# Acu Nugget Recall

> Tactic: Extract atomic units from one paper and score how much of a caller-supplied summary covers. Use for ACU-style binary or Nugget-style ternary recall checks; cannot run without a target summary.

- Skill: `yogsoth-ai/acu-nugget-recall` (Agent Skill)
- Install (CLI): `npx skillmds@latest add yogsoth-ai/acu-nugget-recall`
- Raw SKILL.md: https://api.skillmd.com/api/skills/yogsoth-ai/acu-nugget-recall/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: yogsoth-ai (https://skillmd.com/u/yogsoth-ai)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/yogsoth-ai/acu-nugget-recall

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# ACU / Nugget Recall

## Orchestration Pattern

1. Require `target_summary`; never generate the scored summary inside this
   tactic.
2. Fetch the paper and create `acu-nugget-recall/`.
3. Extract units before exposing the summary to the unit-writing step. ACU
   uses extracted/binary units; Nugget uses authored, importance-tagged units.
4. Match all units against `target_summary` in one call.
5. Aggregate the results and write `03-recall-aggregate.json`.

Write `01-atomic-unit-writing.json`, `02-atomic-unit-matching.json`, and
`03-recall-aggregate.json`. Record the summary source. Report every unmatched
unit, not just the score. For a single-summary Nugget run, carry the method's
weak per-topic reliability caveat alongside the number.