SKILLEMALL.ai

AB autopilot

Fully autonomous end-to-end task run with NO human gates — pulls the work item (via the azure-devops or github skill if installed, or takes an inline task description), plans against the real codebase, executes incrementally with per-increment verification, writes and runs tests, code-reviews and fixes blocking findings, then STOPS before any commit/push/PR and delivers an evidence-backed report with every assumption logged. Replaces interactive questions with a documented-assumption protocol; halts only for destructive actions, missing access, or unimplementable specs. Use this skill whenever the user says "autopilot", "/autopilot", "run task <id> autonomously", "work this task end to end without asking", "full autonomy on this", "do the whole task, skip commits and PR", or launches a headless run with a task id — even if they don't explicitly say "autopilot skill". Do not use when the user wants interactive planning gates (use task-executor) or wants commits/PRs created.

ClawHub Agent Skills author: Dennis Rongo v1.0.0 MIT-0 2 files body ≈ 2 524 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process B 78/100 · Nearly there — weak spots: result and completion, inputs and preconditions, running it twice

AnalyzerGitHubAzureSoftware developmentInfrastructureData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
90
Run on models
none yet
Process rating
B
78/100
Nearly there
Inputs and preconditions w 11
0
Running it twice w 4
30
Result and completion w 14
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: 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 78/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 18 mutating operations with no state check
    • 40Result and completion. Does not say what the result is
    • 100Tools and files. No external tools needed
    • 100Steps. 24 steps
    • 100When it triggers. States when to use and when not to
    • 100Failures and branches. 5 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2524 tokens
    • 100Progress reporting. Reports progress
    • 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

    • +3Description length 987: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 7 example trigger phrases
    • +4Description says when NOT to use the skill
    • +4Structure: 16 headings
    • +3Step-by-step instructions: 24 items
    • +4Has examples (0 code blocks)

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

    External checks

    ClawHub: clean
    This skill openly enables hands-off codebase work with safeguards, but users should run it only when they intentionally want autonomous file edits and command execution.
    LLM: benign (high) · VirusTotal: · 16 Aug 2026