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AB iaterm-ws-agent

Interact with IATerm terminals via the local WebSocket API (ws://127.0.0.1:19790/ws). Use when the user asks to list workspaces, displays, or panels, view active terminal connections, send commands to a terminal, or capture/subscribe to terminal output. Also use when integrating external AI agents with IATerm.

ClawHub Agent Skills author: sutaixu v1.0.4 MIT-0 3 files body ≈ 2 083 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process B 74/100 · Nearly there — weak spots: consistency, running it twice, progress reporting

IntegrationAI and agentsInfrastructuretype 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
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
90
Run on models
none yet
Process rating
B
74/100
Nearly there
Progress reporting w 2
0
Running it twice w 4
30
Consistency w 8
40
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: 3. 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 74/100

    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 8 mutating operations with no state check
    • 40Consistency. Frontmatter name (iaterm-ws-agent) differs from the folder (iaterm-ws-client)
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 42 steps
    • 100Inputs and preconditions. Inputs and preconditions are listed
    • 100Failures and branches. 4 branches, has a failure section
    • 100Execution cost. Instruction body is 2083 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)
    • +1No license
    • +2Single-language instructions
    • +3Description length 311: enough signal without eating the budget
    • +4Structure: 25 headings
    • +3Step-by-step instructions: 42 items
    • +3Output format is stated explicitly
    • +4Has examples (13 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.

    External checks

    ClawHub: suspicious
    This skill is mostly transparent about controlling IATerm terminals, but it exposes high-impact terminal access with an under-scoped interactive JSON mode that can bypass the documented approval checks.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026