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Agent skill

Wow Digest

by glebis in glebis/claude-skills

Daily digest of 3-7 genuinely surprising items from newsletters and Telegram channels.

MITAuto-check passedWriting & Content

Install Wow Digest

skills CLI
$ npx skills add glebis/claude-skills --skill wow-digest -a claude-code

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

GitHub CLI
$ gh skill install glebis/claude-skills wow-digest --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/glebis/claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/wow-digest .claude/skills/wow-digest && 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
wow-digest
GitHub stars
391
Token cost
~1.2k tokens
SKILL.md length
546 words
Files
9 (incl. scripts)
Skills in repo
92
Repo updated
First seen
Licence
MIT

At a glance

Daily digest of 3-7 genuinely surprising items from newsletters and Telegram channels.

  • Works in 8 steps: Run scripts/ingest.py to pull and… → Run scripts/enrich.py to fetch full… → Run scripts/salience_filter.py to drop… → …
  • The user says /wow-digest
  • SKILL.md covers Purpose, Workflow, Manual run and Dry-Run Mode, plus 6 more sections
  • Runs Python scripts from its folder; calls python3

What it does

Wow Digest is an agent skill from glebis/claude-skills. Daily digest of 3-7 genuinely surprising items from newsletters and Telegram channels. Scores content for epistemic friction, not just relevance. Appends to daily note. Use when the user says "/wow-digest", "run the wow digest", "what's surprising today", "morning reading", or "digest my newsletters".

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including scripts (for example `config/sources.yaml`, `scripts/enrich.py` and `scripts/feedback.py`).

It sits in Writing & Content, covering Newsletters and Note-taking. It works with Telegram. The repository describes itself as: Collection of Claude Code skills for enhanced AI workflows. The licence is MIT.

When your agent uses it

  • The user says /wow-digest
  • Run the wow digest
  • Whats surprising today
  • Morning reading

Example prompts

  • “/wow-digest”
  • “run the wow digest”
  • “s surprising today”
  • “/wow-digest”

Requirements

  • Python 3

Workflow steps

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

  1. Run scripts/ingest.py to pull and normalize candidates from all sources
  2. Run scripts/enrich.py to fetch full content for link-only newsletters (LinkedIn, beehiiv, Substack)
  3. Run scripts/salience_filter.py to drop obvious noise (marketing, payments, greetings)
  4. Run scripts/wow_score.py on filtered candidates to score and select WOW items
  5. Append selected items to today's daily note under ## Reading
  6. Save raw candidates to .wow-eval/candidates/YYYYMMDD.jsonl for replay
  7. Archive processed newsletter emails via GWS
  8. During eval phase: run scripts/feedback.py to collect human verdicts

What it can do on your machine

Read from SKILL.md and the folder at commit 3b88261. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 5 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python3

    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.

Context cost

Wow Digest loads about 1.2k tokens when it runs. Until then it costs about 78 tokens; SKILL.md has 546 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~78
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from glebis/claude-skills at commit 3b88261, republished under its MIT licence (© glebis). 546 words, ~1,249 tokens.

Download SKILL.mdSave it as .claude/skills/wow-digest/SKILL.md (or your agent's skills folder). This skill also uses 8 other files; get the full folder from GitHub.
name
wow-digest
description
Daily digest of 3-7 genuinely surprising items from newsletters and Telegram channels. Scores content for epistemic friction, not just relevance. Appends to daily note. Use when the user says "/wow-digest", "run the wow digest", "what's surprising today", "morning reading", or "digest my newsletters".

wow-digest

Purpose

Pull last 24h of newsletters (email) and Telegram channel posts, filter noise, score survivors for genuine surprise against the user's focus and recent research, and append 3-7 WOW items to today's daily note.

Workflow

  1. Run scripts/ingest.py to pull and normalize candidates from all sources
  2. Run scripts/enrich.py to fetch full content for link-only newsletters (LinkedIn, beehiiv, Substack)
  3. Run scripts/salience_filter.py to drop obvious noise (marketing, payments, greetings)
  4. Run scripts/wow_score.py on filtered candidates to score and select WOW items
  5. Append selected items to today's daily note under ## Reading
  6. Save raw candidates to .wow-eval/candidates/YYYYMMDD.jsonl for replay
  7. Archive processed newsletter emails via GWS
  8. During eval phase: run scripts/feedback.py to collect human verdicts

Manual run

bash
python3 scripts/ingest.py --days 1 --output /tmp/wow-candidates.jsonl
python3 scripts/enrich.py --input /tmp/wow-candidates.jsonl --output /tmp/wow-enriched.jsonl
python3 scripts/salience_filter.py --input /tmp/wow-enriched.jsonl --output /tmp/wow-filtered.jsonl
python3 scripts/wow_score.py --input /tmp/wow-filtered.jsonl --output /tmp/wow-selected.json
# Then the skill appends to daily note and archives emails

Dry-Run Mode

When the user says /wow-digest --dry-run or "preview the digest", run the full pipeline but:

  1. Do NOT append to daily note
  2. Do NOT archive emails
  3. Instead, print the selected items with scores and hooks directly in the conversation

This lets the user preview what would be appended without side effects.

Context Sourcing

The scoring prompt uses three context signals from the vault (~/Brains/brain/):

  • {focus} — From My Focus.md, sections ## Current, ## Base, ## Primary (stops at ## Nice to have). This tells the scorer what the user cares about right now.
  • {research} — From ai-research/*.md files (last 30 days), parsed from filenames (YYYYMMDD-topic.md) and research_topic: frontmatter. Shows what the user has already investigated.
  • {recent_topics} — From Daily/YYYYMMDD.md headings (last 7 days), excluding ## do and ## log. Shows recent daily note themes.

If these files don't exist, scoring still works but with degraded personalization.

Dedup

Ingestion deduplicates against the last 7 days of .wow-eval/candidates/*.jsonl using SHA-256 hashes of title|source_name (case-insensitive). Same article shared to multiple channels or re-sent in a newsletter won't appear twice. Pass --no-dedup to ingest.py to skip.

Config

Edit config/sources.yaml to add/remove email patterns or Telegram channels. Edit config/wow_prompt.txt to tune the scoring prompt.

Show full SKILL.md (233 more words)Show less

Output Format

After scoring, append to today's daily note (Daily/YYYYMMDD.md) ABOVE the - - - separator, below any existing content:

markdown
## Reading

- **[Title]** (Source) — hook explaining WHY it's surprising
- **[Title]** (Source) — hook
...

_WOW digest · N candidates → M selected · YYYY-MM-DD_

CRITICAL: Always run date +"%Y%m%d" to get today's date. Never assume.

If ## Reading already exists in the daily note, append items to it rather than creating a duplicate section.

Archive

After appending to daily note, archive processed newsletter emails:

  1. Collect all message_id values from email candidates
  2. Run GWS batchModify to remove INBOX label
bash
gws gmail users messages batchModify \
  --params '{"userId":"me"}' \
  --json '{"ids":["ID1","ID2",...],"removeLabelIds":["INBOX"]}'

Eval Mode (first 2 weeks)

During eval phase, do NOT auto-archive. Instead:

  1. Run ingest + scoring as normal
  2. Present the selected items to the user with FULL CONTENT, not just titles. For each item show:
    • Title + source
    • The snippet (first 300-500 chars of actual content)
    • The LLM's hook and challenged_assumption
    • WOW score breakdown (relevance, surprise, bridge_value, predictability)
  3. Show all items in a single text block first so the user can read the content
  4. Then ask via AskUserQuestion: "Was this actually WOW?" with options: wow / meh / noise / already_knew
  5. Record feedback via scripts/feedback.py
  6. Show current feedback stats
  7. Only archive after user confirms

CRITICAL: The user CANNOT judge WOW from titles alone. Always show the snippet content. If the snippet is empty or too short, fetch the full email body via GWS before presenting.

To check if eval mode is active:

  • If .wow-eval/feedback.jsonl has fewer than 50 entries → eval mode
  • If 50+ entries → auto mode (archive without asking)

© glebis, 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 8 other files (scripts) in wow-digest of glebis/claude-skills.

  • SKILL.md
  • config/sources.yaml
  • config/wow_prompt.txt
  • requirements.txt
  • scripts/enrich.py
  • scripts/feedback.py
  • scripts/ingest.py
  • scripts/salience_filter.py
  • scripts/wow_score.py

Open the folder on GitHubat commit 3b88261

Compare with similar skills

Wow Digest 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.

Wow Digest compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Wow Digest this skillglebis/claude-skills391—~1.2kAutomated safety check: PassMIT
Youtube Processornicepkg/ai-workflow285—~1.3kAutomated safety check: NotesMIT
Communityericrisco/rsc-harness180—~3.4kAutomated safety check: PassMIT
Opencli Readerhimself65/finance-skills3.4k—~2.9kAutomated safety check: PassMIT
Internal Communications Writeranthropics/skills180k38 repos~378Automated safety check: PassApache-2.0
Whole-Book Explainer Noteslijigang/ljg-skills7.5k—~1kAutomated safety check: PassMIT

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Works with

Categories

Questions about Wow Digest

What does Wow Digest do?

Daily digest of 3-7 genuinely surprising items from newsletters and Telegram channels. Wow Digest is an agent skill from glebis/claude-skills. Daily digest of 3-7 genuinely surprising items from newsletters and Telegram channels.

When should I use Wow Digest?

Wow Digest fits situations like: the user says /wow-digest; run the wow digest; whats surprising today; morning reading.

How do I install Wow Digest in Claude Code?

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

How do I install Wow Digest in Codex?

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

Can I use Wow Digest 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 glebis/claude-skills --skill wow-digest -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/wow-digest, .gemini/skills/wow-digest, .github/skills/wow-digest and .opencode/skills/wow-digest in your project.

What does Wow Digest need to run?

Going by SKILL.md and its folder, Wow Digest needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.

Does Wow Digest 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 Wow Digest 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Wow Digest use?

Wow Digest 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 Wow Digest use?

About 1.2k tokens (SKILL.md is roughly 5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Wow Digest?

Skills that share tags, products or a category with Wow Digest: Youtube Processor (nicepkg/ai-workflow, 285 stars), Community (ericrisco/rsc-harness, 180 stars), Opencli Reader (himself65/finance-skills, 3.4k stars) and Internal Communications Writer (anthropics/skills, 180k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Wow Digest?

glebis (a GitHub user) maintains it in glebis/claude-skills, which has 391 GitHub stars. The repository holds 92 skills in this directory. The repository was last updated on October 8, 2026.

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