SKILLEMALL.ai

AC oz

Dispatch coding tasks to Warp Oz cloud agents and chain them into multi-agent pipelines — all from chat. Includes a bash wrapper covering every Oz API endpoint (runs, schedules, artifacts, agents) and a Python pipeline orchestrator that chains specialized agents (e.g., architect → developer → security → red-teamer) with automatic severity-based retry loops. Use when you want to kick off cloud coding agents, poll run status, manage cron schedules, run multi-turn conversations in a shared sandbox, or orchestrate multi-agent review pipelines. NOT for local Warp terminal usage.

ClawHub Agent Skills author: in-liberty420 v1.1.0 MIT-0 6 files · 1 script body ≈ 1 102 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 52/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

IntegrationAI and agentsInfrastructureSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
98/100
safety, quality, tests
Safety 60%
100
Quality 40%
95
Run on models
none yet
Process rating
C
52/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
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: 6. 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 52/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 2 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
    • 100Steps. 22 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1102 tokens

    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
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 580: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 22 items
    • +4Has examples (4 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)
    • +3All 2 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 95.

    External checks

    ClawHub: clean
    This skill is a disclosed Warp Oz cloud-agent integration; it uses a Warp API key to start, monitor, chain, and schedule remote coding agents, with no evidence of hidden or deceptive behavior.
    LLM: benign (high) · VirusTotal: · 29 May 2026