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AC alibabacloud-cdn-refresh-preload

Read-only diagnostics for Alibaba Cloud CDN refresh and preload issues. Use when a URL/file/directory refresh or preload looks ineffective - refresh failed, preload failed, cache not cleared, or the task failed. Verifies task records and edge cache status, and produces a diagnosis report; never submits refresh/preload jobs. Triggers: "refresh failed", "preload failed", "cache not cleared", "purge not working", "prefetch not cached", "warm up ineffective", "invalidation unsuccessful", "pre-warming failure", "pre-fetching".

ClawHub Agent Skills author: alibabacloud-skills-team v0.0.1 MIT-0 11 files body ≈ 2 742 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

Read-only diagnostics for Alibaba Cloud CDN refresh and preload issues.

As a process C 61/100 · Has gaps — weak spots: result and completion, when it triggers, running it twice

AnalyzerData and analyticstype 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
98/100
safety, quality, tests
Safety 60%
100
Quality 40%
96
Run on models
none yet
Process rating
C
61/100
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 · 0

    ✓ No critical or high findings

    Files scanned: 11. 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 61/100

    • 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. 1 mutating operations with no state check
    • 60Tools and files. Uses tools (bash, web, python, node) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 27 steps
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2742 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

    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 9 example trigger phrases
    • +3Description length 527: enough signal without eating the budget
    • +4Structure: 23 headings
    • +3Step-by-step instructions: 27 items
    • +4Has examples (5 code blocks)
    • +4Reference files are cited in the instructions (3 of 5)
    • +3All 3 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 96.

    External checks

    ClawHub: suspicious
    The skill is mostly a disclosed read-only CDN diagnostic tool, but it can automatically enumerate CDN task records across all visible domains when the user gives incomplete input.
    LLM: suspicious (high) · 17 Aug 2026