SKILLEMALL.ai

AC wps-ocr

A lightweight, high-performance file parsing tool that can quickly and accurately extract text, handwritten text, formulas, tables, documents and seals from files into Markdown structure. It supports various common file scenarios such as scanned documents, screenshots and regular photos, and is compatible with multiple file formats including JPG, PNG, BMP, HEIF and WEBP, making it an efficient tool for text digitization.

ClawHub Agent Skills author: randyliu111 v1.0.1 MIT-0 5 files body ≈ 815 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process C 56/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

GeneratorInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
75
Run on models
none yet
Process rating
C
56/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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: 5. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 56/100

  • 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
  • 30Running it twice. 2 mutating operations with no state check
  • 60Tools and files. Uses tools (web, python) that frontmatter does not declare
  • 70When it triggers. States when to use, but not when not to
  • 75Steps. 3 steps
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 815 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 424: enough signal without eating the budget
  • +4Structure: 10 headings
  • +3Step-by-step instructions: 3 items
  • +4Has examples (4 code blocks)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.

External checks

ClawHub: clean
This OCR skill clearly discloses that it sends user-provided files or URLs to WPS/Kingsoft cloud for text extraction.
LLM: benign (high) · VirusTotal: · 29 May 2026