SKILLEMALL.ai

AC effector-ecosystem

Use when designing, reviewing, generating, or refactoring React applications built with Effector, effector-react, Farfetched, Atomic Router, @effector/next, patronum, effector-storage, forms, i18n, testing, and related Effector ecosystem tooling. For Feature-Sliced Design project structure and placement decisions, use the separate effector-fsd skill.

ClawHub Agent Skills author: Mark Davydkin v0.6.0 MIT-0 30 files body ≈ 3 426 tokens Open the sourceclawhub.ai analyzed 21 h ago

Use when designing, reviewing, generating, or refactoring React applications built with Effector, effector-react, Farfetched, Atomic Router, @effector/next…

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

AnalyzerSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
89
Run on models
none yet
Process rating
C
59/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
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: 30. 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

    • 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. 11 mutating operations with no state check
    • 40Result and completion. Does not say what the result is
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 100Steps. 87 steps
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3426 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
    • +2Single-language instructions
    • +3Description length 352: enough signal without eating the budget
    • +4Structure: 16 headings
    • +3Step-by-step instructions: 87 items
    • +4Has examples (12 code blocks)
    • +4Reference files are cited in the instructions (12 of 12)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.

    External checks

    ClawHub: clean
    The supplied scanner telemetry is clean, and no artifact-backed evidence of hidden or unsafe behavior was found.
    LLM: benign (medium) · VirusTotal: · 9 Jul 2026