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BC nested-container-frames

Create a container-in-container layout system using nested frames. Use an outer centered container with visible vertical boundary lines and corner markers. Inside, place inner containers inset from the edges, each with its own background and rounded frame. Technique: outer container defines global bounds, inner containers use padding to create inset spacing, layered frames (border + background) to separate levels, and consistent spacing between outer frame and inner blocks.

MengTo/Skills Agent Skills author: MengTo MIT 4 files body ≈ 187 tokens Open the sourcegithub.com↗ analyzed 3 d ago

Create a container-in-container layout system using nested frames.

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

Generatortype and topics are labelled automatically from the skill text
Runs in: 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) OpenClaw Goose OpenCode
JSON
Technical rating
B
91/100
safety, quality, tests
Safety 60%
98
Quality 40%
80
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

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
    • low Obfuscation obf-base64-blob demo/index.html:19
      Long base64-looking blob (quoted — discussed, not commanded)
      const encodedHtml = "PCFE…bWw+Cjxo…YWQ+Cjxt…bmV
      quoted
    • low Secrets in code secret-high-entropy-token demo/index.html:19
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      const encodedHtml = "PCFE…bWw+Cjxo…YWQ+Cjxt…bmV
      quoted

    Files scanned: 4. 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 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. No external tools needed
    • 100Steps. 8 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 187 tokens
    • 100Running it twice. No mutating operations
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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)
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +3Description length 478: enough signal without eating the budget
    • +4Structure: 4 headings
    • +3Step-by-step instructions: 8 items

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.