SKILLEMALL.ai

AC asi-proxy-phase-skill

Diagnose, explain, and improve an evidence-gated, protocol-relative ASI-proxy readiness regime using K. Takahashi's pinned papers and public repositories. Use for observable-only or no-meta agent improvement, verification bottlenecks, provenance and memory failures, certified reusable capability, finite-resource phase diagnostics, paper-to-implementation lineage, multi-repository intervention planning, or iterative implementation and evaluation. Do not use for unrelated generic coding or to claim that real ASI or a scientific phase transition has been achieved.

ClawHub Agent Skills author: K. Takahashi (Kadubon) v1.1.0 MIT-0 51 files body ≈ 2 063 tokens Open the sourceclawhub.ai analyzed 2 d ago

Diagnose, explain, and improve an evidence-gated, protocol-relative ASI-proxy readiness regime using K.

As a process C 59/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

AnalyzerSoftware developmentData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
98/100
safety, quality, tests
Safety 60%
100
Quality 40%
96
Run on models
none yet
Process rating
C
59/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • 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: 26. 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 59/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 8 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 50Failures and branches. 0 branches, has a failure section
    • 100Tools and files. No external tools needed
    • 100Steps. 57 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2063 tokens
    • low No test case covers injection arriving through data

    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
    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 567: enough signal without eating the budget
    • +4Structure: 13 headings
    • +3Step-by-step instructions: 57 items
    • +4Has examples (6 code blocks)
    • +4Reference files are cited in the instructions (5 of 5)
    • +3All 6 scripts are documented
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 96.

    External checks

    ClawHub: clean
    The skill’s actions are mostly disclosed and purpose-aligned, but the inspected package appears to be missing a bundled paper index needed for normal operation.
    LLM: benign (high) · VirusTotal: · 31 Jul 2026