AC persian-documents
Generate production-quality Persian documents with correct RTL layout, bidirectional text handling, and professional typography. Use this skill whenever the user asks to create Persian documents — reports, letters, articles, technical documentation, resumes, PDFs, Word documents, or any document containing Persian text mixed with English, numbers, code, URLs, or other LTR content. Also trigger when the user asks to "fix RTL" or "fix direction" in a Persian document, or when a document needs to be regenerated because Persian text rendered incorrectly. This skill is NOT just for writing Persian prose — it is for producing documents where the final rendered output is typographically correct, structurally sound, and ready for real-world use.
Generate production-quality Persian documents with correct RTL layout, bidirectional text handling, and professional typography.
As a process C 56/100 · Has gaps — weak spots: inputs and preconditions, failures and branches, running it twice
How to improve
- 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
-
low Obfuscation
uni-zero-widthscripts/validate_doc.py:41Zero-width / invisible characters (possible hidden text) (4 occurrences) (a stray character, not a sequence)ZWNJ = '␀'
stray character
Files scanned: 10. 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 56/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 2 mutating operations with no state check
- 60Tools and files. Uses tools (node) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70When it triggers. States when to use, but not when not to
- 85Steps. 78 steps, 1 vague phrases
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1710 tokens
- low 10 top-level sections: this looks like several domains in one skill
- medium 5 test cases, all positive: not one "should refuse" or "should ask first"
- low No test case covers injection arriving through data
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
- +4Description does not say when NOT to use the skill (false activations)
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +5Description quotes 2 example trigger phrases
- +3Description length 747: enough signal without eating the budget
- +4Structure: 20 headings
- +3Step-by-step instructions: 78 items
- +3Output format is stated explicitly
- +4Reference files are cited in the instructions (2 of 2)
- +3All 3 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 95.