opener-variator

Opener Variator (H3 first paragraph rewrite)

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Install skill "opener-variator" with this command: npx skills add willoscar/research-units-pipeline-skills/willoscar-research-units-pipeline-skills-opener-variator

Opener Variator (H3 first paragraph rewrite)

Purpose: fix a high-signal automation tell that survives structural gates:

  • many H3s begin with the same rhetorical shape

  • "overview" narration replaces content-bearing framing

This skill is intentionally narrow:

  • only rewrite the first paragraph (or first 2–4 sentences) of the flagged H3 files

  • keep the argument moves and citations intact

Inputs

Required:

  • output/WRITER_SELFLOOP_TODO.md (Style Smells section)

  • the referenced sections/S<sub_id>.md files

Optional (helps you stay aligned):

  • outline/writer_context_packs.jsonl (use opener_mode , tension_statement , thesis )

Outputs

Note: keep this as an openers-last pass. Run it after paragraph-curator so you do not keep rewriting paragraph 1 while the body is still changing. Current compatibility policy: the script is marker-only; substantive opener repair should happen upstream in subsection-writer / chapter-lead-writer , not through blind regex rewriting.

  • Updated sections/S<sub_id>.md files (still body-only; no headings)

Workflow (route from the self-loop report)

  • Open output/WRITER_SELFLOOP_TODO.md and locate ## Style Smells .

  • Treat the flagged sections/S*.md list as the only scope for this pass.

  • For each flagged file:

  • Optional: look up its entry in outline/writer_context_packs.jsonl and read opener_mode / tension_statement / thesis to stay aligned.

  • Do the real rewrite upstream in subsection-writer or chapter-lead-writer ; do not rely on blind local regex passes.

  • Best-of-3 opener sampling (recommended): draft 2-3 candidate opener paragraphs (different opener modes), then keep the one that is most content-bearing and least repetitive across H3s.

  • Rerun writer-selfloop and confirm the Style Smells list shrinks.

Role prompt: Opener Editor (paper voice)

You are rewriting the opening paragraph of a survey subsection.

Goal:

  • replace narration/overview openers with a content-bearing framing
  • vary opener cadence across subsections so the paper reads authored

Constraints:

  • do not invent facts
  • do not add/remove/move citation keys
  • do not change the subsection’s thesis

Checklist:

  • sentence 1 is content-bearing (tension/decision/failure/protocol/contrast), not “what we do in this section”
  • paragraph 1 ends with a clear thesis/takeaway
  • no slide navigation (“Next, we…”, “In this subsection…”, “This section provides an overview…“)

What to delete (high-signal narration)

Rewrite immediately if the opener contains any of:

  • “This section/subsection provides an overview …”

  • “In this section/subsection, we …”

  • “This subsection surveys/argues …”

  • “Next, we move/turn …”

  • repeated opener labels (“Key takeaway:” spam)

What to replace with (opener moves)

Pick one opener mode per H3 (the writer pack may suggest opener_mode ). Do not copy labels; write as natural prose.

Allowed opener moves (choose 1; keep it concrete):

  • Tension-first: state the real trade-off; why it matters; end with thesis.

  • Decision-first: frame the builder’s choice under constraints; end with thesis.

  • Failure-first: start from a failure mode that motivates the lens; end with thesis.

  • Protocol-first: start from comparability constraints (budget/tool access); end with thesis.

  • Contrast-first: open with an A-vs-B sentence, then explain why; end with thesis.

  • Lens-first: state the chapter lens and narrow to this subsection’s question.

Mini examples (paraphrase; do not copy)

Bad (overview narration):

  • This subsection provides an overview of tool interfaces for agents.

Better (content-bearing):

  • Tool interfaces define what actions are executable; interface contracts therefore determine which evaluation claims transfer across environments.

Bad (process narration):

  • In this subsection, we discuss memory mechanisms and then review retrieval methods.

Better (tension-first):

  • Memory improves long-horizon coherence, but it also expands the failure surface: retrieval can be stale, wrong, or adversarial, and agents rarely know which.

Done checklist

  • No flagged file starts with “overview/narration” stems.

  • Paragraph 1 ends with a thesis/takeaway (same meaning).

  • Citation keys are unchanged (no adds/removes/moves).

  • writer-selfloop still PASSes and Style Smells shrink.

Script

Quick Start

  • python .codex/skills/opener-variator/scripts/run.py --workspace workspaces/<ws>

All Options

  • --workspace <dir> (required)

  • --unit-id <U###>

  • --inputs <semicolon-separated>

  • --outputs <semicolon-separated>

  • --checkpoint <C#>

Examples

  • Rewrite openers in a survey workspace:

  • python .codex/skills/opener-variator/scripts/run.py --workspace workspaces/survey-llm-agents

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