: image that looks like a business card, or keywords "명함", "bizcard", "연락처 저장". Settings: /bizcard config

modbender/skill-library-mcp Agent Skills author: modbender MIT 6 files body ≈ 4 347 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Business card scanner + Google Contacts manager.

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureInfrastructureSoftware developmenttype 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
A
93/100
safety, quality, tests
Safety 60%
94
Quality 40%
91
Run on models
none yet
Process rating
C
51/100
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

    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 · 2

    ✓ No critical or high findings

    Medium and low: 2
    • medium Broad scope meta-agent-memory-dump templates/SOUL.md
      Agent memory / workspace files bundled with the skill (1) — likely a workspace dump with personal data or tokens
      templates/SOUL.md
    • low Dangerous commands cmd-shell-rc README.md:38
      Writes to a shell startup file (documentation of a security skill)
      echo 'export MATON_API_KEY="your-key-here"' >> ~/.zshrc
      security skill

    Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 51/100

    • 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
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 8 mutating operations with no state check
    • 70Execution cost. Instruction body is 4347 tokens
    • 100Tools and files. No external tools needed
    • 100Steps. 41 steps
    • 100Consistency. Name and required fields are in place
    • 100Progress reporting. Reports progress
    • low 19 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)
    • +3Output format is not stated: the model decides each time
    • -232 emoji in the instructions: noise for the model
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 2 example trigger phrases
    • +3Description length 331: enough signal without eating the budget
    • +4Structure: 49 headings
    • +3Step-by-step instructions: 41 items
    • +4Has examples (26 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.