Front Matter Writer (paper shell, high leverage)
Purpose: make the draft feel like a real paper before subsection-level detail.
Front matter is where many "automation tells" originate (method-note spam, slide narration, title narration, cite dumps). This skill encodes how to write it in a paper-like way so C5 does not start from a hollow shell.
Inputs
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DECISIONS.md (must include Approve C2 )
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outline/outline.yml (the paper\x27s section order; determines which H2 are Intro/Related Work)
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outline/mapping.tsv (for what to cite where; especially for Introduction/Related Work)
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Optional (helps with method note and consistent scope):
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papers/retrieval_report.md (candidate pool + time window)
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papers/core_set.csv (core set size)
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GOAL.md
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queries.md (evidence_mode / draft_profile)
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outline/coverage_report.md (weak coverage flags)
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outline/writer_context_packs.jsonl (for cross-cutting/global citations)
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citations/ref.bib
Outputs (files and heading rules)
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sections/abstract.md (MUST start with ## Abstract or ## 摘要 ; merger places it right under the paper title)
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sections/S<sec_id>.md for H2 sections that have no H3 subsections (typically Introduction , Related Work )
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body-only (NO headings; merger injects ## <H2 title> already)
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sections/discussion.md (MUST include a ## Discussion heading; merger appends the file verbatim)
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sections/conclusion.md (MUST include a ## Conclusion heading; merger appends the file verbatim)
Workflow (keep it paper-like)
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Approval gate
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Confirm DECISIONS.md contains Approve C2 .
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Load scope + structure
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Read GOAL.md to restate the problem boundary in one sentence.
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Read queries.md to understand evidence_mode (abstract vs fulltext) and draft_profile (survey/deep).
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Read papers/retrieval_report.md (and/or count papers/core_set.csv ) to extract: time window, candidate pool size, core set size.
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Read outline/outline.yml to identify the H2 sections that are front matter (Intro/Related Work) and their S<sec_id> file names.
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Plan citations (avoid "prior survey" buckets)
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Use outline/mapping.tsv
- outline/coverage_report.md to see which themes are well-covered vs thin.
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Use outline/writer_context_packs.jsonl to pick a small set of cross-cutting/global anchors (surveys, benchmarks, protocol papers) that can appear in Intro/Related Work.
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Validate every citation key against citations/ref.bib before you write.
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Write the files (see the section-specific contracts below)
Openers-last (front matter)
Front matter is where template voice often originates. To keep it authorial without adding new machinery:
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Draft the middle paragraphs first (lens paragraphs + gap statement + the single methodology paragraph) with real citations.
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Rewrite paragraph 1 last so it reflects the file's real claim (avoid "This survey..." / "This section provides an overview..." stems).
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If later C5 edits change the paper's lens/structure, do one final pass rewriting only the first 1-2 paragraphs of Introduction and Related Work (no new facts/citations).
Best-of-2 sampling (recommended)
Front matter is high leverage and easy to make templated. For the opener paragraph of Introduction and Related Work, draft 2 candidates (different framing modes: tension-first vs protocol-first vs contrast-first), then keep the one that:
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is content-bearing (not "This survey..." / "This section provides an overview...")
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commits to a clear scope boundary + lens
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embeds citations as evidence (no trailing cite-dump line)
Do not keep both variants in the final file.
Role cards (use explicitly)
Positioner (scope + boundary)
Mission: define what counts as an agent here and why the boundary matters for evaluation.
Do:
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State scope and exclusions in testable language.
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Commit to a small set of lenses/axes that organize the survey.
Avoid:
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Outline narration ("we organize as follows") without content.
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A dedicated "Prior surveys" bucket by default; integrate surveys into lens paragraphs.
Methodologist (methodology note once)
Mission: state the survey methodology exactly once (time window, candidate pool, core set size, evidence mode) in paper voice.
Do:
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Write one short paragraph (Intro or Related Work) that states: time window, candidate pool size, core set size, and evidence mode (abstract/fulltext), plus a brief reproducibility caveat.
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Keep the rest of the paper content-focused.
Avoid:
- Repeating abstract-only disclaimers inside H3 bodies.
Cartographer (related work through your lens)
Mission: position prior work as a map, not a list.
Do:
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Organize related work by your survey lenses (interfaces, planning/memory, adaptation, evaluation/risks).
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End with a gap statement tied to your lens (protocol-aware comparisons, threat models, etc.).
Avoid:
- Citation-dump paragraphs.
Stylist (paper voice)
Mission: remove automation tells before they appear everywhere.
Do:
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Replace navigation with argument bridges.
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Keep tone calm and academic; avoid hype and PPT speaker notes.
Avoid:
- Pipeline jargon and repeated template stems.
Role prompt: Front Matter Author (positioning + methodology)
You are the author of the survey’s front matter (Abstract / Introduction / Related Work / Discussion / Conclusion).
Your job is to build the paper shell that makes the rest of the draft readable:
- define scope and boundary (what counts as an agent here, what does not)
- commit to a small set of lenses/axes that organize the survey
- state the survey methodology exactly once (time window, candidate pool, core set size, evidence mode) as a paper paragraph (not as execution logs)
- position the work through those lenses (not as a “prior surveys” list)
Style:
- content-bearing, understated, academic
- avoid outline narration and slide navigation
- avoid pipeline jargon entirely
Constraints:
- do not invent facts or citations
- only use citation keys present in citations/ref.bib
- do not repeat abstract-only disclaimers across subsections (one paragraph total)
Paper voice contract (front matter specific)
Avoid "narrating the outline":
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Don\x27t write: This section surveys... , In this section, we... , Next, we move... , We now turn to...
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Do write: content-bearing claims + argument bridges (why the next lens follows).
Avoid self-referential survey narration (a common automation tell):
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Don't default to: This survey ... / Our survey ... / In this survey ... as the sentence opener.
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Do write: direct, content-bearing claims (optionally with "We"), or use third-person ("This work") sparingly.
Avoid "pipeline voice":
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Don\x27t write: evidence pack(s) , writer context pack(s) , quality gate , workspace , stage C2/C3...
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Do write: "survey methodology" phrasing (what was collected, what was prioritized, what is uncertain).
Avoid count-based slot structures:
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Don't default to "Two limitations..." / "Three takeaways..." as the paragraph opener across multiple sections.
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If you truly need enumeration, do it once, keep it sentence-level, and vary the opener syntax so it reads authorial (not templated).
Keep the methodology note exactly once:
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Put one paragraph in Introduction or Related Work.
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Do not repeat "abstract-only evidence / claims provisional" across subsections.
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If a specific claim is only abstract-supported, mark locally as (abstract-only) only when it changes interpretation.
What to write (semantic structure, not templates)
sections/abstract.md (one paragraph, high signal)
Format:
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Start with ## Abstract (or ## 摘要 ).
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Then write a single paragraph.
Goal: define scope + axes + what the reader gets.
Include (in ~5-8 sentences):
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problem framing (agents as closed-loop systems)
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boundary/definition (what counts as an agent here)
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the survey lens (interfaces -> planning/memory -> adaptation/multi-agent -> evaluation/risks)
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what is new/useful (taxonomy + protocol-aware comparisons + evaluation/risk takeaways)
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3-6 citations (surveys + benchmarks/protocol papers; avoid dumping keys)
Anti-patterns:
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generic "This paper surveys..."
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"we organize as follows" without content
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self-referential survey framing ("This survey ...") that narrates structure instead of stating a claim
sections/S<sec_id>.md — Introduction (body-only)
Job: motivate + define boundaries + commit to a lens + tell the reader how to read the survey.
Recommended paragraph jobs:
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Motivation: why "agent = closed-loop system" is hard now (tools, environments, safety).
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Boundary/definition: what you include/exclude (agent vs tool-using LM; single vs multi-agent; online vs offline).
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Why interfaces/protocols matter: the interface contract determines what evaluation claims mean.
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Taxonomy preview: what axes you use and why (avoid listing 10 axes; choose a few stable ones).
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Methodology paragraph (ONE paragraph; no label like "Methodology note"): state time window + candidate pool size + core set size + evidence mode (abstract/fulltext), phrased as survey methodology (not "run logs"). Start it like a normal sentence (e.g., "We retrieved ...").
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Contributions: what the survey delivers (taxonomy, evaluation lens, open problems).
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Organization: light, one paragraph max (avoid slide narration).
sections/S<sec_id>.md — Related Work (body-only)
Job: position this survey vs adjacent lines of work through your lens, not as "prior survey list".
Recommended moves:
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One paragraph: what "related work" means here (surveys + system papers + evaluation/protocol papers).
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3-5 paragraphs grouped by lens:
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interface contracts / tool use / environments
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planning/memory/adaptation (why these are not comparable without protocols)
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multi-agent coordination and safety/risk work
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Integrate "prior surveys" as citations inside these paragraphs (do NOT create a "Prior Surveys" mini-section).
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End with a gap statement: what existing surveys miss (e.g., protocol-aware comparisons, threat model, reproducibility).
sections/discussion.md (must include heading)
Goal: cross-cutting synthesis (not per-chapter recap).
Include:
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3-6 paragraphs that each make one cross-chapter claim with citations (>=2 per synthesis paragraph).
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explicit limitations and what to verify next (protocol mismatch, cost models, tool access assumptions).
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concrete future directions (avoid generic "more research").
Avoid:
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Per-chapter recap ("In Section X we...") or title narration ("From X to Y").
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Meta advice without evidence ("future work should...") or citation-dump paragraphs.
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Repeating the evidence-mode disclaimer here; it belongs in the single methodology note.
sections/conclusion.md (must include heading)
Goal: close the loop: restate the thesis + strongest takeaways + what matters next.
Include:
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a compact thesis restatement (agents as closed-loop systems; interfaces/protocols decide meaning of results)
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2-3 takeaways as prose sentences (avoid literal template bullet dumps)
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a final "evaluation-first" closing sentence (what to standardize / measure / report).
Avoid:
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Template narration ("This paper/survey concludes...") and slide navigation.
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Count-based openers ("Two limitations...", "Three takeaways...") used as a default structure.
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Overclaiming beyond the cited evidence level (especially in abstract-only mode).
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Repeating the same takeaway label or ending with a citation dump line.
Small rewrite recipes (keep prose natural)
Narration -> content:
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Bad: This section surveys tool interfaces for agents.
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Better: Tool interfaces expose the action space an agent can reliably execute; interface contracts therefore determine which evaluation claims are even interpretable.
Slide navigation -> argument bridge:
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Bad: Next, we move from planning to memory.
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Better: Planning determines how decisions are formed, while memory determines what evidence those decisions can condition on under a fixed protocol.
Meta "survey should" -> literature-facing observation:
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Bad: Therefore, survey comparisons should control for tool access.
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Better: Across reported protocols, tool access and budget assumptions vary widely, which makes head-to-head comparison fragile unless those constraints are normalized.
Done checklist
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sections/abstract.md exists, starts with ## Abstract (or ## 摘要 ), and citations are embedded (no dump line).
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Introduction + Related Work files are body-only (no headings) and contain the single methodology note paragraph (exactly once).
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sections/discussion.md contains ## Discussion ; sections/conclusion.md contains ## Conclusion .
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No pipeline/meta jargon appears in these files.
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Citations all exist in citations/ref.bib and are used as evidence (not list tags).