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AD ibm-ace-copilot

Use this skill when working with IBM App Connect Enterprise (ACE) 12.0, including message flow development, ESQL scripting, BAR file deployment, integration node/server management, and troubleshooting. Trigger when the user mentions: IBM ACE, App Connect Enterprise, message flows, ESQL, Compute nodes, BAR files, mqsideploy, mqsistart, mqsistop, mqsicreatebroker, integration nodes, integration servers, MQ input/output nodes, HTTP nodes, ACE Toolkit, ACE CLI, broker deployment, message routing, flow debugging, user trace, service trace, ACE development, IBM integration, or any ACE-specific development tasks such as reading JIRA tickets and implementing changes in ACE flows, committing changes, or opening PRs for ACE projects. When in doubt, trigger this skill.

ClawHub Agent Skills author: Shoaib Khan v1.0.0 MIT-0 9 files body ≈ 489 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process D 45/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches

IntegrationJiraInfrastructuretype 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
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
85
Run on models
none yet
Process rating
D
45/100
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
    • 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: 8. 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 45/100

    • 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
    • 30Running it twice. 7 mutating operations with no state check
    • 40Consistency. Frontmatter name (ibm-ace-copilot) differs from the folder (ace-copilot)
    • 60Tools and files. Uses tools (node) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 17 steps
    • 100Execution cost. Instruction body is 489 tokens
    • medium 3 test cases, all positive: not one "should refuse" or "should ask first"

    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
    • +2Single-language instructions
    • +3Description length 768: enough signal without eating the budget
    • +4Structure: 4 headings
    • +3Step-by-step instructions: 17 items
    • +4Reference files are cited in the instructions (6 of 6)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.

    External checks

    ClawHub: suspicious
    This appears to be a legitimate IBM ACE helper, but it needs review because it includes broad activation plus powerful deployment, credential, and diagnostic guidance without enough safeguards.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026