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AC volc-flink-skill

火山引擎 Flink 版统一管理技能，智能路由到合适的子技能处理 Flink 相关问题。包括工具管理、项目配置、资源管理、连接管理、任务开发、任务运维、监控诊断等全流程功能。Use this skill as the entrypoint when the user expresses a concrete Flink intent on a concrete object, such as installing `volc_flink`, listing projects, inspecting catalog tables, configuring Kafka endpoints, creating SQL/JAR jobs, stopping/restarting jobs, checking logs/metrics, or diagnosing checkpoint/OOM failures. Always trigger when the request includes an action + target object in the Flink domain, rather than only generic words like "Flink" or "任务".

ClawHub Agent Skills author: Cui Wenzheng v1.0.4 MIT-0 61 files body ≈ 1 309 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 59/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

AnalyzerInfrastructureData 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
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
75
Run on models
none yet
Process rating
C
59/100
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

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: 7. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "required_binaries"
    • note frontmatter-key unknown frontmatter key "may_access_config_paths"
    • note frontmatter-key unknown frontmatter key "credentials"

    Process rating: all ten parameters 59/100

    • 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
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 74 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1309 tokens
    • 100Running it twice. No mutating operations

    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
    • -253 emoji in the instructions: noise for the model
    • +1No license
    • +2Single-language instructions
    • +3Description length 548: enough signal without eating the budget
    • +4Structure: 30 headings
    • +3Step-by-step instructions: 74 items

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.

    External checks

    ClawHub: suspicious
    This Flink administration skill is mostly legitimate, but it mixes read-only framing with real configuration-changing and credential-sensitive workflows that should be reviewed before use.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026