acquaint.deslop

The deterministic half of deslop: find the patterns that make prose read as machine-written, scaled to the reader.

How strict the check is depends on the recipient’s tolerance of AI-sounding text, recorded as ai_tolerance in their style.md (tolerant, neutral, averse; anything else counts as unknown, which is neutral):

• tolerant enforces tier E only, with looser counts;

• neutral enforces E and W;

• averse enforces E, W and S, with the tightest counts.

Findings outside the enforced tiers are still reported, marked enforced: False. The catalogue is data (acquaint/data/deslop/tells.yaml) and a keyword argument, so a list derived from the operator’s own writing can replace it without code changes.

>>> result = lint_text("Great question! This robust tool serves as a bridge.", tolerance="neutral")
>>> sorted({f["rule"] for f in result["findings"] if f["enforced"]})
['ai-vocabulary', 'chat-leftover', 'copula-avoidance']
>>> lint_text("Sending the export on Friday. Two sites, not five.")["ok"]
True

acquaint.deslop.lint_text(text: str, *, tolerance: str = 'neutral', blocklist: Iterable[str] = (), catalog: dict[str, Any] | None = None) → dict[str, Any]

Check a draft against the tells catalogue at a reader’s tolerance: {"ok", "findings", "metrics", "relational"}.

blocklist holds phrases this recipient’s card says never to use; each hit is tier E. catalog replaces the shipped catalogue (same schema as tells.yaml). An unrecognised tolerance is an error here; normalise recorded values first with normalize_tolerance().

acquaint.deslop.normalize_tolerance(value: Any) → tuple[str, str | None]

A recorded ai_tolerance as one of TOLERANCES, with a warning when it was something else.

>>> normalize_tolerance("Averse"), normalize_tolerance(None)
(('averse', None), ('unknown', None))
>>> normalize_tolerance("low")[0]
'unknown'

acquaint.deslop.recipient_card(entity: Any) → dict[str, Any]

What the check needs from a recipient’s writing card (style.md): tolerance, disclosure, blocklist, warnings.

ai_tolerance and disclosure come from the card’s frontmatter. Blocklist phrases are the items of its ## Blocklist section: the quoted phrase when an item quotes one, else the item without its source tag.

acquaint.deslop.text_metrics(text: str) → dict[str, float]

Counts the checks use: words, sentences, sentence-length variation, em-dash rate, headers, bold.

>>> text_metrics("One two three. Four five!")["sentences"]
2