Agent skill

Narrative

by Muuuun in Muuuun/luxas

Narrative discipline for research reports — article-type templates (empirical / feasibility / comparison / policy-zh) and the feedback revision protocol that keeps outline, prose, and figures…

MITAuto-check passedResearch & Science

Install Narrative

skills CLI
$ npx skills add Muuuun/luxas --skill narrative -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Muuuun/luxas narrative --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Muuuun/luxas.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/narrative .claude/skills/narrative && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
narrative
GitHub stars
1.2k
Token cost
~1.5k tokens
SKILL.md length
736 words
Files
6 (incl. references)
Skills in repo
9
Repo updated
First seen
Licence
MIT

At a glance

Narrative discipline for research reports — article-type templates (empirical / feasibility / comparison / policy-zh) and the feedback revision protocol that keeps outline, prose, and figures…

  • Works in 2 steps: Revision protocol — how to absorb… → Article-type templates — positive…
  • Tasks that involve Deep research
  • SKILL.md covers First draft (thin — most rules…, Revision protocol (core) and Number provenance (interaction…
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Narrative is an agent skill from Muuuun/luxas. Narrative discipline for research reports — article-type templates (empirical / feasibility / comparison / policy-zh) and the feedback revision protocol that keeps outline, prose, and figures coherent across many feedback rounds.

Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including reference files (for example `references/figure_narrative.md`, `templates/comparison.md` and `templates/empirical.md`). Compatibility notes: Always available. No external dependencies.

It sits in Research & Science, covering Deep research. The repository describes itself as: An autonomous research colleague — from a question to a compiled manuscript, while you sleep. The licence is MIT.

When your agent uses it

  • Tasks that involve Deep research

Example prompts

  • “/narrative”

Requirements

  • Compatibility (from SKILL.md): Always available. No external dependencies.
  • Pre-approved tools (allowed-tools): read

Workflow steps

2 steps, taken from the first numbered list in SKILL.md.

  1. Revision protocol — how to absorb PI/user feedback without the report
  2. Article-type templates — positive examples of section logic per

What it can do on your machine

Read from SKILL.md and the folder at commit 9f77cef. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • read

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Always available. No external dependencies.

    From compatibility in the SKILL.md frontmatter.

Context cost

Narrative loads about 1.5k tokens when it runs, and up to ~2.1k if it reads all its reference files. Until then it costs about 60 tokens; SKILL.md has 736 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~60
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Muuuun/luxas at commit 9f77cef, republished under its MIT licence (© Muuuun). 736 words, ~1,459 tokens.

Download SKILL.mdSave it as .claude/skills/narrative/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
narrative
description
Narrative discipline for research reports — article-type templates (empirical / feasibility / comparison / policy-zh) and the feedback revision protocol that keeps outline, prose, and figures coherent across many feedback rounds.
allowed-tools
read
compatibility
Always available. No external dependencies.

Narrative Skill

Two jobs, in order of importance:

  1. Revision protocol — how to absorb PI/user feedback without the report degrading back into a patchwork (most narrative damage happens during feedback rounds, not first drafts).
  2. Article-type templates — positive examples of section logic per article type, consumed at outline time.

This skill is the delta on top of brain.md's <report_synthesis_protocol> (outline-first, claims-as-titles, lab-book test, anti-stacking pass). It does not repeat those rules — it adds what they lack: per-type section logic, the figure-narrative binding, and what to do when feedback arrives.

First draft (thin — most rules live in brain.md)

  1. Pick the article type and record it as the first line of notes/report_outline.md: type: empirical | feasibility | comparison | policy-zh | survey. Surveys: stop here and follow skills/review/ + skills/survey-methodology/ instead — never both pipelines.
  2. Read templates/<type>.md BEFORE writing the outline. The template gives the section logic for that type; your outline instantiates it with this project's claims. The lab-book test catches structure that mirrors the experiment DAG; the template shows what to write instead.
  3. Read references/figure_narrative.md before commissioning figures. The outline must name its Figure 1 (schematic) and its hero figure (the one figure that settles the central claim) — both are outline-level decisions, not afterthoughts.

Revision protocol (core)

Every feedback batch that touches the report gets classified BEFORE any edit. Mixed batches: tag every item first, edit second (tag-all-before- edit-any) — append-only reviews/pi_feedback.md means earlier instructions never vanish, so there is no need to rush.

Add the class tag to each checklist line in notes/memory.md (the existing pi_correction_protocol checklist — same boxes, one tag + one-line rationale extra):

- [ ] <instruction verbatim>  [class: local-fix | section-rewrite | restructure — <one-line why>]
Class 1 — local-fix (a number, a wording, a citation)

The pi_correction_protocol order applies unchanged: ledger first, report second. Then:

  • grep report.tex for OTHER occurrences of the corrected number (abstract, captions, tables — printed values drift in packs, not alone).
  • re-read the first sentence of the touched paragraph against its section's outline thesis (10 seconds — does the paragraph still serve the claim?).
  • the outline is NOT touched — unless the corrected number appears in, or defines, the central-claim sentence (e.g. a threshold comparison like "99.987% < 99.99%"). Then this is not a local-fix; reclassify as restructure and follow that flow.
Class 2 — section-rewrite (a section's argument is wrong/weak)

Precondition: if the feedback strikes an L2 claim, the experiment re-spawn (ledger fix) comes FIRST; this class begins only after notes/experiments.md § L2.X reflects the new physics.

  1. Edit that section's block in notes/report_outline.md first (thesis / evidence / synthesis move).
  2. Rewrite the section from outline + ledger — single-section scope (mv the old text into the editor's view, don't patch sentence by sentence around a broken spine).
  3. Check the transitions: the last paragraph of the previous section and the first of the next still hand over correctly.
Show full SKILL.md (286 more words)Show less
Class 3 — restructure (the central claim changes)

Default triggers — burden of proof is reversed. Any of:

  • feedback strikes a headline finding (an L2 claim quoted in the abstract),
  • feedback contradicts a sentence of the abstract,
  • experiments are added or removed after the report exists.

→ classify as restructure BY DEFAULT. Downgrading to a smaller class requires a one-line written justification on the checklist line.

Flow:

  1. Re-derive the WHOLE outline (new central claim, possibly new type template consultation). Diff old vs new outline.
  2. Walk report.tex section by section against the new outline — rewrite what the diff touches, keep what it doesn't.
  3. Figure re-audit: does the hero figure still settle the NEW central claim? If not, commission a replacement — and the illustrator_write spawn task must quote the NEW claim text (spawn prompts are frozen snapshots; re-spawning with the old task resurrects the old framing).
  4. Re-verify every already-ticked checkbox in notes/memory.md PI sections. Prose-level feedback ("stop calling it deterministic") lives only in report.tex — a rewrite can silently resurrect what an earlier round corrected. Each previously-ticked box gets re-checked against the new text; re-tick or re-fix.
Pre-finish reconciliation

Before finish() (and before the final PI review that the finish gate requires): one outline-vs-tex walkthrough — for each section, first paragraph vs outline thesis. Attach the outline verbatim to the final request_pi_review so PI reviews the argument, not just the prose.

Number provenance (interaction with correctness gates)

Rewrites must not orphan numbers. Every quantitative value in report.tex traces to a results.json computed.* field plus a stated transform (rounding, unit change). After a restructure, sweep the rewritten sections for numbers with no surviving source — flag, don't guess. Char-for-char identity is NOT required (rounding and Chinese prose legitimately reformat); traceability is.

© Muuuun, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files (references) in skills/narrative of Muuuun/luxas.

  • SKILL.md
  • references/figure_narrative.md
  • templates/comparison.md
  • templates/empirical.md
  • templates/feasibility.md
  • templates/policy-zh.md

Open the folder on GitHubat commit 9f77cef

Compare with similar skills

Narrative next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Narrative compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Narrative this skillMuuuun/luxas1.2k—~1.5kAutomated safety check: PassMIT
GitHub Deep Researchbytedance/deer-flow83k5 repos~1.3kAutomated safety check: PassMIT
Deep Research WorkflowTokenRhythm/opensquilla7.1k—~1.3kAutomated safety check: PassApache-2.0
X Researchrohunvora/x-research-skill1.2k1 repos~1.6kAutomated safety check: PassNone
Deep Researchsanjay3290/ai-skills43110 repos~683Automated safety check: NotesApache-2.0
ResearchWeizhena/Deep-Research-skills2.3k3 repos~1.1kAutomated safety check: PassMIT

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Questions about Narrative

What does Narrative do?

Narrative discipline for research reports — article-type templates (empirical / feasibility / comparison / policy-zh) and the feedback revision protocol that keeps outline, prose, and figures…. Narrative is an agent skill from Muuuun/luxas. Narrative discipline for research reports — article-type templates (empirical / feasibility / comparison / policy-zh) and the feedback revision protocol that keeps outline, prose, and figures coherent across many feedback rounds.

When should I use Narrative?

Narrative fits situations like: tasks that involve Deep research.

How do I install Narrative in Claude Code?

Run `npx skills add Muuuun/luxas --skill narrative -a claude-code`. Or copy the skill folder (skills/narrative in Muuuun/luxas) into .claude/skills/narrative in your project. Claude Code loads it when a task matches its description.

How do I install Narrative in Codex?

Run `npx skills add Muuuun/luxas --skill narrative -a codex`. Or copy the skill folder (skills/narrative in Muuuun/luxas) into .agents/skills/narrative in your project. Codex loads it when a task matches its description.

Can I use Narrative in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Muuuun/luxas --skill narrative -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/narrative, .gemini/skills/narrative, .github/skills/narrative and .opencode/skills/narrative in your project.

What does Narrative need to run?

SKILL.md names no scripts, command-line tools or credentials: Narrative is instructions for the agent only. Its frontmatter pre-approves these tools: read. Compatibility (from SKILL.md): Always available. No external dependencies..

Does Narrative access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Narrative safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Narrative use?

Narrative is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Narrative use?

About 1.5k tokens (SKILL.md is roughly 5.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 659 tokens, read only when the agent opens those files.

What are the alternatives to Narrative?

Skills that share tags, products or a category with Narrative: GitHub Deep Research (bytedance/deer-flow, 83k stars), Deep Research Workflow (TokenRhythm/opensquilla, 7.1k stars), X Research (rohunvora/x-research-skill, 1.2k stars) and Deep Research (sanjay3290/ai-skills, 431 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Narrative?

Muuuun (a GitHub user) maintains it in Muuuun/luxas, which has 1,169 GitHub stars. The repository holds 9 skills in this directory. The repository was last updated on September 6, 2026.

Source: Muuuun/luxas on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.