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BB ai-elements

Build AI chat interfaces using ai-elements components — conversations, messages, tool displays, prompt inputs, and more. Use when the user wants to build a chatbot, AI assistant UI, or any AI-powered chat interface.

mxyhi/ok-skills Agent Skills author: mxyhi Apache-2.0 80 files body ≈ 1 742 tokens Open the sourcegithub.com↗ analyzed 4 d ago

Build AI chat interfaces using ai-elements components — conversations, messages, tool displays, prompt inputs, and more.

As a process B 67/100 · Nearly there — weak spots: result and completion, running it twice, progress reporting

GeneratorGitHubSoftware developmentAI and agentsCustomer supporttype 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
90/100
safety, quality, tests
Safety 60%
96
Quality 40%
80
Run on models
none yet
Process rating
B
67/100
Nearly there
Result and completion w 14
0
Progress reporting w 2
0
Running it twice w 4
30
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 · 4

    ✓ No critical or high findings

    Medium and low: 4
    • low Obfuscation obf-base64-blob scripts/chain-of-thought.tsx:17
      Long base64-looking blob (detector / deny-list definition)
      "/9j/4AAQ…AAD/2wCE…AQE
      detector
    • low Secrets in code secret-high-entropy-token scripts/chain-of-thought.tsx:17
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      "/9j/4AAQ…AAD/2wCE…AQE
      quoted
    • low Obfuscation obf-base64-blob scripts/image.tsx:7
      Long base64-looking blob (detector / deny-list definition)
      "/9j/4AAQ…AAD/2wCE…AQE
      detector
    • low Secrets in code secret-high-entropy-token scripts/image.tsx:7
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      "/9j/4AAQ…AAD/2wCE…AQE
      quoted

    Files scanned: 80. 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 67/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 2 mutating operations with no state check
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 11 steps
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1742 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)
    • +3Output format is not stated: the model decides each time
    • -448 reference files, but SKILL.md never points to them: the model will not open them
    • +1No license
    • +2Single-language instructions
    • +3Description length 215: enough signal without eating the budget
    • +4Structure: 15 headings
    • +3Step-by-step instructions: 11 items
    • +4Has examples (4 code blocks)

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