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AC nano-gpt

Use when tasks need the NanoGPT API for text, image, or video generation through the local `nano-gpt` CLI and bundled wrapper scripts for OpenClaw or ClawHub workflows. This skill requires a NanoGPT API token.

ClawHub Agent Skills author: icework v0.1.2 MIT-0 32 files · 6 scripts body ≈ 926 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 52/100 · Has gaps — weak spots: result and completion, when it triggers, consistency

IntegrationAI and agentsMedia and videoInfrastructuretype 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
93/100
safety, quality, tests
Safety 60%
99
Quality 40%
84
Run on models
none yet
Process rating
C
52/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
When it triggers w 12
20
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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Secrets in code secret-password-literal cli/test/config.test.ts:40
      Hard-coded password / key literal (may be an example) (placeholder value)
      apiKey: "abcd…678",
      placeholder

    Files scanned: 32. 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 52/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 2 mutating operations with no state check
    • 40Consistency. Frontmatter name (nano-gpt) differs from the folder (nano-gpt-cli)
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 60Failures and branches. 2 branches
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 19 steps
    • 100Execution cost. Instruction body is 926 tokens
    • 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
    • -31 of 6 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +3Description length 209: enough signal without eating the budget
    • +4Structure: 6 headings
    • +3Step-by-step instructions: 19 items
    • +4Has examples (12 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: clean
    This skill coherently wraps the NanoGPT API and only sends user-provided prompts or media, though users should prefer environment variables over storing the API key locally.
    LLM: benign (high) · VirusTotal: · 29 May 2026