SKILLEMALL.ai

AB mano-afk

Autonomous full-cycle app builder — PRD, architecture, code, deployment, testing, and bug fixing from a natural language description. Remembers user preferences and development pitfalls to self-evolve across projects. Use when the user explicitly requests a fully autonomous end-to-end app build.

ClawHub Agent Skills author: HanningWang v1.0.8 MIT-0 9 files body ≈ 3 284 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 76/100 · Nearly there — weak spots: result and completion, running it twice

GeneratorInfrastructureSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
82
Run on models
none yet
Process rating
B
76/100
Nearly there
Running it twice w 4
30
Result and completion w 14
40
Tools and files w 18
60
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: 9. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "homepage"

    Process rating: all ten parameters 76/100

    • 30Running it twice. 19 mutating operations with no state check
    • 40Result and completion. Does not say what the result is
    • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 85Steps. 44 steps, 1 vague phrases
    • 100When it triggers. States when to use and when not to
    • 100Failures and branches. 8 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3284 tokens
    • 100Progress reporting. Reports progress

    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
    • +1No license
    • +2Single-language instructions
    • +3Description length 296: enough signal without eating the budget
    • +4Structure: 17 headings
    • +3Step-by-step instructions: 44 items
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (7 of 7)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.

    External checks

    ClawHub: clean
    The skill is a disclosed autonomous app-building workflow with expected local project creation, testing, limited credential use, and opt-in cloud E2E behavior.
    LLM: benign (high) · VirusTotal: · 1 Jun 2026