SKILLEMALL.ai

AD skill-isolator

Project-based skill isolation and management. Enables different projects to use different skill sets with automatic loading based on current working directory. Supports multiple skill sources (clawhub, local, git, url) with priority-based resolution, version locking, and auto-sync. Use when: (1) working in a project with .openclaw-skills.json, (2) need to manage project-specific skills, (3) want to isolate skills between projects, (4) need to install skills from clawhub or other sources.

ClawHub Agent Skills author: Criss_Su v1.0.0 MIT-0 13 files body ≈ 1 509 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process D 48/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureSoftware developmentInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
82
Run on models
none yet
Process rating
D
48/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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: 13. 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 48/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 20When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (node) that frontmatter does not declare
    • 100Steps. 13 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1509 tokens
    • 100Running it twice. No mutating operations
    • 100Progress reporting. Reports progress
    • low 14 top-level sections: this looks like several domains in one skill

    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
    • -214 emoji in the instructions: noise for the model
    • -44 reference files, but SKILL.md never points to them: the model will not open them
    • +2Single-language instructions
    • +3Description length 492: enough signal without eating the budget
    • +4Structure: 41 headings
    • +3Step-by-step instructions: 13 items
    • +4Has examples (19 code blocks)
    • +3All 3 scripts are documented
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.

    External checks

    ClawHub: suspicious
    This skill has a legitimate project-skill-management purpose, but it can install skills and even run shell-injected commands from project configuration without enough user review or validation.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026