SKILLEMALL.ai

AB karpathy-guidelines

engineering execution guardrails for coding, implementing features, fixing bugs, debugging failures, reviewing diffs, refactoring code, simplifying overbuilt solutions, and planning multi-step code changes. use for choosing implementation approaches, editing code safely, reviewing correctness and scope, reducing unnecessary complexity, surfacing hidden assumptions, deciding what belongs in deterministic code rather than model judgment, defining concrete verification steps, and keeping software tasks to the smallest effective change.

ClawHub Agent Skills author: gmvp3 v1.0.3 MIT-0 3 files body ≈ 1 609 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 75/100 · Nearly there — weak spots: inputs and preconditions, consistency, running it twice

ReferenceSoftware developmenttype 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
B
75/100
Nearly there
Inputs and preconditions w 11
0
Running it twice w 4
30
Consistency w 8
40
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: 3. 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 75/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 2 mutating operations with no state check
    • 40Consistency. Frontmatter name (karpathy-guidelines) differs from the folder (karpathy-engineering-guidelines)
    • 50When it triggers. No condition that starts the skill
    • 100Tools and files. No external tools needed
    • 100Steps. 62 steps
    • 100Result and completion. Output format and completion criterion are stated
    • 100Failures and branches. 3 branches, has a failure section
    • 100Execution cost. Instruction body is 1609 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)
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +3Description length 538: enough signal without eating the budget
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 62 items
    • +3Output format is stated explicitly

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

    External checks

    ClawHub: clean
    This is a text-only engineering guidance skill that fits its stated purpose and shows no hidden access, persistence, or unsafe behavior.
    LLM: benign (high) · VirusTotal: · 29 May 2026