# Review Newsletter Subscriptions

> Audit and evaluate newsletter subscriptions based on past 30 days of ingestion reports and suggestion review history. Analyzes newsletter frequency, suggestion conversion rates (accepted vs. rejected), and rubric blocklist vetoes to propose evidence-backed recommendations: Keep, Unsubscribe, or Adjust/Filter. Use whenever the user asks to 'review my newsletter subscriptions', 'audit newsletters', 'which newsletters should I unsubscribe', 'analyze newsletter subscriptions', 'evaluate newsletter value', '檢查電子報訂閱', '該取消訂閱哪些電子報', '分析電子報', or asks for advice on newsletter subscriptions.

- Skill: `allanbian1017/review-newsletter-subscriptions` (Agent Skill, multi-file: 6 files)
- Install (CLI): `npx skillmds@latest add allanbian1017/review-newsletter-subscriptions`
- Raw SKILL.md: https://api.skillmd.com/api/skills/allanbian1017/review-newsletter-subscriptions/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Security
- Author: allanbian1017 (https://skillmd.com/u/allanbian1017)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/allanbian1017/review-newsletter-subscriptions

---


# review-newsletter-subscriptions

Audit and triage newsletter subscriptions by cross-referencing ingestion reports with user suggestion review history over the past 30 days (or a custom date range).

---

## Workflow Overview

```mermaid
graph TD
    Trigger["User Request / Scheduled Audit"] --> RunScript["Step 1: Execute Telemetry Script<br/>(scripts/analyze_subscriptions.py)"]
    RunScript --> Triage["Step 2: Apply Multi-Dimensional Triage<br/>(references/triage_criteria.md)"]
    Triage --> Artifact["Step 3: Render Audit Artifact<br/>(newsletter_subscription_audit_YYYY-MM-DD.md)"]
    Artifact --> Guidance["Step 4: Present Inline Summary &<br/>Gmail Search / Unsubscribe Checklist"]
```

---

## Step 1 — Run Telemetry Script

Execute the bundled analysis script to obtain deterministic statistics across reports and suggestion files:

```bash
python3 .agents/skills/review-newsletter-subscriptions/scripts/analyze_subscriptions.py --days 30 --json
```

*(Note: If the user specified a custom window like 60 days or explicit dates, pass `--days N` or `--start-date YYYY-MM-DD --end-date YYYY-MM-DD`.)*

The script outputs structured JSON containing:
- `reports_count`: Total reports received per source in `reports/Newsletter_*`
- `reviewed_count`: Suggestions reviewed by user in `data/suggestions_reviewed.md`
- `accepted_count` / `rejected_count`: Feedback breakdown
- `filtered_count`: Suggestions blocked in `data/suggestions_filtered.md` with veto categories
- `acceptance_rate` ($A / R$) and `yield_rate` ($A / N$)
- Initial `triage` tag (`Keep`, `Unsubscribe`, `Adjust`, `Watch`)

---

## Step 2 — Qualitative Triage & Contextual Analysis

Consult `references/triage_criteria.md` to evaluate each newsletter source against quantitative thresholds and qualitative project alignments:

1. **🟢 Keep (繼續訂閱)**:
   - Acceptance Rate $\ge 60\%$ or Yield $\ge 20\%$.
   - Has produced high-value project skills, prompt templates, or architecture improvements.
2. **🔴 Unsubscribe (建議取消訂閱)**:
   - Acceptance Rate $< 40\%$ (with $\ge 3$ reviews), OR
   - High Hard-Veto ratio (e.g. Paper reading, Claude Code/Cursor), OR
   - High paywalled teaser / course sales marketing ratio, OR
   - High volume ($N \ge 10$) with negligible yield ($< 8\%$).
3. **🟡 Adjust / Filter (設定 Gmail 篩選器)**:
   - High volume ($N \ge 15$), positive core value ($A \ge 2$), but contains separable noise (e.g. weekend specials, robotics).
   - Formulate targeted Gmail filter query (e.g. `from:sender "Sunday Special"`).
4. **⚪ Watch (持續觀察)**:
   - Low volume ($N < 5$, $R < 2$) without strong negative signals, or suggestions currently in `data/suggestions_pending.md`.

---

## Step 3 — Generate Audit Artifact

Create a dedicated Markdown Artifact using `references/review_template.md`:
- Target Path: `<appDataDir>/brain/<conversation-id>/newsletter_subscription_audit_YYYY-MM-DD.md`
- Title: `# 📬 Newsletter Subscription Audit (YYYY-MM-DD ~ YYYY-MM-DD)`
- Contents:
  1. Telemetry Table (Markdown table from `analyze_subscriptions.py`)
  2. 🟢 **Keep**: Highlight top articles, accepted suggestions, and workflow impact.
  3. 🔴 **Unsubscribe**: Detail why they failed (cite rejection comments and veto rules) + exact Gmail search queries.
  4. 🟡 **Adjust & Filter**: Specific Gmail filter rules to eliminate noise while preserving core signal.
  5. ⚪ **Watch**: Pending or low-sample notes.
  6. ✅ **Action Checklist**: Checkboxes with copyable Gmail search queries for manual execution.

---

## Step 4 — Deliver Inline Summary in Chat

After rendering the artifact, present a concise executive summary directly in the chat conversation:
- Point the user to the generated audit artifact.
- Highlight the Top 3 to Keep and Top 3 to Unsubscribe with core rationale.
- Reiterate that destructive actions (unsubscribing or setting Gmail filters) remain strictly under human control, referencing the checklist in the artifact.