CLR-001
Context default
layer: word
Prefer the precise familiar word
IF two words are equally accurate AND one is more familiar to the audience, THEN use the familiar word ELSE keep the precision-bearing term.
Why the rule exists
Familiarity reduces decoding effort when precision is unchanged.
Condition
The rule fires when this evaluates true. Paths marked below must be present in the fact base; the engine reports the rest rather than guessing them.
- ALL
- word.candidate_count gte 2
- word.candidates.equal_accuracy eq true
Facts this rule reads
| Path | Source |
|---|---|
word.candidate_count |
You supply it |
word.candidates.equal_accuracy |
You supply it |
Then
- select — target
word
Else
- retain — target
current_text, No triggering condition is present.
LAKA
- Smallest sufficient intervention
- Yes
- Primary axes
Sources
-
Principles of plain language — Digital.gov / U.S. General Services Administration
link
Design content so the intended audience can find, understand, and use it. -
Microsoft Writing Style Guide — Microsoft
link
Warm, clear, concise, helpful technical communication. -
Making Content Usable for People with Cognitive and Learning Disabilities — W3C
link
Clear words, simple voice and tense, explicit instructions, and supportive structure. -
On Writing Well — William Zinsser
Clarity, simplicity, voice, and nonfiction craft.
The raw rule record
Verbatim from 11-clarity-style-rules.json. Also available at /v1/rules/CLR-001.
{
"id": "CLR-001",
"name": "Prefer the precise familiar word",
"domain": "clarity",
"layer": "word",
"strength": "context_default",
"human_logic": "IF two words are equally accurate AND one is more familiar to the audience, THEN use the familiar word ELSE keep the precision-bearing term.",
"when": {
"all": [
{
"path": "word.candidate_count",
"operator": "gte",
"value": 2
},
{
"path": "word.candidates.equal_accuracy",
"operator": "eq",
"value": true
}
]
},
"then": [
{
"action": "select",
"target": "word",
"by": "audience_familiarity"
}
],
"else": [
{
"action": "retain",
"target": "current_text",
"reason": "No triggering condition is present."
}
],
"unless": [],
"because": "Familiarity reduces decoding effort when precision is unchanged.",
"diagnostics": [],
"examples": {},
"source_ids": [
"WEB-002",
"WEB-004",
"WEB-006",
"BK-013"
],
"laka": {
"smallest_sufficient_intervention": true,
"primary_axes": [
"scope",
"depth",
"magnitude",
"reversibility"
]
}
}
Other clarity rules
- CLR-002 Define necessary jargon IF a domain term is necessary AND the intended reader may not know it, THEN define it at first use and use it consistently ELSE replace it with plain language. Context default
- CLR-003 Expand unfamiliar abbreviations IF an abbreviation is not universally familiar to the audience, THEN spell it out at first use and pair it with the abbreviation ELSE retain. Context default
- CLR-004 One term per concept IF multiple terms refer to the same technical concept without rhetorical need, THEN select one preferred term and replace the variants ELSE retain. Context default
- CLR-005 One concept per term IF the same term denotes multiple concepts in one context, THEN rename or qualify the concepts ELSE retain. Hard constraint
- CLR-006 Replace vague reference words IF THIS, THAT, IT, THEY, FORMER, or LATTER has an uncertain referent, THEN repeat or summarize the referent ELSE retain. Hard constraint
- CLR-007 Quantify actionable vagueness IF vague quantity, frequency, time, or probability affects a decision, THEN provide a range, threshold, date, or defined category ELSE retain approximate language. Context default
- CLR-008 Use concrete examples after abstractions IF a central abstraction lacks a concrete instance AND the audience knowledge gap is moderate or large, THEN add one representative example ELSE retain. Heuristic
- CLR-009 State implied steps for novice readers IF success requires an unstated inference that a novice may not make, THEN state the step or prerequisite ELSE retain expert compression. Context default