SKILLEMALL.ai
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BC django-creator

This project eliminates the time wasted on creating virtual machines and setting up environments from scratch. It automatically provisions a ready-to-use development environment with commonly used ...

modbender/skill-library-mcp Agent Skills author: modbender MIT 2 files body ≈ 317 tokens Open the sourcegithub.com↗ analyzed 2 d ago

This project eliminates the time wasted on creating virtual machines and setting up environments from scratch.

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

GeneratorSoftware developmentInfrastructuretype 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
87/100
safety, quality, tests
Safety 60%
95
Quality 40%
76
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

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 · 5

    ✓ No critical or high findings

    Medium and low: 5
    • low Dangerous commands cmd-eval-dynamic scriptBackend.py:47
      Dynamic code execution from decoded/untrusted input (quoted — discussed, not commanded)
      os.system(f'''echo "from django.urls import path
      quoted
    • low Dangerous commands cmd-eval-dynamic scriptBackend.py:53
      Dynamic code execution from decoded/untrusted input (quoted — discussed, not commanded)
      os.system(f'''echo "from django.shortcuts import render
      quoted
    • low Dangerous commands cmd-eval-dynamic scriptBackend.py:69
      Dynamic code execution from decoded/untrusted input (quoted — discussed, not commanded)
      os.system(f'''echo "from django.contrib import admin
      quoted
    • low Dangerous commands cmd-eval-dynamic scriptBackend.py:96
      Dynamic code execution from decoded/untrusted input (quoted — discussed, not commanded)
      os.system(f'''echo "from rest_framework_nested import routers
      quoted
    • low Dangerous commands cmd-eval-dynamic scriptBackend.py:104
      Dynamic code execution from decoded/untrusted input (quoted — discussed, not commanded)
      os.system(f'''echo "from rest_framework.viewsets import ModelViewSet
      quoted

    Files scanned: 2. 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
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 1 mutating operations with no state check
    • 100Tools and files. No external tools needed
    • 100Steps. 7 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 317 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)
    • +4Structure: 0 headings, hard to scan
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +3Description length 200: enough signal without eating the budget
    • +3Step-by-step instructions: 7 items

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.