SKILLEMALL.ai

AB autogrind

Let the agent work continuously and fully autonomously without stopping. Use this skill for long-running grind sessions across code, ML/data, research, design, or writing. Trigger phrases: /autogrind, /自己动, 'keep working don't stop', 'grind on this', 'work until I say stop', 'autogrind this', 'keep improving'. Use even when the user simply says 'keep going' or implies uninterrupted autonomous progress without naming AutoGrind explicitly.

ClawHub Agent Skills author: Tony L. He v1.0.1 MIT-0 2 files body ≈ 3 619 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 69/100 · Nearly there — weak spots: result and completion, inputs and preconditions, running it twice

GeneratorAI and agentsSoftware developmentInfrastructuretype 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
B
69/100
Nearly there
Result and completion w 14
0
Inputs and preconditions w 11
0
Running it twice w 4
30
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 69/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 7 mutating operations with no state check
    • 70Failures and branches. 5 branches
    • 100Tools and files. No external tools needed
    • 100Steps. 45 steps
    • 100When it triggers. States when to use and when not to
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3619 tokens
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low The response is described with custom markup (4 tags): a typed call is more reliable

    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
    • -5TODO / placeholder text left in the skill
    • +2Single-language instructions
    • +3Description length 441: enough signal without eating the budget
    • +4Structure: 16 headings
    • +3Step-by-step instructions: 45 items
    • +4Has examples (2 code blocks)
    • +1License stated

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

    External checks

    ClawHub: suspicious
    This instruction-only skill is transparent about autonomous work, but it asks the agent to keep acting indefinitely and to weaken approval controls, so users should review it carefully before use.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026