agentleFS
manazoid4manazoid4/maz-works-knowledge-vault/skills/defuddle/SKILL.md

defuddle

Skill0 starsChanged 3 months agoMITView on GitHub

Strip clutter from web pages before ingesting into the wiki. Removes ads, navigation, headers, footers, and boilerplate: leaving clean readable markdown that saves 40-60% tokens. Triggers on: defuddle, clean this page, strip this url, fetch and clean, clean web content before ingesting, strip ads, remove clutter, clean URL content, readable markdown from URL.

  • Installs packages

65 other projects use a version of this, 1 of them edited.

Adopted by

Most recently taken up by

Used with

Projects with it also use results-report, knap and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • Galaxy-DawnSkill

    results-report

    This skill should be used when the user asks to "write an experiment report", "summarize experimental results", "do experiment retrospection", "write a results report", "写实验总结报告", "写实验复盘", or mentions turning completed experiment artifacts into a structured, decision-oriented research report. It assumes strict analysis should come from `results-analysis` first.

    Also in 3 projects that use this

  • lucasmaher-hashSkill

    knap

    Render Markdown from templates and structured data using Knap CLI. Use when the user asks to apply a Knap template, turn JSON or CSV data into notes, batch-generate Markdown files, or format Defuddle output into a note.

    Also in 4 projects that use this

  • Clay-HHKSkill

    daily-coding

    Daily coding assistant that auto-triggers when writing/modifying code, providing a core checklist.

    Also in 3 projects that use this

  • Clay-HHKSkill

    kaggle-learner

    This skill should be used when the user asks to "learn from Kaggle", "study Kaggle solutions", "analyze Kaggle competitions", or mentions Kaggle competition URLs. Provides access to extracted knowledge from winning Kaggle solutions across NLP, CV, time series, tabular, and multimodal domains.

    Also in 3 projects that use this

  • kharlamenkodevSkill

    bug-detective

    Also in 3 projects that use this

  • az9713Skill

    vault-health

    Audit vault health: unresolved links, orphan notes, dead-end files, missing frontmatter, structural gaps. Produces an actionable report note with prioritized fix suggestions. Use when wanting to clean up, organize, or assess the current state of the vault.

    Also in 3 projects that use this

  • +2 more from Clay-HHK

The file

We split this skill into the rules it gives an agent

6 rules. 0 are common, 5 are distinctive, and 1 is very specific to this project.

  • 0

    Common

    Most of the 59 edited versions we read keep these.

  • 5

    Distinctive

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Use this before any URL ingestion.

    line 11
  2. Distinctive:

    After running defuddle, prepend the source URL and fetch date:

    line 41
  3. Distinctive:

    If defuddle is not installed, check:

    line 70
  4. Distinctive:

    If not installed: use WebFetch directly.

    line 76
  5. Distinctive:

    Run the save command above

    line 85
  6. Very specific:

    When working on this skill, apply the 10-principle loop.

    line 92

“Common” is measured: kept by at least 6 in 10 of the 59 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

defuddle: Web Page Cleaner

Defuddle extracts the meaningful content from a web page and drops everything else: ads, cookie banners, nav bars, related articles, footers, social sharing buttons. What remains is the article body as clean markdown.

Use this before any URL ingestion. It is optional but strongly recommended. It cuts token usage by 40-60% on typical web articles and produces cleaner wiki pages.

Substrate note (v1.7+): Unlike obsidian-markdown / obsidian-bases / json-canvas (where we defer to kepano/obsidian-skills), this defuddle workflow comes from the vault's MIT-licensed upstream foundation; kepano's marketplace does not ship a defuddle skill. The underlying defuddle-cli is independent and lives at github.com/kepano/defuddle.


Install

npm install -g defuddle-cli

Verify: defuddle --version


Usage

Clean a URL directly

defuddle https://example.com/article

Outputs clean markdown to stdout.

Save to .raw/

defuddle https://example.com/article > .raw/articles/article-slug-$(date +%Y-%m-%d).md

Add frontmatter header after saving

After running defuddle, prepend the source URL and fetch date:

SLUG="article-slug-$(date +%Y-%m-%d)"
{ echo "---"; echo "source_url: https://example.com/article"; echo "fetched: $(date +%Y-%m-%d)"; echo "---"; echo ""; defuddle https://example.com/article; } > .raw/articles/$SLUG.md

Clean a local HTML file

defuddle page.html

When to Use

Use defuddle when:

  • Ingesting a news article, blog post, or documentation page from a URL
  • The page has a lot of surrounding content (most web pages do)
  • You want to stay within token budget on a long article

Skip defuddle when:

  • The source is already a clean markdown or PDF file
  • The page is a dashboard, app, or structured data (defuddle expects article-style content)
  • defuddle is not installed and the article is short enough to process raw

Fallback

If defuddle is not installed, check:

which defuddle 2>/dev/null || echo "not installed"

If not installed: use WebFetch directly. The content will be less clean but still workable.


Integration with /wiki-ingest

The /wiki-ingest skill checks for defuddle automatically when a URL is passed. You do not need to run defuddle manually before ingesting a URL. The ingest skill will call it if available.

To manually clean a page and save before ingesting:

  1. Run the save command above
  2. Then: ingest .raw/articles/[slug].md

How to think (10-principle mapping)

When working on this skill, apply the 10-principle loop. See skills/think/SKILL.md for the canonical framework.

#PrincipleApplication here
1OBSERVE (ext)Which URL? What's actually on the page? Don't assume the title matches the content.
2OBSERVE (int)Am I assuming the page has the content the user expects? Verify before extracting.
3LISTENDid the user say "the article" (main content only) or "the link" (everything visible)?
4THINKStrip boilerplate, preserve structure, capture metadata. Quote URLs in shell to avoid injection.
5CONNECT (lat)How does this domain typically render? Some sites mangle defuddle's heuristics; track those.
6CONNECT (sys)Shells out to defuddle-cli (kepano); output lands in .raw/ for wiki-ingest pickup.
7FEELClean markdown that reads like the original, not boilerplate residue.
8ACCEPTSome pages don't extract well. Flag and move on; don't force when the heuristic loses.
9CREATEMarkdown to stdout, redirected to .raw/articles/<slug>-<date>.md.
10GROWExtraction failures suggest defuddle-cli upgrade or alternative extractor — track them as backlog.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.