SKILLEMALL.ai

AC parameter-golf-monitor

Monitor the openai/parameter-golf competition leaderboard by fetching PR data from GitHub. Use this skill whenever the user asks about the parameter-golf competition, leaderboard standings, competitor scores, PR rankings, who's winning, what the current SOTA is, or wants to track competition progress. Also trigger when the user mentions "parameter golf", "val_bpb scores", "competition PRs", or asks to check/watch the leaderboard. Works for any competitor — not tied to a specific GitHub account.

ClawHub Agent Skills author: Dex v1.0.0 MIT-0 5 files body ≈ 1 093 tokens Open the sourceclawhub.ai analyzed 3 d ago

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

ReferenceGitHubInfrastructureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
97/100
safety, quality, tests
Safety 60%
100
Quality 40%
93
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
    • 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: 5. 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. 1 mutating operations with no state check
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 19 steps
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1093 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

    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +5Description quotes 3 example trigger phrases
    • +3Description length 499: enough signal without eating the budget
    • +4Structure: 11 headings
    • +3Step-by-step instructions: 19 items
    • +4Has examples (3 code blocks)
    • +3All 1 scripts are documented
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 93.

    External checks

    ClawHub: clean
    This skill is a straightforward leaderboard checker that fetches public GitHub pull request data and does not show hidden credential access or unsafe installation behavior.
    LLM: benign (high) · VirusTotal: · 29 May 2026