SKILLEMALL.ai

AD iaiops-fab

Fab edition of iaiops — semiconductor / display (panel TFT-LCD/OLED) fab equipment over SECS/GEM (SEMI E5 SECS-II, E30 GEM, E37 HSMS) plus OPC-UA for the equipment's internal control layer, with the cross-protocol brain (downtime root-cause copilot, OEE, asset inventory, data quality). Use when the task mentions SECS/GEM, SECS-II, HSMS, GEM host, wafer, panel, fab equipment, MES equipment interface, SVID, ECID, ALID, PPID / process program, recipe list, or a semiconductor / display fab tool. Read-first, MOC-gated writes.

ClawHub Agent Skills author: wei zhou v0.27.0 MIT-0 2 files body ≈ 1 503 tokens Open the sourceclawhub.ai analyzed 2 d ago

Fab edition of iaiops — semiconductor / display (panel TFT-LCD/OLED) fab equipment over SECS/GEM (SEMI E5 SECS-II, E30 GEM, E37 HSMS) plus OPC-UA for the…

As a process D 48/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureSecurityAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
80
Run on models
none yet
Process rating
D
48/100
Unfinished process
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: 0. 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 48/100

    • 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
    • 20When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 100Steps. 35 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1503 tokens
    • 100Running it twice. No mutating operations
    • 100Progress reporting. Reports progress

    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 526: enough signal without eating the budget
    • +4Structure: 8 headings
    • +3Step-by-step instructions: 35 items

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

    External checks

    ClawHub: clean
    The skill is a coherent industrial fab-equipment diagnostics skill with disclosed high-impact equipment access and stated write safeguards, though users should note the Chinese-only runtime instructions and external package dependency.
    LLM: benign (high) · VirusTotal: · 3 Sept 2026