SKILLEMALL.ai

AC skill-router

Context-based skill auto-routing + federated skill composition. Analyzes user input to auto-select single or multiple skills and execute in order. First gateway for all requests. Use on every request to determine optimal skill combination.

ClawHub Agent Skills author: mupengi-bot v1.0.0 3 files body ≈ 1 751 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process C 58/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorInfrastructuretype 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
C
58/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
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: 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 58/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 6 mutating operations with no state check
    • 40Consistency. Frontmatter name (skill-router) differs from the folder (mupeng-skill-router)
    • 100Tools and files. No external tools needed
    • 100Steps. 35 steps
    • 100Failures and branches. 10 branches, has a failure section
    • 100Execution cost. Instruction body is 1751 tokens
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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
    • +1No license
    • +2Single-language instructions
    • +3Description length 239: enough signal without eating the budget
    • +4Structure: 15 headings
    • +3Step-by-step instructions: 35 items
    • +4Has examples (5 code blocks)

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

    External checks

    ClawHub: suspicious
    This skill is a broad automatic router that can run and chain other skills, including account and deployment workflows, without enough clear scoping or user control.
    LLM: suspicious (high) · VirusTotal: suspicious · 28 May 2026