SKILLEMALL.ai

BF 💕 Ellya Skill

name: Ellya description: OpenClaw virtual companion skill. Use it to bootstrap runtime files (SOUL and base image), guide user personalization, learn and store style prompts from uploaded photos, a...

modbender/skill-library-mcp Agent Skills author: modbender MIT 5 files body ≈ 1 586 tokens Open the sourcegithub.com analyzed 2 d ago

name: Ellya description: OpenClaw virtual companion skill.

As a process F 41/100 · Will not run — References files that are not bundled: assets/base.*, assets/base.<ext>, assets/base.<original_extension>

ProcedureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
85/100
safety, quality, tests
Safety 60%
95
Quality 40%
70
Run on models
none yet
Process rating
F
41/100
Will not run
References files that are not bundled: assets/base.*, assets/base.<ext>, assets/base.<original_extension>
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

How to improve

  1. The text references files that are not there: add them or drop the references.
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 · 1

✓ No critical or high findings

Medium and low: 1
  • medium Broad scope meta-agent-memory-dump templates/SOUL.md
    Agent memory / workspace files bundled with the skill (1) — likely a workspace dump with personal data or tokens
    templates/SOUL.md

Files scanned: 5. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning missing-ref reference to a missing file: assets/base.*
  • warning missing-ref reference to a missing file: assets/base.<ext>
  • warning missing-ref reference to a missing file: assets/base.<original_extension>

Process rating: all ten parameters 41/100

Will not run. References files that are not bundled: assets/base.*, assets/base.<ext>, assets/base.<original_extension>
  • 0Tools and files. 3 referenced file(s) missing: assets/base.*, assets/base.<ext>, assets/base.<original_extension>
  • 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
  • 40Consistency. Frontmatter name (💕 Ellya Skill) differs from the folder (ellya)
  • 100Steps. 78 steps
  • 100Failures and branches. 5 branches, has a failure section
  • 100Execution cost. Instruction body is 1586 tokens
  • 100Running it twice. Mutating operations check current state
  • low The response is described with custom markup (5 tags): a typed call is more reliable

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 200: enough signal without eating the budget
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 78 items
  • +4Has examples (4 code blocks)
  • +3All 1 scripts are documented

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