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AC iaiops-renewables

Renewables edition of iaiops — solar PV plants and wind farms: PV inverters / string combiners and wind-turbine controllers over Modbus (SUN2000 / Growatt / generic wind-turbine templates), plant SCADA over OPC-UA, and MQTT-Sparkplug telemetry, plus the cross-protocol brain (PdM, downtime, OEE, alarm) and a renewables signature tool pv_performance (underperforming-string detection). Use when the task mentions solar / 光伏 / PV / photovoltaic, inverter / 逆变器 / 组串 / string / combiner, irradiance / 辐照 / POA, wind / 风电 / turbine / 风机 / nacelle / pitch / yaw, plant SCADA, performance ratio, soiling / 积灰 / shading / 遮挡, or 电站. Read-first; this edition's tool surface is read-only.

ClawHub Agent Skills author: wei zhou v0.27.0 MIT-0 2 files body ≈ 1 464 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

Renewables edition of iaiops — solar PV plants and wind farms: PV inverters / string combiners and wind-turbine controllers over Modbus (SUN2000 / Growatt /…

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureSecurityAI 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%
80
Run on models
none yet
Process rating
C
53/100
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: 2. 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 53/100

    • 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
    • 20When it triggers. No condition that starts the skill
    • 100Tools and files. No external tools needed
    • 100Steps. 33 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1464 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
    • +1No license
    • +2Single-language instructions
    • +3Description length 680: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 33 items

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

    External checks

    ClawHub: suspicious
    The skill is mostly coherent as an industrial renewables analysis helper, but it claims to be read-only while listing publish, push, and export tools that can transmit or affect external systems.
    LLM: suspicious (high) · 3 Sept 2026