added-typos

name

added-typos

description

Add authentic human typing errors to text documents. Simulates natural typo patterns including sticky keys, adjacent key misses, letter transpositions, and optionally dyslexic spelling or punctuation habits. Triggers on phrases like "using added-typos skill", "add typos to", "amend with added-typos", "simulate typing errors", or when user wants to make text appear naturally human-typed rather than AI-generated. Accepts any text file (.md, .txt, .docx, .html) as input.

Added-Typos Skill

Transforms sterile text into authentically human-typed output by introducing controlled, natural error patterns.

Configuration Parsing

Extract from user prompt (use defaults when unspecified):

Parameter	Values	Default
intensity	light (1-2%), moderate (3-5%), heavy (7-10%), or percentage	moderate
profile	keyboard-hardware, speed-typist, fatigue, balanced	balanced
dyslexic	true/false	false
punctuation	true/false	false

Example triggers:

• "add typos to draft.md" → all defaults
• "amend report.txt with added-typos, heavy intensity" → heavy + balanced
• "simulate typing errors, speed-typist profile with punctuation habits" → moderate + speed-typist + punctuation enabled

Preservation Rules (Always Active)

Never introduce errors into:

• URLs: https?://\S+
• Emails: \S+@\S+\.\S+
• Code blocks: fenced ``` blocks and inline code
• Numbers and dates: \d+ patterns, date formats
• Markdown syntax: #, **, *, _, [](), >, - list markers

Core Error Patterns

1. Sticky Keys (Repetition/Omission)

High-frequency letters may double or drop. See references/qwerty-mapping.md for frequency weights.

Letter	Sticky Weight	Example (double)	Example (drop)
e	0.15	"thee"	"th"
t	0.12	"thatt"	"tha"
a	0.10	"thaat"	"tht"
o	0.09	"tooo"	"to" (for "too")
i	0.09	"thinkiing"	"thnking"
n	0.08	"thinkinng"	"thikig"

Probability: 60% double, 40% drop (when sticky triggers).

2. Adjacent Key Errors

Finger misses target key, hits neighbor. See references/qwerty-mapping.md for full adjacency map.

Error types:

• Substitution: wrong key replaces correct → "thr" for "the" (e→r)
• Insertion: extra key added → "thew" for "the" (w inserted)

Probability: 70% substitution, 30% insertion.

3. Transposition

Adjacent letters swap positions within word.

Examples: "teh" for "the", "freind" for "friend", "recieve" for "receive"

Probability weight: higher for common letter pairs (th, ie, ei, er).

Intensity Calculation

Calculate target error count per 100 words:

Intensity	Errors per 100 words
light	1-2
moderate	3-5
heavy	7-10

Distribute errors across pattern types based on active profile.

Workflow

1. Parse configuration from user prompt
2. Load profile from references/pattern-profiles.md
3. If dyslexic enabled: load references/dyslexic-patterns.md
4. If punctuation enabled: load references/punctuation-habits.md
5. Tokenize input text, marking preservation zones
6. Calculate error budget based on intensity and word count
7. Distribute errors across patterns per profile weights
8. Apply errors randomly across eligible tokens
9. For fatigue profile: weight errors toward document end
10. Output modified text

Profile Selection Guide

Profile	Best For	Dominant Patterns
balanced	General authenticity	Even mix of all patterns
keyboard-hardware	Simulating worn keyboards	Sticky keys (60%), adjacent (30%), transposition (10%)
speed-typist	Fast typing simulation	Adjacent (50%), dropped letters (30%), transposition (20%)
fatigue	Long documents, tired writer	Progressive: clean start → heavy errors at end

See references/pattern-profiles.md for detailed weights.

Output

Return the modified text with errors applied. Do not annotate or highlight the errors—output should read as natural human-typed text.