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Section Logic Polisher

Checked
willoscar·vlatest·writing

This tool refines Markdown sections for clearer logic and flow, improving readability and organization of your content.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add willoscar/research-units-pipeline-skills --skill section-logic-polisher -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

willoscar

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned willoscar/research-units-pipeline-skills at f53f82f8d7.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
f53f82f8d7
Manifest
.codex/skills/section-logic-polisher/SKILL.md
Scanned
2 files, 414 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

The Section Logic Polisher refines Markdown sections to improve their logical flow and readability, specifically addressing issues that create a “paper feel” even in detailed content. It focuses on ensuring each subsection presents a clear argument with a strong thesis statement and well-connected paragraphs. This skill helps ensure the first paragraph of a section explicitly states its claim (thesis) and that transitions between paragraphs are substantive rather than just connectors.

When to use it

  • After drafting a long, citation-dense Markdown subsection.
  • When a subsection lacks a clear thesis statement in the opening paragraph.
  • To improve the flow of arguments within a section by strengthening connections between paragraphs.
  • As part of a review process before merging content.
  • When sections feel disjointed or like "paragraph islands."

Key capabilities

  • Thesis Statement Enforcement: Ensures the first paragraph ends with an explicit, clear thesis statement (content claim).
  • Logical Flow Enhancement: Improves connections between paragraphs to create a cohesive argument.
  • Content-Bearing Bridges: Rewrites empty transitions into substantive bridges that advance the argument (contrast, causation, implication).
  • Focus on Existing Content: Does not add new citations or invent facts; it refines existing content.
  • Uses Contextual Information: Leverages outline/subsection_briefs.jsonl and optionally outline/writer_context_packs.jsonl to guide the polishing process, incorporating intended thesis statements and paragraph plans.

Example prompts

While this skill operates as a local polish step rather than responding directly to prompts, relevant context can be provided through input files:

  • "Polish section S<sec>_<sub>.md using the intent from outline/subsection_briefs.jsonl."
  • "Refine section S<sec>_<sub>.md, prioritizing must_use anchors and constraints from outline/writer_context_packs.jsonl."

Tips & gotchas

  • Prerequisite: This skill is best used after a draft has been created. It's not designed to generate content from scratch.
  • Focus: The tool specifically targets thesis statements and paragraph bridges; it does not address redundancy or overall section length (use "paragraph-curator" for that).
  • Connector Word Counts as Signals: While connector word counts are tracked, avoid forcing a specific number of connectors, as this can lead to unnatural writing. Treat these numbers as diagnostic indicators rather than goals.