Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add OneWave-AI/claude-skills --skill gmail-to-crm-pipelinegit clone --depth 1 https://github.com/OneWave-AI/claude-skillsWrote 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.
[](https://agentmods.dev/skills/onewave-ai/claude-skills/gmail-to-crm-pipeline)<a href="https://agentmods.dev/skills/onewave-ai/claude-skills/gmail-to-crm-pipeline"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/gmail-to-crm-pipeline/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.
<a href="https://agentmods.dev/skills/onewave-ai/claude-skills/gmail-to-crm-pipeline"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/gmail-to-crm-pipeline.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00043 | $0.00733 |
| Opus 5 | $0.00022 | $0.00367 |
| Sonnet 5 | $0.00009 | $0.00147 |
| Haiku 4.5 | $0.00004 | $0.00073 |
Grade A, and why
gmail-to-crm-pipeline 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.
How it starts
The opening of the file, as written. The whole thing — 40 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Gmail-to-CRM Pipeline
Turn a Gmail inbox into a structured sales pipeline using Claude's MCP Connectors -- the Gmail connector reads and drafts email, and the Supabase connector persists CRM data. No external scripts or API keys required.
Workflow
- Connect. Verify the Gmail and Supabase MCP Connectors are available. On first run, create the CRM tables and seed config. Load ICP config from the
pipeline_configtable. Seereferences/configuration.md(first run, error handling) andreferences/crm-schema.md. - Search. Run the targeted Gmail search queries to find unread lead emails over the time window (default: last 24 hours). Collect unique message IDs and deduplicate. See
references/gmail-retrieval.md. - Parse. Read each unique message, strip signatures and disclaimers, and extract the structured field set. See
references/gmail-retrieval.md. - Extract. Build the lead profile (contact, company, inquiry, metadata) for each email. Set missing fields to
nullrather than guessing. Seereferences/lead-extraction.md. - Score. Score each lead on ICP fit (0-40), intent (0-35), and urgency (0-25), then apply adjustment modifiers. Map the total to a qualification tier and priority. See
references/scoring-model.md. - Draft. For each qualified lead (score >= 25), draft a personalized, tier-appropriate response and save it as a Gmail draft. Never auto-send. See
references/response-templates.md. - Log. Check for duplicates, then insert or update the lead in Supabase, log activity, and set the next action by priority. See
references/crm-schema.md. - Report. Query the pipeline snapshot and generate
lead-pipeline-report.mdin the working directory, then display the executive summary. Seereferences/pipeline-report.md.
Between runs, handle manual lead commands (mark contacted, move stage, disqualify, add note, schedule follow-up, query leads) and ICP/search customization. See references/configuration.md.
Hard Rules
What ships with it
7 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.
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.
- 9d ago First seen · 40 lines · 43 tokens per session scan A db26fd21e686
gmail-to-crm-pipeline is a skill published in the GitHub repository OneWave-AI/claude-skills (291 stars, last pushed 1mo ago), licensed MIT. It adds 43 tokens to every session and 733 once invoked, about $0.0002 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 2026-09-03.
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