Condense

Normative authority: docs/SCIPAPER_STANDARD.md. §5.3 (condense, do not accumulate) is the policy this skill executes; the policy text lives ONLY in the standard — this skill implements it and never restates a competing version. §6 rewrite eligibility defines the fidelity invariants every deletion and compression must preserve.

condense — 精简：one canonical home per fact

0. What this skill does

A whole-document sweep that removes all content which is unnecessary or already stated elsewhere in the document, then proves the result with the mechanical length gate. It is the plugin's redundancy/length action surface: paper-review dimension I detects redundancy as findings; condense executes the removal. --report-only stops after §1: the removal map is returned with no deletion applied.

The map is not built by reading. tools/condense_map.py enumerates every removable entry with the words it would free, and the pass is judged against that count: a pass that dispositions every entry and meets the map's target has condensed; a pass that reads the paper and trims a phrase here and there has not. That failure mode — a sweep that removes a few percent by hand while the map lists ten — is the reason the tool exists.

Boundary with /sci-paper:de-ai (canonical home: de-ai SKILL.md §0; mirrored here verbatim): de-ai removes the authorship fingerprint (L0-L4 signals, structural tells, voice; its Pass-3 length cap only guards its own rewrites against growth). condense removes redundancy and length (cross-document deduplication under one-canonical-home-per-fact). At the overlap (verbose AI-isms such as rule-of-three padding or connective stacking), de-ai DETECTS the tell; when the right fix is deletion rather than rewrite, the deletion EXECUTES under condense's ranked sweep.

0.1 Non-negotiable rules

1. Preference order: delete > condense-in-place > same-length rewrite. Growth is forbidden; the only exceptions are §5.3's own (author-requested new content, or a source-verified scientific necessity), each with a recorded justification.
2. Fidelity invariants (§6). Every surviving passage preserves claims, numbers, units, uncertainties, citations, named entities, comparison direction, negation, causal direction, scope, stance, qualifiers, and logical dependencies. Never delete a fact's sole support: dedup keeps exactly one canonical home; the copies are deleted or replaced by a cross-reference — the fact itself never vanishes.
3. One canonical home per fact. A number, definition, or claim stated in two places is a defect with one exception (rule 4). The canonical home is where the reader needs it — normally the most detailed, first-consumed occurrence.
4. Genre carve-out. The abstract's summary of key results and the conclusion's restatement of the take-home message are scholarly convention, NOT duplication. The map reports these entries with genre_carve_out: true and leaves them out of the default target.
5. Forward narrative. Removal never leaves a scar ("as discussed above, we omit..."); the text reads as if written short from the start.
6. Every map entry is dispositioned. Deleted, merged, or kept — and kept carries a reason a reader could check (the survivor is the sole support; the repeat is the carve-out; the "dead" label is consumed by an include the map cannot see). An entry without a disposition is an entry the pass skipped.
7. Deletions are evidence-backed. A "dead" symbol, figure, table, or definition is deleted only after a whole-document grep proves nothing consumes it; the map's condense-dead:* entries carry that grep, and any deletion outside the map records its own.

1. Measure — build the removal map

1. Read the target file completely. Resolve --field as in /sci-paper:de-ai §1 (shared style-profile convention).
2. Snapshot the length baseline before any edit: cp <file> <scratch>/length-baseline.tex (or record the clean git ref). Without an honest baseline the closing gate is meaningless.
3. Build the map: python tools/condense_map.py <file> --format json --output <scratch>/condense-map.json. Six scans, each entry with removable_words:
   • condense-restatement — a sentence whose content words are ≥ 80 % covered by earlier sentences in union, with one earlier sentence (any section) covering ≥ 60 % on its own: canonical home named, copy listed.
   • condense-zero-gain — roadmap sentences ("In this section we..."), assurance refrains, Note that / It is worth noting openers.
   • condense-dead:{figure,table,label,macro,acronym} — defined or placed, never consumed; the grep is the finding.
   • condense-verbose — in order to, due to the fact that, hedge stacks (may possibly), each with the words its replacement saves.
   • condense-regloss — the same symbol glossed twice.
   • condense-duplicate — a paragraph repeated across sections (Jaccard ≥ 0.60 over ≥ 30 content words). condense_budget totals them: removable_total, removable_by_rule, and default_target_words = restatement + zero-gain outside the carve-out. The map is exhaustive for what it scans and blind to what it does not (a claim restated in three sentences, a paragraph that only repeats a figure caption); add those by reading, with the same fields.
4. Rank the map by removable mass (largest first). The default shrink target is default_target_words; --target overrides it and is recorded.

2. Act — ranked removal, one disposition per entry

For each map entry, in rank order, record deleted / merged / kept:<reason>:

1. Restatements and duplicates: choose the canonical location; delete the copies, or where the distant reader genuinely needs the pointer, replace with a cross-reference (Section~\ref{...}); re-read both sites in context.
2. Zero-gain text: delete. If a fragment carries one load-bearing clause, fold that clause into the neighbouring sentence — do not keep the paragraph for one clause.
3. Dead artifacts: delete the artifact and every orphaned mention; re-run the map afterward to confirm nothing dangles.
4. Verbose spans and repeated glosses: rewrite shorter. Gate every shortened rewrite with python tools/rewrite_reward.py --field <field> --reference <claim-record> --original <span> --candidates ... — a candidate that drops a protected invariant is ineligible regardless of its brevity; among eligible candidates the shorter wins. --field is required by the tool (it exits 2 without one); resolve it as in §1 step 1.

Apply each change with a minimal Edit and re-read the affected region plus every cross-reference into it.

3. Verify — prove the shrink

1. Length gate against the target: python tools/length_gate.py <file> --before <scratch>/length-baseline.tex --require-shrink <default_target_words> (a percentage such as 8% or a fraction is also accepted). Exit 0 requires both no unjustified growth and a net cut of at least the target; a cut short of it is a strong length-shrink-short finding with exit 1, and the pass may not close on it — either remove more, or record which kept entries account for the gap.
2. Residue: python tools/deai_residue.py <file> --before <scratch>/length-baseline.tex. A condensation must not leave a heading or caption promising what the body no longer says; exit 1 blocks closing.
3. No orphans: rebuild/compile the document if it is LaTeX (0 errors, 0 undefined references, no newly-missing labels); re-run the map and grep every deleted label and symbol to confirm zero remaining consumers.
4. Fidelity: re-check the §6 invariants over every edited span against the snapshot; every number, citation, and claim in the final text traces to the same source as before.

4. Loop until dry

Repeat §1-§3 over the whole document until two consecutive maps list no entry outside the carve-out with a disposition other than kept. A single clean sweep is not convergence; the first removal round exposes restatements the map could not see while the copies stood.

5. Report

# condense — Report
Target: <file> | Baseline: <snapshot/ref> | Sweeps: K (last 2 dry)
Map: <n entries>, removable <words> (<by rule>); target <words> (<default|--target>)
Net length delta: <words, per section and total>; length_gate --require-shrink: exit <0|1>

## Dispositions (every map entry)
- <rule> L<line>: <excerpt> — deleted | merged into <loc> | kept: <reason>

## Removed outside the map
- <content> : canonical home <loc>; copies removed <locs>; evidence <grep>

## Compressed spans
- <loc>: <before-words> -> <after-words>; eligibility PASS

## Gate findings
- <length-growth / length-shrink-short / residue findings and their recorded justifications>
No number, citation, claim, or sole-support fact was deleted.

6. Anti-patterns

• Appending an explanation instead of deleting the redundancy (the §5.3 explanatory patch — the exact disease this skill exists to cure).
• Removing less than half of the map's restatement mass without a per-entry kept: reason — the scraping pass that trims phrases and leaves the repeated claims standing.
• Deleting a fact's only occurrence because it "felt repeated" — dedup requires proving the survivor exists.
• Gutting the abstract or conclusion under the dedup rule (genre carve-out).
• Trimming hedges, uncertainties, or qualifiers to save words — those are protected invariants, not padding.
• Declaring convergence after one clean sweep, or closing on a length-shrink-short finding without naming the entries that account for the shortfall.
• Leaving removal scars or drafting-history narration in the text.
• Doing de-ai's job: structural-tell rewriting (voice, templates, L0 words) belongs to /sci-paper:de-ai; condense only deletes and compresses.

7. Interfaces

• docs/SCIPAPER_STANDARD.md — §5.3 (the policy this skill executes), §6 (fidelity invariants), §0 (consequence classes and dispositions).
• tools/condense_map.py — the removal map and its budget (exit 0/2).
• tools/length_gate.py — the mechanical closing gate; --require-shrink turns the map's target into an exit code.
• tools/deai_residue.py — the residue gate over the before/after pair.
• tools/rewrite_reward.py — eligibility + condensation ranking for shortened rewrites.
• /sci-paper:paper-review — dimension I findings are this skill's input queue.
• /sci-paper:de-ai — the authorship-fingerprint surface (boundary in §0).