git:20260728.4a5ab11 to git:20260728.c30c7bf

---

name: match-outline

description: >-

Whole-document voice analysis: compare a draft against a corpus profile,

extract voice persona blueprints from exemplar papers, and rewrite the

Triggers: compare my outline, section analysis, does my intro match the

field, methodology conventions, results conventions, rewrite in the

style of, apply the voice, voice persona, exemplar, blueprint

extraction, mimic this paper, rewrite my draft, whole-document rewrite.

---

# Match outline (whole-document voice analysis)

This skill answers "does my draft's structure and voice match the field?"

It compares a draft's conventions against a corpus profile, extracts voice

persona blueprints from exemplar papers, and rewrites drafts as a whole

document with a plagiarism guard.

It complements `match-structure` (which provides the quantitative metrics,

frequency tables, and similarity math this skill imports) and `filter-tells`

(which detects generic AI-writing patterns at the paragraph level).

## Where things live

- **Quantitative profile:** `<db-dir>/voice-profile.json`, written by

`match-structure`'s `style.py corpus`.

- **Qualitative profile:** `<db-dir>/voice-profile.md`, written by the model

following `references/voice-analysis-instructions.md` Part 1.

- **Comparison reports:** `<db-dir>/voice-reports/<draft-stem>-voice.md`,

following `references/comparison-report-template.md`.

- **Exemplar blueprints:** `<db-dir>/voice-blueprint-<slug>.md`, extracted

from chosen exemplar papers following `voice-analysis-instructions.md`

Part 3 (consensus vs idiosyncrasy).

- **Rewritten drafts:** `<draft-stem>-rewritten.md` next to the draft. The

draft itself is never modified.

## Running the scripts

The scripts run in the pixi-managed environment that ships beside the skill

(`pixi.toml` / `pixi.lock` at the agent-directory root). The agent provisions

it on repo open via `<agent-dir>/scripts/ensure-env.sh`; then the commands

below use `$RUN` for the wrapper:

```bash

RUN="pixi run --manifest-path <skill>/../../pixi.toml python"

```

## The workflow (interactive)

### 1. Locate the corpus

Find `references.yaml` at or above the working directory. If it does not

exist, or no entries have `status: summarized` with an existing `md_path`

file, stop and tell the user to run `update-references` first.

### 2. Quantitative profiles

```bash

$RUN <match-structure>/scripts/style.py --db <db-path> corpus

```

This writes `voice-profile.json`. Skip if the existing profile is unchanged.

### 3. Qualitative profile

Read the corpus papers and write `voice-profile.md` following **Part 1** of

`references/voice-analysis-instructions.md`. Every claim carries a quote.

### 4. Compare the draft

```bash

$RUN <match-structure>/scripts/style.py --db <db-path> compare <draft.md>

```

Then write the comparison report following **Part 2** of

`voice-analysis-instructions.md` and the structure of

`comparison-report-template.md`.

### 5. Report back

Summarize: the verdict (close match / partial / divergent), the two or

three highest-impact changes, and the report path.

## Exemplar blueprints (mimic a specific paper or venue)

When the user wants to mimic specific papers, extract a voice persona

blueprint following **Part 3** of `voice-analysis-instructions.md`.

## Rewrite mode (opt-in)

Whole-document rewrite following

`references/style-application-instructions.md`. The model receives the

entire draft plus blueprint plus exemplar papers in one pass, preserving

cross-section transitions and structural coherence. Paragraph structure

may change freely — the model can merge, split, or reshuffle as the voice

demands. After the rewrite: content preservation check (citations, numbers)

and similarity guard via `match-structure`'s `style.py similarity`.

## Headless mode

`match_outline.py` runs every mode without an interactive session.

```bash

# Compare a draft

$RUN <skill>/scripts/match_outline.py <draft.md> --db <db-path>

# Extract a blueprint

$RUN <skill>/scripts/match_outline.py --db <db-path> \

--exemplar paper1 --exemplar paper2 --name icml

$RUN <skill>/scripts/match_outline.py <draft.md> --db <db-path> --rewrite

```

## Exemplar sources

Two sources of exemplars are accepted:

- **`references.yaml` corpus** (default) — the papers fetched by

`update-references`, selected with `--db`.

- **`writing-voice/manifest.yaml`** — a curated exemplar directory. Pass

`--voice-dir <path>` with optional `--role`, `--anchor-tags`, `--stratum`.

## Dependencies

`match_outline.py` imports `style` from `match-structure/scripts/` for