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CustomerNewsletter: Skill for Claude Code

.github/skills/events-extraction/SKILL.md

events-extraction is a skill for Claude Code, Codex from briancl2/CustomerNewsletter. It costs 71 tokens per session (1,993 once invoked), scanned A, original, MIT.

A workflow for collecting upcoming events and webinars from web pages and formatting them for a newsletter. Webinars are online events; events can be classified as virtual, in-person, or hybrid.

In plain words
What is it for?
Use it in Phase 2 with the required event-source artifact and source configuration to fetch event details, classify them, and create the newsletter events section.
Why use it?
It avoids visiting each event page and formatting every entry by hand. It also applies consistent categories and separates event types in the output.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

This is briancl2/CustomerNewsletter's own configuration. It tells Claude Code and Codex how to work on CustomerNewsletter itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything CustomerNewsletter configures →

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is python3 tools/extract_event_sources.py <START_DATE> <END_DATE>.

not rated 11repo 3mo ago A scan 71 tokens original MIT
View source ↗ briancl2/CustomerNewsletter briancl2.github.io
Reuse

Borrowing it

Nothing to install: this file belongs to briancl2/CustomerNewsletter. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/briancl2/CustomerNewsletter/main/.github/skills/events-extraction/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/briancl2/CustomerNewsletter

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for events-extraction

README.md
[![agentmods](https://agentmods.dev/badge/skills/briancl2/customernewsletter/events-extraction/github.svg)](https://agentmods.dev/skills/briancl2/customernewsletter/events-extraction)
Your own site
<a href="https://agentmods.dev/skills/briancl2/customernewsletter/events-extraction"><img src="https://agentmods.dev/badge/skills/briancl2/customernewsletter/events-extraction/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for events-extraction

Your own site · 80×15
<a href="https://agentmods.dev/skills/briancl2/customernewsletter/events-extraction"><img src="https://agentmods.dev/badge/skills/briancl2/customernewsletter/events-extraction.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 71 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,993 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00071 $0.01993
Opus 5 $0.00036 $0.00996
Sonnet 5 $0.00014 $0.00399
Haiku 4.5 $0.00007 $0.00199

Measured 9d ago against content hash 9a1d9f57cc62, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

events-extraction scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.github/skills/events-extraction/SKILL.md · 191 lines

How it starts

The opening of the file, as written. The whole thing — 191 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Events Extraction

Extract, classify, and format upcoming events and webinars for the newsletter.

Quick Start

  1. Receive list of event URLs (5-15 typical)
  2. Run python3 tools/extract_event_sources.py <START_DATE> <END_DATE>
  3. Record the phase2_event_sources receipt for the generated JSON
  4. Fetch each URL and extract event details
  5. Classify: Virtual, In-person, or Hybrid
  6. Assign canonical categories (max 2, prefer 1)
  7. Format into tables and bullet lists
  8. Write output to workspace/newsletter_phase2_events_YYYY-MM-DD.md

Sequencing: This phase starts only after Phase 1C discoveries have been written and receipted.

Inputs

  • Deterministic Phase 2 event-source artifact (mandatory):
    • workspace/newsletter_phase2_event_sources_YYYY-MM-DD.json
    • Generated by: python3 tools/extract_event_sources.py <START_DATE> <END_DATE>
  • Deterministic source config (required by extractor):
    • kb/EVENT_SOURCES.yaml
  • Optional direct URLs (fallback only when artifact is missing):
    • https://github.com/resources/events
    • https://developer.microsoft.com/en-us/reactor/series/S-1625/
    • https://developer.microsoft.com/en-us/reactor/series/S-1631/
    • Note: Reactor series IDs are curated seeds and should be refreshed during KB maintenance.
  • Curator notes file (optional): workspace/Jan.md or similar
  • COLLECTION_DATE: Date for filename (defaults to today)

Output

  • File: workspace/newsletter_phase2_events_YYYY-MM-DD.md

Core Workflow

Step 0: Deterministic Source Extraction

Run deterministic extraction before event curation:

python3 tools/extract_event_sources.py <START_DATE> <END_DATE>

Then verify output exists:

  • workspace/newsletter_phase2_event_sources_<END_DATE>.json

If this phase is part of a full run, record receipt immediately after writing the JSON:

bash tools/record_phase_receipt.sh <START_DATE> <END_DATE> phase2_event_sources workspace/newsletter_phase2_event_sources_<END_DATE>.json

Read the full file on GitHub · 191 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 191 lines · 71 tokens per session scan A 9a1d9f57cc62

Subscribe to this mod's changes

events-extraction is a skill published in the GitHub repository briancl2/CustomerNewsletter (11 stars, last pushed 3mo ago), licensed MIT. It adds 71 tokens to every session and 1,993 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Researchagentic-workflowsagentscopilotllmopsmkdocsnewsletter
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