SKILLEMALL.ai

AC vn-translate

Translate fiction from a source language into Vietnamese using a streaming pipeline. Read raw.md in ~12 KiB chunks with RawReader, write each translated part to out/, maintain consistent proper names and forms of address, track progress in _vartemp.json, optionally index chapter titles, then merge and export EPUB.

ClawHub Agent Skills author: kaibazax-dev v1.1.0 MIT-0 13 files body ≈ 3 819 tokens Open the sourceclawhub.ai analyzed 36 h ago

Translate fiction from a source language into Vietnamese using a streaming pipeline.

As a process C 59/100 · Has gaps — weak spots: inputs and preconditions, running it twice, progress reporting

ProcedureWriting and documentstype 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
C
59/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
Running it twice w 4
30
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: 1. 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 59/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 5 mutating operations with no state check
  • 50When it triggers. No condition that starts the skill
  • 55Failures and branches. 1 branches
  • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 85Steps. 70 steps, 1 vague phrases
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3819 tokens
  • low 16 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)
  • +1No license
  • +2Single-language instructions
  • +3Description length 315: enough signal without eating the budget
  • +4Structure: 44 headings
  • +3Step-by-step instructions: 70 items
  • +3Output format is stated explicitly
  • +4Has examples (26 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)
  • +3All 8 scripts are documented

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

External checks

ClawHub: clean
This skill is a coherent Vietnamese fiction translation workflow with local file writes and helper scripts that fit its stated purpose, though users should review cleanup commands before running them.
LLM: benign (high) · VirusTotal: · 9 Aug 2026