Redundancy Pruner
Purpose: make the survey feel intentional by removing “looped template paragraphs” and consolidating global disclaimers, while keeping meaning and citations stable.
Role cards (use explicitly)
Compressor
Mission: remove repeated boilerplate without deleting subsection-specific work.
Do:
- •Collapse repeated disclaimers into one front-matter paragraph (not per-H3 repeats).
- •Delete repeated narration stems and empty glue sentences.
- •Keep each H3’s unique contrasts/evaluation anchors/limitations intact.
Avoid:
- •Cutting unique comparisons because they sound similar.
- •Turning pruning into a rewrite (this skill is subtraction-first).
Narrative Keeper
Mission: keep the argument chain readable after pruning.
Do:
- •Replace slide-like navigation with short argument bridges (NO new facts/citations).
- •Ensure each H3 still has a thesis, contrasts, and at least one limitation.
Avoid:
- •Generic transitions that could fit any subsection ("Moreover", "Next") without concrete nouns.
Role prompt: Boilerplate Pruner (editor)
text
You are pruning redundancy from a survey draft. Your job is to remove repeated boilerplate and make transitions content-bearing, without changing meaning or citations. Constraints: - do not add/remove citation keys - do not move citations across ### subsections - do not delete subsection-specific comparisons, evaluation anchors, or limitations Style: - delete narration and generic glue - keep one evidence-policy paragraph in front matter; avoid repeated disclaimers
Inputs
- •
output/DRAFT.md - •Optional (helps avoid accidental drift):
- •
outline/outline.yml(subsection boundaries) - •
output/citation_anchors.prepolish.jsonl(if you are enforcing anchoring)
- •
Outputs
- •
output/DRAFT.md(in-place edits)
Workflow
Use the role cards above.
Steps:
- •Identify repeated boilerplate (not content):
- •repeated disclaimer paragraphs (evidence-policy, methodology caveats)
- •repeated opener labels (e.g.,
Key takeaway:spam) - •repeated slide-like narration stems (e.g., “In the next section…”) and generic transitions
- •Pick a single home for global disclaimers:
- •keep the evidence-policy paragraph once in front matter (Introduction or Related Work)
- •delete duplicates inside H3 subsections
- •Rewrite transitions into argument bridges:
- •keep bridges subsection-specific (use concrete nouns from that subsection)
- •do not add facts or citations
- •Sanity check subsection integrity:
- •each H3 still has its unique thesis + contrasts + limitation
- •no citation-only lines and no trailing citation-dump paragraphs
- •if
outline/outline.ymlexists, use it to confirm you did not prune across subsection boundaries - •if
output/citation_anchors.prepolish.jsonlexists, treat it as a regression anchor (no cross-subsection citation drift)
Guardrails (do not violate)
- •Do not add/remove citation keys.
- •Do not move citations across
###subsections. - •Do not delete subsection-specific comparisons, evaluation anchors, or limitations.
Mini examples (rewrite intentions; do not add facts)
Repeated disclaimer -> keep once:
- •Bad (repeated across many H3s):
Claims remain provisional under abstract-only evidence. - •Better (once in front matter): state evidence policy as survey methodology, then delete duplicates in H3.
Slide navigation -> argument bridge:
- •Bad:
Next, we move from planning to memory. - •Better:
Planning determines how decisions are formed, while memory determines what evidence those decisions can condition on under a fixed protocol.
Template synthesis stem -> content-first sentence:
- •Bad:
Taken together, these approaches...(repeated many times) - •Better: state the specific pattern directly (e.g.,
Across reported protocols, X trades off Y against Z...).
Troubleshooting
Issue: pruning removes subsection-specific content
Fix:
- •Restrict edits to obviously repeated boilerplate; keep anything that encodes a unique comparison/limitation for that subsection.
Issue: pruning changes citation placement
Fix:
- •Undo; citations must remain in the same subsection and keys must not change.