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BC generate-console-theme

Generate a data-only animated theme preset for Ruflo Console Theme Studio. Use when the user requests a new console color palette, cyberpunk theme, or variation of Orbital globe, stars, and swarm animation in Claude or Codex.

The skillemall take

Generates themes for Ruflo Console Theme Studio—takes a palette request and outputs a config with orbital, star, and swarm animations. Claims support for nine platforms from Claude to DeepSeek.

The 428 tokens of code are clean: no critical errors, linter passes. Quality scores 80, but process only 57—logic works, testing and docs lag behind. No model runs, no sandbox tests. No serious findings reported.

Whether themes actually render remains untested. The skill hasn't run on real models, and platform support is unclear—could be a genuine list or wishful thinking. Install if you need a template and don't mind tweaking it yourself.

ruvnet/claude-flow Agent Skills author: ruvnet MIT 3 files body ≈ 428 tokens Open the sourcegithub.com↗ analyzed 6 d ago

Generate a data-only animated theme preset for Ruflo Console Theme Studio.

As a process C 57/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

GeneratorAI and agentsSoftware developmentDesigntype 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
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
80
Run on models
none yet
Process rating
C
57/100
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

The same skill appears in 1 more place: ruflo

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 · 0

    ✓ No critical or high findings

    Files scanned: 3. 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 57/100

    • 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
    • 30Running it twice. 1 mutating operations with no state check
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. Tools declared in frontmatter
    • 100Steps. 5 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 428 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: 1 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 225: enough signal without eating the budget
    • +3Step-by-step instructions: 5 items
    • +4Reference files are cited in the instructions (1 of 1)

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