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Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/michelbr84-gmail-organize
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: documents, writing
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/gmail-organize
What's inside
- Skill name
gmail-organize- Description
- Inbox organization advisor. Detects unlabeled emails, clusters them by sender, domain, subject pattern, and content type, then suggests a complete label taxonomy with Gmail filter rules. Prescriptive counterpart to gmail-labels (which is descriptive). Supports --pdf and --pt (Portuguese).
- License
- MIT
- Instructions
- 118 lines in SKILL.md · view on GitHub
Agent Skills spec issues
- files: referenced but missing: scripts/organization_analyzer.py, templates/organization-report.md, scripts/generate_pdf_report.py
Files (1)
- SKILL.md
SKILL.md (first lines)
# gmail-organize — Inbox Organization Advisor ## Purpose Analyze emails that lack useful labels and suggest a complete, actionable label taxonomy with Gmail filter rules. While `gmail-labels` answers **"how is your inbox organized today"**, this skill answers **"how should your inbox be organized"**. ## Trigger - `/gmail organize month` - `/gmail organize week` - `/gmail organize year` - `/gmail organize --from 2026-02-01 --to 2026-03-01` - `/gmail suggest-labels month` (alias) ## Supported Flags All standard period and filter flags apply, plus: - `--pdf` — Generate PDF version of the organization report - `--pt` — Output report in Portuguese (default: English) - `--include-spam` — Include spam when analyzing clutter patterns - `--unread-only` — Focus on unread backlog organization ## What It Analyzes 1. **Unlabeled emails** — Messages with only `INBOX` or `CATEGORY_*` labels 2. **Sender patterns** — Frequent senders, domains, automated origins 3. **Subject patterns** — Recurring keywords, prefixes, formats 4. **Content type** — Newsletters, receipts, notifications, human conversation 5. **Domain clusters** — Groups by sender domain (e.g., all `@github.com`) 6. **Repetitive messages** — Same sender + similar subject = pattern ## Clustering Strategy The analyzer identifies natural groupings and maps them to label suggestions: | Pattern Detected | Suggested Label | Confidence | |-----------------|----------------|------------| | Recurring newsletter sender | `Newsletters` | High | | Payment/receipt subjects | `Receipts` | High | | Bank/financial domains | `Finance` | High | | Travel booking confirmations | `Travel` | Medium | | Work-related domains | `Work` | Medium | | Family member addresses | `Family` | Medium | | AI tool notifications | `AI Tools` | Medium | | Security alerts/2FA | `Security` | High | | Shopping/order confirmations | `Shopping` | High | | Service notifications | `Notifications` | High | | Subscription confirmations | `Subscriptions` | Medium | | Unanswered threads | `Follow Up` | Medium | Custom clusters are generated dynamically based on actual data — not limited to these defaults. ## Workflow 1. **Fetch data** for the period 2. **Filter to unlabeled** — Keep only messages without custom labels 3. **Run `scripts/organization_analyzer.py`** to cluster and suggest 4. **Generate report** using `templates/organization-report.md` 5. Optionally generate PDF via `scripts/generate_pdf_report.py` ## Report Output ### Sections 1. **Overview** - Total emails analyzed - Unlabeled count and percentage - Clusters found 2. **Suggested Label Taxonomy** - Label name - Rationale - Estimated volume - Confidence (High / Medium / Low) 3. **Cluster Examples** - 3–5 sample emails per cluster - Sender, subject, date 4. **Suggested Gmail Filters** - Match criteria (from, subject, has:attachment, etc.) - Recommended action (apply label, skip inbox, etc.) - Target label 5. **Organization Score (0–100)** - Current organization level - Improvement opportunity ### Output Files | Flag | Output | |------|--------| | (default) | `GMAIL-REPORT-ORGANIZE.md` | | `--pdf` | `GMAIL-REPORT-ORGANIZE.pdf` | | `--pt` | Report in Portuguese | | `--pdf --pt` | PDF in Portuguese | ## V1 Scope (Current) - ✅ Analysis and clustering - ✅ Label taxonomy suggestion - ✅ Gmail filter rules as text - ✅ Organization score - ✅ Markdown and PDF output - ✅ Portuguese language support - ❌ Automatic label application (future v2) - ❌ Filter export to Gmail format (future v2) ## Integration This skill uses `gmail-organization-analysis` subagent for the clustering phase during full reports, and can also run standalone via `/gmail organize`.
From michelbr84/gmail-report-claude, MIT.
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Signals
- Stars
- 0
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Mar 6, 2026 (7 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.
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Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
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gmail-organize skill. Agent Mart. https://agentmart.dev/skills/michelbr84-gmail-organize (last updated 2026-10-24)