abstract

name	abstract
description	Draft or tighten the abstract as a contract — every number and claim in it must appear identically in the body, within the venue's word limit, calibrated to what the paper actually shows
user-invocable	true

Abstract

Core Rule

The abstract is a contract, not a teaser. Every quantity and every claim in it must appear identically in the body (Results) — same number, same scope, same calibrated verb — fit within the venue's word/structure limit, and never assert anything the paper does not show. An abstract is the most-read and least-checked part of a manuscript, which is exactly why a number that drifts from the Results table, or a verb that outruns the evidence, does the most damage. Never introduce a number or a claim in the abstract that is not already in the body. If the body does not contain it, it does not go in the abstract — you fix the body first (a Protected Claim) or you cut the line.

This skill drafts/tightens the abstract and reports a consistency check; it is not a licence to invent a headline result the experiments did not produce.

When to Use

Invoke with /abstract when:

• The Results are settled and you need a first abstract built from them.
• An existing abstract is over budget, or reads as a list of methods rather than findings.
• After a revision changed a reported number — the abstract must be re-reconciled to the body (a silent abstract/body mismatch is the classic submission embarrassment).
• Before submission, as the last consistency pass: every abstract number ↔ its body source.

State the venue if it sets the format: /abstract NeurIPS (unstructured, ~caps differ) vs a journal that mandates a structured abstract. If none is given, read it from MANUSCRIPT_MAP.md → Target journal.

Process

Phase 1: Pull the Contract Material

Before writing a word, gather what the abstract is allowed to say — all of it from inside the manuscript:

1. Read MANUSCRIPT_MAP.md — the Thesis (one sentence), the Contribution (what is new), the Audience, the Target journal, and Claims that need extra care (the do-not-inflate list — these constrain the abstract hardest).
2. Read the Results section in full (and the primary table/figure). Every number you might put in the abstract must already live here. Note each headline result with its exact value, its uncertainty, and its scope (which harness, which task set).
3. Read the Introduction's contribution statement — the abstract's claims should be the contribution list compressed, not a new set of promises.
4. Find the word/structure limit — venue word cap and whether it is structured (Background / Methods / Results / Conclusions) or a single unstructured paragraph. Treat any exact cap as verify against the current call unless MANUSCRIPT_MAP quotes it.

If a number you want in the abstract is not in the body, stop: either it belongs in Results first (raise it as a Protected Claim per CLAUDE.md), or it does not go in the abstract. Do not let the abstract be where a quantity makes its debut.

Phase 2: Draft Within Budget

Write the smallest abstract that carries thesis → gap → what-we-did → key result → what it means. Structure to the venue:

• Unstructured (most ML/NLP venues — NeurIPS/ACL): one paragraph. Problem and gap (1–2 sentences) → approach (1–2) → the headline quantitative result (1–2) → the takeaway (1).
• Structured (many journals): fill the mandated labels; keep each to its purpose.

Discipline while drafting:

• Lead with the finding, not the machinery. "We present a verification gate…" buries the result; "A pre-execution verification gate reduced the hallucinated tool-call rate by 18 percentage points…" leads with it. (MANUSCRIPT_MAP → Audience wants the payoff up front.)
• Use the locked term for each concept (MANUSCRIPT_MAP → Terminology): "tool-call accuracy", "hallucinated tool-call rate", "task success", "task horizon" — do not alternate synonyms between abstract and body.
• Carry uncertainty if the venue allows it. "18 pp (95% CI 11–25)" is stronger and more honest than a bare point estimate; at minimum do not state a point estimate the Results qualify heavily.
• No citations in the abstract unless the venue explicitly permits — and even then, never introduce a \cite here that the body does not also carry.

Phase 3: Verify Every Quantity Against the Body

This is the heart of the contract. For each number in the draft abstract, find its twin in the body and confirm they are identical — recompute, do not eyeball (CLAUDE.md → Model vs Code; agent_docs/statistics.md → text ↔ tables ↔ abstract):

• Value matches the Results sentence / table cell exactly (92% in the abstract is not 89% in Table 2).
• Scope matches — "across all tasks" in the abstract must not summarize a result the body reports for one task subset.
• Units / percentage-vs-percentage-points match the body's usage.
• N and uncertainty, if stated, match.

Any number with no body twin is a contract breach: cut it, or fix the body first. If you cannot confirm a value against the body, mark it [VALUE — verify] in the consistency check — do not ship an unverified abstract number.

Phase 4: Calibrate the Verbs

Run each claim sentence against the evidence the body actually provides (agent_docs/academic-style.md → verb ladder):

• The abstract's verb must not exceed the body's. If Results show an association, the abstract says "was associated with", not "caused". If one harness was tested, the abstract does not say "in deployment" or "in general".
• Cross-check every claim against MANUSCRIPT_MAP → Claims that need extra care. A "first / SOTA / general" claim in the abstract needs the comparison in the body that earns it — if the body does not establish it, soften or cut.
• Hedge once, at the right rung — an over-hedged abstract buries the finding as badly as an over-claimed one misrepresents it.

Phase 5: Report

Output the abstract, the word count against budget, and the consistency check (every abstract number ↔ its body source). Do not change a reported quantity to make the abstract "work" — that is a Protected Claim; surface the mismatch and let the author resolve it in the body.

Output Format

# Abstract — <manuscript> → ACL (unstructured, verify ~150-word cap)

## Draft
A pre-execution verification gate for LLM-agent tool calls is proposed to curb
hallucinated tool calls on long-horizon tasks. Across 512 held-out tasks on a ReAct
harness, the gate raised tool-call accuracy by 18 percentage points (95% CI 11–25)
and reduced the hallucinated tool-call rate from 21% to 6%, with task success
unchanged. The effect grew with task horizon, consistent with grounding each call
before execution. The gate is model-agnostic and adds one verification step per call.

Word count: 71 / ~150 (CONFIRM exact cap against the current ACL call)

## Consistency check (every abstract number ↔ body source)
| Abstract claim / number | Body source | Match? |
|---|---|---|
| "18 percentage points (95% CI 11–25)" | Results ¶2 / Table 2 row "gate vs base" | OK |
| "hallucinated tool-call rate from 21% to 6%" | Results ¶3 / Table 2 | OK |
| "512 held-out tasks" | Methods ¶1 | OK |
| "task success unchanged" | Results ¶4 ("no significant change, p = 0.41") | OK — verb calibrated |
| "grew with task horizon" | Results ¶5 / fig:horizon | OK |
| "model-agnostic" | — | GAP — body tests one model; soften to "in the tested setting" or cut |

## Calibration notes
- "consistent with grounding each call" — correct hedge; the mechanism is inferred, not
  shown (matches MANUSCRIPT_MAP → Claims that need extra care).
- "model-agnostic" exceeds the evidence (one model tested) — flagged above.

## Flags
- [Protected] "model-agnostic" has no body support — do not assert in the abstract until
  the body shows it. Cut or rescope; needs author decision.
- Confirm the ~150-word cap against the current ACL call for papers.

End with the contract tally: (numbers matched / mismatched / unverified) and the word count vs budget. Never report an abstract "done" while a number lacks a body twin or a [VALUE — verify] remains.

Pairs With

• /claim-check — run it on the abstract's claim sentences for the deep verb/quantifier pass; /abstract checks the abstract↔body contract, /claim-check checks each claim against its source.
• citation-gate.sh (PostToolUse) — if the venue allows abstract citations, this proves any \cite resolves; the abstract must not introduce a key the body lacks.
• agent_docs/academic-style.md — the verb/quantifier ladder the calibration phase applies; read it for the strength/scope rungs.
• /journal-fit — for the venue's abstract format and length convention before drafting.

Common Rationalizations

Rationalization	Reality
"The abstract can round 89% up to ~90%"	The abstract must match the body's number, not a friendlier version of it. 89% in Table 2 is 89% in the abstract.
"This result is so strong I'll lead with the stronger framing"	The abstract's verb may not exceed the body's. Calibrate to what Results show, not to what would impress.
"I'll add the headline number; the body basically has it"	"Basically" is a contract breach. If the exact number is not in the body, put it there first (Protected Claim) or cut it.
"It's just the abstract, reviewers read the paper"	The abstract is the most-read part and the one editors screen on. A mismatch here is the first thing a careful reviewer flags.
"Over budget, but every sentence matters"	A 200-word abstract in a 150-word venue gets truncated or bounced. Cut the machinery sentence, keep the finding.

Notes

• This skill never invents a result to headline. Its only sourcing output is the consistency check and [VALUE — verify] flags — honest, per the cardinal rule in CLAUDE.md.
• Reconciling the abstract to the body and calibrating verbs is judgment work — run on the Reasoner model (CLAUDE.md → Model Selection); the word count is texcount, not estimation.
• A recurring abstract/body mismatch (the author keeps catching drifted numbers) is a rule — log it under tasks/reviews/, applies_to: [abstract, statistics], promote to ## Top Rules if it recurs (CLAUDE.md → Self-Improvement Loop).
• Changing a reported quantity to reconcile the two is a Protected Claim — fix the body with author sign-off; never silently edit the abstract to a number the Results do not show.