SKILLEMALL.ai
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BC ocas-look

Converts user-provided images into validated, decision-ready action drafts. Routes images by inferred intent across domains: events from flyers, macros from meal photos, places to save, products to price, receipts to log, documents to file, civic issues to report. Supports reverse image search via Yandex and Google. NOT for generic OCR, computer vision research, or surveillance.

ClawHub Hermes author: Indigo Karasu v2.3.1 MIT-0 23 files · 1 script body ≈ 2 657 tokens Open the sourceclawhub.ai↗ analyzed 6 d ago

Converts user-provided images into validated, decision-ready action drafts.

As a process C 51/100 · Has gaps — weak spots: result and completion, inputs and preconditions

AnalyzerData and analyticsPersonal productivityAI and agentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Hermes Agent
JSON
Technical rating
B
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
81
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
When it triggers w 12
50
the three weakest of ten parameters · all ten

How to improve

  1. For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
For the model run — optional
  • 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: 22. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 381 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • note frontmatter-key unknown frontmatter key "warning"
  • note frontmatter-key unknown frontmatter key "source"
  • note frontmatter-key unknown frontmatter key "includes"
  • note frontmatter-key unknown frontmatter key "triggers"

Process rating: all ten parameters 51/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 50When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
  • 60Consistency. The Hermes dialect needs category and tags
  • 85Steps. 71 steps, 2 vague phrases
  • 100Execution cost. Instruction body is 2657 tokens
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • low 25 top-level sections: this looks like several domains in one skill
  • medium 3 test cases, all positive: not one "should refuse" or "should ask first"

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
  • +3Output format is not stated: the model decides each time
  • -31 of 1 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +3Description length 381: enough signal without eating the budget
  • +4Structure: 25 headings
  • +3Step-by-step instructions: 71 items
  • +4Has examples (3 code blocks)
  • +4Reference files are cited in the instructions (14 of 14)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.

External checks

ClawHub: suspicious
The skill's image-to-action purpose is mostly clear, but it also installs persistence and silent self-updates from GitHub, which users should review before installing.
LLM: suspicious (high) · 23 Sept 2026