SKILLEMALL.ai

AD prefect-flow-builder

Build, modify, and review Prefect-based offline orchestration in this repository. Use when adding a new Prefect flow, wrapping an existing offline computation as a flow or task, editing prefect.yaml, splitting deployments by resource profile, configuring resources or concurrency, or aligning CI, Prefect, and Kubernetes deployment behavior.

ClawHub Agent Skills author: ExenVitor v1.0.0 MIT-0 8 files body ≈ 1 273 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process D 45/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerKubernetesInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
Run on models
none yet
Process rating
D
45/100
Unfinished process
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: 8. 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 45/100

    • 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
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 16 mutating operations with no state check
    • 40Consistency. Frontmatter name (prefect-flow-builder) differs from the folder (k8s-prefect-flow-builder)
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 65Failures and branches. 3 branches
    • 100Steps. 50 steps
    • 100Execution cost. Instruction body is 1273 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
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +3Description length 341: enough signal without eating the budget
    • +4Structure: 6 headings
    • +3Step-by-step instructions: 50 items
    • +4Reference files are cited in the instructions (5 of 5)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: clean
    This is a documentation-style helper for building Prefect workflows, with no executable code or hidden behavior found.
    LLM: benign (high) · VirusTotal: · 29 May 2026