SKILLEMALL.ai

AC deliberate-practice-for-manual-skills

Use when you want to quickly acquire, improve, or master a specific manual, trade, craft, or embodied skill (e.g., welding technique, instrument playing, knot tying precision, tool handling, gardening methods). The agent designs personalized deliberate practice regimens, breaks down the skill, generates drills, tracks progress with logs, provides feedback loops, and adjusts based on your reports. You focus exclusively on the physical repetition, execution, and embodied learning.

ClawHub Agent Skills author: HowToUseHumans v1.0.0 MIT-0 2 files body ≈ 2 271 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process C 62/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorAI and agentsInfrastructureData and analyticstype 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
C
62/100
Has gaps
Inputs and preconditions w 11
0
When it triggers w 12
20
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 62/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 2 mutating operations with no state check
    • 40Result and completion. Does not say what the result is
    • 65Failures and branches. 3 branches
    • 85Steps. 61 steps, 3 vague phrases
    • 100Tools and files. No external tools needed
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2271 tokens
    • 100Progress reporting. Reports progress
    • low 10 top-level sections: this looks like several domains in one skill

    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
    • +1No license
    • +2Single-language instructions
    • +3Description length 483: enough signal without eating the budget
    • +4Structure: 16 headings
    • +3Step-by-step instructions: 61 items

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

    External checks

    ClawHub: clean
    This is a plain-text coaching skill for planning and tracking manual skill practice, with no evidence of hidden code execution or malicious behavior.
    LLM: benign (high) · VirusTotal: · 29 May 2026