# Narrative Framing

> Theory-driven reading tactic — define a theoretical framework first, then guide reading to fill it with evidence. Five stages (theme identification, argument construction, evidence collection, counter-evidence, synthesis). The most intellectually demanding tactic.

- Skill: `yogsoth-ai/narrative-framing` (Agent Skill)
- Install (CLI): `npx skillmds@latest add yogsoth-ai/narrative-framing`
- Raw SKILL.md: https://api.skillmd.com/api/skills/yogsoth-ai/narrative-framing/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: yogsoth-ai (https://skillmd.com/u/yogsoth-ai)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/yogsoth-ai/narrative-framing

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# Narrative Framing

Define a theoretical framework first, then guide reading to fill it with evidence.

## Stages

1. **Theme identification** — from initial reading, identify 3-5 major themes
2. **Argument construction** — define the narrative arc (thesis → evidence → synthesis)
3. **Evidence collection** — targeted reading to support each theme
4. **Counter-evidence** — actively search for work that challenges the narrative
5. **Synthesis** — weave themes into coherent argument

## Available SOPs

- `paper-search` (import) — targeted reading for evidence
- `paper-research` (import) — deep reading of key supporting/opposing papers
- `thematic-coding` (subagent) — identify patterns across papers
- `web-research` (import) — blogs, opinion pieces, industry perspectives

## Execution Guidance

- This is the most "intellectual" tactic — requires judgment about what matters
- thematic-coding helps identify patterns across papers
- CC must actively seek counter-evidence (intellectual honesty)
- Output is not a list but a structured argument
- Themes should emerge from reading, not be imposed a priori

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## Available SOPs

Optional, no fixed order; the final leaf is always a sop.

| SOP | When to use |
| --- | --- |
| knowledge-acquisition-paper-research | Full-depth paper reading with raw text extraction. Import of literature-engine/literature-research skill. Must read fullText (true) — equations, hyperparameters, specific claims extracted. |
| knowledge-acquisition-paper-search | AI-summarized paper reading for intermediate depth. Import of literature-engine/literature-search skill. Must call get_paper_content for every analyzed paper. |
| knowledge-acquisition-web-research | Full-page web reading for non-academic perspectives — blogs, tech reports, product pages, industry analysis. Import of web-browsing/web-research skill. Must fetch full page via apify for every analyzed page. |
| thematic-coding | Identify recurring themes across papers using qualitative coding methodology. Produces a codebook with theme definitions, supporting evidence, and frequency counts. Used by narrative-review. |

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