disambiguation-score

name

disambiguation-score

description

One repeatable pass that keeps fak's growing namespace CRYSTAL-CLEAR - each similar-sounding concept (cache / vCache / KV cache / cachemeta / the provider prompt-cache; guard vs gate; the two witnesses) given one canonical name, a written definition, and an explicit line drawn against the siblings it is confused with. Runs the concept-disambiguation scorecard (tools/concept_disambiguation_scorecard.py) over a data dir of confusable-concept rows cross-checked against the tree (the grounding token must appear in the production corpus; the glossary anchor must exist; a distinct_from reference must resolve), turns each HARD defect into a required fix (rename a true canonical collision, write a missing definition, draw + anchor a missing distinction, replace a fabricated grounding) and each uncovered tree token into a coverage row to ADD, retires disambiguation-debt worst-first, re-measures to PROVE the debt dropped, and commits only the scorecard lane by explicit path. The NAMING-clarity counterpart of conflation-score (number provenance) and product-score (can a person use the concept). Use after adding a confusable name, when two concepts blur, or on a /loop cadence to keep the vocabulary from fogging as it grows.

disambiguation-score - the crystal-clarity / naming pass

An instance of the generic scorecard doctrine. Read that for the five laws and the RSI loop; this file is the per-surface specialization.

Why this scorecard exists

fak has grown a large vocabulary, and several roots are badly overloaded. The word "cache" alone names at least a dozen distinct things (KV cache, vCache, cachemeta, the provider prompt-cache, ViewCache, enginecache, RadixKV, ...); "guard" and "gate" blur; "witness" means two unrelated ideas. As the system grows, a reader cannot tell the concepts apart - and a name a reader cannot pin is a name they will misuse.

The crystal-clarity law, in one line: every distinct concept gets one canonical name, a written definition, and an explicit line drawn against the siblings it is confused with - and that distinction lives in a doc that exists, not tribal memory.

This is orthogonal to its two easily-confused siblings (an irony the glossary notes): conflation-score keeps every reported NUMBER labeled by provenance (WITNESSED vs OBSERVED); product-score asks whether a person can USE a concept. This one asks whether the NAME is unambiguous.

The KPIs (what it grades)

• well_formed (HARD) - required fields present, enums in the closed vocabulary, unique id, family declared.
• canonical_unique (HARD) - no two concepts share THE canonical name. A real collision is fixed by a RENAME, never a note.
• defined (HARD) - every concept carries one distinguishing definition sentence.
• disambiguated (HARD) - the heart: a concept in a family with >= 1 positioned sibling must carry a distinction line AND a distinct_from that resolves to a real catalog id. A confusable concept that never says what it is NOT is the core debt.
• grounded (HARD) - the grounding token must appear in the production corpus by STRICT identity (a fabricated policyloaded that merely contains policy is refused).
• anchored (HARD) - a concept claiming crystal clarity must have its distinction written in a glossary_anchor that exists; any non-empty anchor must resolve on disk.
• clarity_consistent (HARD) - the declared verdict must match the evidence (crystal / defined / drifting / colliding / undocumented). Calling an unanchored concept crystal is the overclaim this catches.
• kind_grounding / hierarchy (SOFT) - advisory: kind agrees with grounding; an optional parent resolves and does not cycle.

Plus coverage: for each watched family the scorecard DISCOVERS the confusable tokens in the tree (a token counts only when it spans >= min_files production files, or is a package/dir name, or a doc heading), and coverage_debt is the count not yet positioned. This is the ungameable engine - you cannot shrink the universe by editing data, only by disambiguating the real concept.

The pass (the shared five-step loop)

1. Run it - python tools/concept_disambiguation_scorecard.py (work-list), --json (payload), --critical (worst-first), --gaps (the coverage backlog by family), --compare baseline.json (prove the drop).
2. Retire disambiguation-debt worst-first - fix the heaviest KPI by changing REALITY: rename a true canonical collision, write a missing definition, draw the distinction + point distinct_from at a real sibling id, replace a fabricated grounding with a real token. Close a real coverage gap atomically with fak concept position --id ID --canonical NAME --family FAMILY --definition TEXT --distinction TEXT --kind KIND --grounding TOKEN --grounding-kind KIND --glossary docs/fak/concept-glossary.md --distinct-from SIBLING_ID; classify a genuine incidental/false-positive discovery with fak concept classify --family FAMILY --token TOKEN --category CATEGORY --reason TEXT. Preview either mutation with --dry-run --json. Never hand-edit a row, family classification, glossary anchor, and generated README as separate operations.
3. Weigh the SOFT signals - fix the cheap real ones (kind/grounding, a dangling parent); do not chase them to zero.
4. Re-measure + prove - --compare prints the debt delta; the positioned rows must stay clean (0 clarity-debt) while coverage rises.
5. Commit exactly the files reported by the authoring verb - verify with --critical and regenerate/check the scorecard baseline when the measured metric changes. Use fak commit --preview followed by fak commit --path for each reported path; never git add -A. End the subject with the (fak <leaf>) trailer.

The anti-gaming rule (specific to this surface)

Disambiguate a concept by making the name + the written distinction real, never by weakening the cross-check. A coverage gap is closed by ADDING an honest, grounded, anchored row - not by dropping the family root so the token stops being discovered, and not by listing a distinct_from id that does not exist. A crystal verdict is earned by writing the distinction into the glossary - not by pointing the anchor at a doc that happens to exist. The grounding cross-check is STRICT identity on purpose: if a real concept's token genuinely is not in the production corpus, the honest fix is to rename the concept toward the name the code actually uses, not to relax the match.

Adding a surface

When a new overloaded root appears (a fresh *-thing family proliferating across the tree), add a family entry to _meta.json (roots, optional ignore inflections, optional exclude substrings, min_files); the scorecard then discovers its confusable tokens and the coverage backlog grows until you position them. Keep the glossary (docs/fak/concept-glossary.md) as the single anchor the crystal rows cite.

ASCII gotcha

Keep the scorecard source + data + glossary ASCII-only (use - for a dash, straight quotes). The repo's provenance pre-commit hook crashes on non-cp1252 UTF-8 before its own escape fires.