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CustomerNewsletter: Skill for Claude Code

.github/skills/content-curation/SKILL.md

content-curation is a skill for Claude Code, Codex from briancl2/CustomerNewsletter. It costs 85 tokens per session (3,066 once invoked), scanned A, original, MIT.

A newsletter-pipeline step that selects and organizes items from a Phase 3 working set into complete newsletter sections. Phase 3 is the stage where gathered material is chosen and shaped for publication.

In plain words
What is it for?
Use it during Phase 3 to prepare sections such as Lead, Copilot, Enterprise and Security, Platform, and Resources.
Why use it?
It provides a defined structure for turning collected material into newsletter-ready sections and uses earlier discoveries only when the working set is missing information.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions Claude Code; mentions OpenCode.

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/init_phase3_curated_sections.py START END.

not rated 11repo 3mo ago A scan 85 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/content-curation/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 content-curation

README.md
[![agentmods](https://agentmods.dev/badge/skills/briancl2/customernewsletter/content-curation.svg)](https://agentmods.dev/skills/briancl2/customernewsletter/content-curation)
Your own site
<a href="https://agentmods.dev/skills/briancl2/customernewsletter/content-curation"><img src="https://agentmods.dev/badge/skills/briancl2/customernewsletter/content-curation.svg" alt="Measured on agentmods" height="20"></a>
Per session 85 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,066 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 $0.00085 $0.03066
Opus 5 $0.00043 $0.01533
Sonnet 5 $0.00017 $0.00613
Haiku 4.5 $0.00009 $0.00307

Measured 8d ago against content hash 86bddfb06177, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

content-curation 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 8d 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/content-curation/SKILL.md · 202 lines

How it starts

The opening of the file, as written. The whole thing — 202 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Content Curation

Transform the Phase 3 working set into polished, newsletter-ready content sections, using Phase 1C discoveries only when the working set flags missing data.

Quick Start

  1. In orchestrated runs, first generate workspace/newsletter_phase3_working_set_YYYY-MM-DD.md with python3 tools/build_phase3_working_set.py START END
  2. If workspace/newsletter_phase3_curated_sections_YYYY-MM-DD.md does not exist yet, create the canonical scaffold with python3 tools/init_phase3_curated_sections.py START END
  3. Always edit the canonical scaffold in place. Do not create the curated sections artifact ad hoc through a generic create-file flow
  4. If the working set exists, use it as the primary Phase 3 input and do not reread raw discoveries, interim IDE files, or long reference docs unless it explicitly flags missing data
  5. Read Phase 1C discoveries from workspace/newsletter_phase1a_discoveries_*.md when no working set exists or the working set flags missing data
  6. Select items using selection criteria with range-aware depth targets
  7. Organize into full newsletter sections: Lead (optional), Copilot (Latest + IDE Parity), Enterprise and Security, Platform, Resources and Best Practices
  8. Apply formatting: bold terms, GA/PREVIEW labels, embedded links, strip metadata
  9. Validate the edited artifact with python3 tools/validate_phase3_curated.py START END workspace/newsletter_phase3_curated_sections_YYYY-MM-DD.md

Inputs

  • Phase 3 Working Set: workspace/newsletter_phase3_working_set_*.md (primary input in orchestrated mode)
  • Phase 1C Discoveries: workspace/newsletter_phase1a_discoveries_*.md (fallback only when the working set is absent or flags missing data)

Output

  • File: workspace/newsletter_phase3_curated_sections_YYYY-MM-DD.md
  • Target: range-aware depth

    • =60-day range: 24+ curated bullets

    • =30-day range: 18+ curated bullets

    • <30-day range: 12+ curated bullets
  • Content: Full section-ready material (no final intro/closing text)

Read the full file on GitHub · 202 lines

Files

What ships with it

4 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. 8d ago First seen · 202 lines · 85 tokens per session scan A 86bddfb06177

Subscribe to this mod's changes

content-curation is a skill published in the GitHub repository briancl2/CustomerNewsletter (11 stars, last pushed 3mo ago), licensed MIT. It adds 85 tokens to every session and 3,066 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.

Marketing and SEOWriting and docsagentic-workflowsagentscopilotllmopsmkdocsnewsletter
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