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Section Logic Polisher Skill for Codex

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4k tokens
context cost
the whole folder, loaded on every use
2
files
ships runnable scripts
0
copies elsewhere
how many repositories repackaged it
496
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/WILLOSCAR/research-units-pipeline-skills --skill section-logic-polisher

What comes with it

11 519 bytes besides the instruction
scripts/run.py

The instruction itself

14 sections, as written by the author

Section Logic Polisher (thesis + argument bridges)

Purpose: close the main “paper feel” gap that remains even when a subsection is long and citation-dense:

  • missing/weak thesis (paragraph 1 never commits to a claim)
  • weak inter-paragraph flow (paragraph islands; no content-bearing bridges)

This is a local, per-H3 polish step that happens after drafting and before merging.

Note: if the main problem is paragraph-count overgrowth, run

paragraph-curator after this check. It only merges adjacent paragraph

boundaries and preserves all prose; semantic redundancy still belongs to the

owning writer.

What this skill blocks on (and what it does not)

Blocking (must fix):

  • paragraph 1 lacks an explicit thesis / takeaway (a content claim)

Non-blocking (diagnostic only):

  • connector word counts (e.g., “moreover/however/therefore”). Counts are a proxy for paragraph islands, but forcing them as a quota often creates “generator cadence” (paragraph-initial adverbs). Treat these stats as *signals*, not goals.

Role prompt: Logic Editor (argument flow)

You are the logic editor for one survey subsection.

Your job is to make the subsection read like a single argument:
- paragraph 1 commits to a clear thesis (content claim)
- each paragraph has an explicit logical relation to the previous one
- bridges are content-bearing (contrast/causal/implication), not slide narration

Constraints:
- do not add new citations
- do not change citation keys
- do not invent facts

Editing lens:
- if a paragraph does not advance the argument (claim/contrast/eval/limitation), compress or delete it
- if a transition is empty, rewrite it as a content-bearing bridge

Inputs

  • sections/ (expects H3 body files like S<sec>_<sub>.md)
  • outline/subsection_briefs.jsonl (use thesis + paragraph_plan[].connector_phrase as intent)
  • Optional: outline/writer_context_packs.jsonl (preferred; has trimmed anchors/comparisons + must_use)

Outputs

  • output/SECTION_LOGIC_REPORT.md (PASS/FAIL for thesis; connector stats shown for diagnosis)

Manual / LLM-first (in place):

  • Update the H3 body files under sections/ (e.g., sections/S<sec>_<sub>.md) to fix thesis/bridges (no new citations; keep keys stable)

Workflow (self-loop)

1) Run the checker script to surface the exact failing files.

2) For each failing H3 file:

  • Work on the concrete H3 body file (pattern): sections/S<sec>_<sub>.md
  • Use outline/subsection_briefs.jsonl as the source of truth for the subsection thesis and paragraph-plan intent.
  • If available, prefer outline/writer_context_packs.jsonl to stay aligned with must_use anchors/constraints (no new cites).
  • Thesis (blocking)
  • Make paragraph 1 end with a conclusion-first thesis sentence.
  • Prefer a content claim, not meta narration. Avoid repetitive openers like This subsection argues/surveys ....
  • Minimal shape (3 sentences; paraphrase, don’t copy):

1) claim / tension

2) why it matters (protocol/evaluation relevance)

3) how the subsection will resolve it (what contrasts/anchors it will use)

  • Flow (fix only when needed)
  • Add 1–2 short bridges where paragraphs feel disconnected.
  • Prefer subject-first sentences and mid-sentence glue (because/while/which) over paragraph-start adverbs.
  • Avoid PPT navigation (Next, we ..., We now turn to ...).

3) Rerun the checker until output/SECTION_LOGIC_REPORT.md is PASS, then

proceed to paragraph-curator, evaluation-anchor-checker, the final

argument-selfloop snapshot, and merge.

Examples

Thesis signal (paragraph 1)

Bad (topic setup only):

  • Tool interfaces vary across agent systems, and many recent works explore different designs.

Better (conclusion-first claim):

  • A central tension in tool interfaces is balancing expressivity with verifiability; as a result, interface contracts often determine which evaluation claims transfer across environments.

Bad (meta narration):

  • This subsection argues that memory is important for agents.

Better (content claim):

  • Memory designs trade off retrieval reliability against write-time contamination, and this trade-off shows up as distinct failure modes under fixed evaluation protocols.

Bridges (avoid paragraph islands)

Bad (no relation):

  • X does ... (para 2)
  • Y does ... (para 3)

Better (explicit tie):

  • Whereas X optimizes for <axis>, Y shifts the bottleneck to <axis>; under fixed budgets, this changes whether the reported gains reflect better planning or simply more expensive search.

Done criteria

  • output/SECTION_LOGIC_REPORT.md shows - Status: PASS
  • No section file contains placeholders (TODO//...) or outline meta markers (Intent:/RQ:/Evidence needs:)
  • Every H3 has a clear paragraph-1 thesis; bridges are added only where flow is actually broken

Script

Quick Start

  • uv run python .codex/skills/section-logic-polisher/scripts/run.py --workspace <workspace>

Notes:

  • The script is a checker; it does not rewrite prose.
  • Connector stats are printed for diagnosis. Do not “write to the counter”; write to the argument.

All Options

  • --workspace <dir>
  • --unit-id <U###>
  • --inputs <semicolon-separated>
  • --outputs <semicolon-separated>
  • --checkpoint <C#>

Examples

  • Default run:

uv run python .codex/skills/section-logic-polisher/scripts/run.py --workspace <workspace>

  • Explicit output path (rare override; prefer defaults):

uv run python .codex/skills/section-logic-polisher/scripts/run.py --workspace <workspace> --outputs output/SECTION_LOGIC_REPORT.md

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How to use it

Copy the folder

Take willoscar/section-logic-polisher from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

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