# Subsection Briefs

> Build per-subsection writing briefs (NO PROSE) so later drafting is driven by evidence and checkable comparison axes (not outline placeholders).

- Skill: `willoscar/subsection-briefs` (Agent Skill, multi-file: 16 files)
- Install (CLI): `npx skillmds@latest add willoscar/subsection-briefs`
- Raw SKILL.md: https://api.skillmd.com/api/skills/willoscar/subsection-briefs/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: WILLOSCAR (https://skillmd.com/u/willoscar)
- Updated: 2026-09-10
- Page: https://skillmd.com/skills/willoscar/subsection-briefs

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# Subsection Briefs

## Triggers & routing

- **Trigger**: subsection briefs, writing cards, intent cards, H3 briefs, scope_rule, axes, clusters, 写作意图卡, 小节卡片, 段落计划.


`outline/subsection_briefs.refined.ok` freezes reviewed briefs only while the marker is newer than the briefs, declared inputs, domain packs, and generator. Stale markers are removed before backed-up regeneration.

Build deterministic H3 brief cards from outline + mapping + paper notes.

Compatibility mode is active: this skill keeps the current `outline/subsection_briefs.jsonl` field contract and paragraph-plan shape while moving phrase/domain logic into `references/` and `assets/`.

## Quick Use

- Run `scripts/run.py` as the deterministic materializer.
- Keep the output NO PROSE: subsection-scoped plans, axes, clusters, and bridge handles only.
- Preserve current downstream compatibility for `transition-weaver`, `writer-context-pack`, and `subsection-writer`.

## Load Order

Always read:
- `references/overview.md`

Read by task:
- If `thesis` feels repetitive or copyable, read `references/thesis_patterns.md`.
- If `tension_statement` is too generic, read `references/tension_patterns.md`.
- If axes are weak or domain-biased, read `references/axis_catalog_generic.md` and `references/axis_catalog_llm_agents.md`.
- If transition handles feel bland, read `references/bridge_terms.md`.
- For calibration, read `references/examples_good.md`.

Machine-readable assets:

- `assets/phrase_packs/thesis_patterns.json`
- `assets/phrase_packs/bridge_contrast.json`
- `assets/domain_packs/generic.json`
- `assets/domain_packs/llm_agents.json`
- `assets/domain_packs/embodied_ai.json`
- `assets/domain_packs/rag_evaluation.json`
- `assets/domain_packs/text_to_image.json`

The script loads these packs first; patch them before changing Python when the issue is phrasing, domain routing, axis inventory, cluster purity, or lexical bridge coverage.

## Inputs

- `outline/outline.yml`
- `outline/mapping.tsv`
- `papers/paper_notes.jsonl`
- Optional: `GOAL.md`
- Optional: `outline/claim_evidence_matrix.md`

## Output

- `outline/subsection_briefs.jsonl`

Required record shape remains compatibility-preserving:

- identity: `sub_id`, `title`, `section_id`, `section_title`
- planning core: `rq`, `thesis`, `scope_rule`, `axes`, `bridge_terms`, `contrast_hook`, `tension_statement`
- evidence hooks: `evaluation_anchor_minimal`, `required_evidence_fields`, `clusters`
- execution plan: `paragraph_plan`, `evidence_level_summary`, `generated_at`

## What `run.py` Should Do

- Read outline, mapping, and notes.
- Normalize subsection seeds from outline bullets.
- Load thesis/tension/domain-axis packs from `assets/`.
- Produce stable JSONL records with the existing contract.

## What `run.py` Should Not Do

- Do not invent papers, citations, or claims.
- Do not emit reader-facing narrative prose.
- Do not hardcode domain-specific sentence templates when an asset pack can hold them.

## Block / Reroute

- If outline, mapping, or notes are missing, stop.
- If evidence is thin, keep `thesis`/`tension_statement` conservative and let downstream evidence skills strengthen the subsection.
- If contrast clusters collapse into overlapping paper pools, reroute before writing: after removing bridge papers, each side should still retain at least 2 unique papers.
- Use `bridge_terms` to surface concrete lexical handles that later evidence/ranking stages can still match (`OOD`, `sim-to-real`, `world model`, `failure detector`, specific benchmark families), not only generic axis names.
- Prefer domain-pack `cluster_rules` over ad-hoc bootstrap overlaps when the mapped set is already large enough to support disjoint clusters.
- Do not “fix” thin evidence by inventing more specific axes or stronger claims.


## Execution notes

When running in compatibility mode, `scripts/run.py` currently reads:
- `outline/outline.yml` for section/subsection structure
- `outline/mapping.tsv` for paper-to-subsection coverage
- `papers/paper_notes.jsonl` for structured evidence
- `GOAL.md` for topic/domain cues
- `outline/claim_evidence_matrix.md` as optional supporting context when present

## Script

### Quick Start

- `uv run python .codex/skills/subsection-briefs/scripts/run.py --workspace <workspace>`

### All Options

- `--workspace <dir>`
- `--unit-id <id>`
- `--inputs <a;b;...>`
- `--outputs <a;b;...>`
- `--checkpoint <C*>`

### Examples

- `uv run python .codex/skills/subsection-briefs/scripts/run.py --workspace <workspace>`

## Troubleshooting

- If the wrong domain pack is selected, inspect `GOAL.md` and the asset packs before changing the script.
- If briefs sound too generic, adjust the phrase/domain packs instead of adding more Python prose.
- If `papers/paper_notes.jsonl` is thin, reroute to note extraction rather than inventing axes.