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AB apidot-ai-api

Use APIDot as one AI API for image generation API, video generation API, chat API, music generation API, and 3D generation API workflows. Use when users ask for APIDot, AI API integration, GPT Image 2 API, Seedance 2 API, Veo 3.1 API, Sora API, Kling API, polling, webhooks, task status, or API key safety guidance based on APIDot docs.

ClawHub Agent Skills author: jiehao71727 v1.0.5 MIT-0 2 files body ≈ 1 103 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

Use APIDot as one AI API for image generation API, video generation API, chat API, music generation API, and 3D generation API workflows.

As a process B 69/100 · Nearly there — weak spots: result and completion, inputs and preconditions, progress reporting

IntegrationGitHubMedia and videoAI and agentstype 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
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
79
Run on models
none yet
Process rating
B
69/100
Nearly there
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
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 · 0

    ✓ No critical or high findings

    Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "homepage"

    Process rating: all ten parameters 69/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 36 steps
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1103 tokens
    • 100Running it twice. Mutating operations check current state
    • 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 336: enough signal without eating the budget
    • +4Structure: 8 headings
    • +3Step-by-step instructions: 36 items

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.

    External checks

    ClawHub: clean
    This is a documentation-only APIDot integration skill with no bundled code, automation, or hidden credential handling.
    LLM: benign (high) · VirusTotal: · 9 Jul 2026