SKILLEMALL.ai

AA daily-dungeon-challenger

Reframe a day into a main dungeon and side quests with clear win conditions, time budgets, fallback modes, and reward prompts. Use for daily planning, morning starts, midday replans, or low-energy recovery.

ClawHub Agent Skills author: haidong v1.0.0 MIT-0 3 files body ≈ 600 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process A 82/100 · Runs to the end — weak spots: when it triggers, running it twice, progress reporting

ProcedureAI and agentsPersonal productivitytype and topics are labelled automatically from the skill text
JSON
Technical rating
A
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
83
Run on models
none yet
Process rating
A
82/100
Runs to the end
Progress reporting w 2
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 82/100

    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 3 mutating operations with no state check
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 29 steps
    • 100Result and completion. Output format and completion criterion are stated
    • 100Failures and branches. 4 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 600 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
    • +4Description does not say when NOT to use the skill (false activations)
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +3Description length 206: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 29 items
    • +3Output format is stated explicitly

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.

    External checks

    ClawHub: clean
    This skill is internally consistent: it reads its own SKILL.md and returns a descriptive planning card without requesting credentials, calling external services, or installing software.
    LLM: benign (high) · VirusTotal: benign · 15 Apr 2026