SKILLEMALL.ai

AC doppel

Build a consent-first, provenance-aware digital twin of a person's own writing voice from local subject-authored material, then use that writing-voice Doppel to draft or revise text for the subject's review. Use when someone wants a digital twin of their own cadence, reasoning movement, and registers across essays, technical writing, outreach, or social posts without uploading a private corpus. Not a personality twin, believed-human simulation, third-party clone, or autonomous publisher.

ClawHub Agent Skills author: Antreas Antoniou v1.0.0 MIT-0 16 files body ≈ 676 tokens Open the sourceclawhub.ai analyzed 30 h ago

Build a consent-first, provenance-aware digital twin of a person's own writing voice from local subject-authored material, then use that writing-voice Doppel…

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorWriting and documentsSales and CRMtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
86
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
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: 15. 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 51/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 2 mutating operations with no state check
    • 100Tools and files. No external tools needed
    • 100Steps. 13 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 676 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)
    • +3Output format is not stated: the model decides each time
    • -31 of 2 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +3Description length 492: enough signal without eating the budget
    • +4Structure: 3 headings
    • +3Step-by-step instructions: 13 items
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (1 of 2)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.

    External checks

    ClawHub: suspicious
    The skill is purpose-aligned and not malicious, but it handles sensitive writing samples while a promised Git ignore safeguard is missing.
    LLM: suspicious (medium) · 5 Sept 2026