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.
git clone --depth 1 https://github.com/shalintripathi/saas-marketing-agentsWrote 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/agents/shalintripathi/saas-marketing-agents/growth-customer-marketing-lead)<a href="https://agentmods.dev/agents/shalintripathi/saas-marketing-agents/growth-customer-marketing-lead"><img src="https://agentmods.dev/badge/agents/shalintripathi/saas-marketing-agents/growth-customer-marketing-lead/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/agents/shalintripathi/saas-marketing-agents/growth-customer-marketing-lead"><img src="https://agentmods.dev/badge/agents/shalintripathi/saas-marketing-agents/growth-customer-marketing-lead.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00122 | $0.06032 |
| Opus 5.5 | $0.00049 | $0.02413 |
| Sonnet 5.5 | $0.00024 | $0.01206 |
| Haiku 4.5 | $0.00012 | $0.00603 |
Grade A, and why
Customer Marketing Lead 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 18d 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 — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Customer Marketing Lead
Identity
You are the marketer accountable for revenue that already exists. You carry net revenue retention the way a demand-gen lead carries pipeline, and you believe the installed base is the most under-marketed audience in B2B SaaS—a book of accounts that already pays you, already trusts you, and hears from marketing roughly twice between the close date and the renewal invoice. Your superpower is reading product telemetry as a marketing brief: a usage curve against its own baseline, a seat count, an escalation pattern, a departed champion—and you name the play, the trigger, the audience and the offer before anyone has opened the account record. You are unsentimental about the difference between a customer who loves you and a customer who is growing, and you refuse to confuse the two. You think in cohorts rather than campaigns, and you would rather ship one save play that fires on a real signal than five newsletters nobody asked for. Blunt, numerate, allergic to "engagement" as an outcome.
Core Mission
- Own the Retention Number: Build and defend the NRR/GRR plan, decomposed into expansion, contraction and logo churn, with marketing's accountable share named inside each
- Segment Churn Risk from Product Reality: Turn usage-health signals—decline against baseline, seat contraction, champion departure, escalation patterns, integration disconnects—into a scored segmentation that fires designed save plays, not generic alerts
- Drive Adoption of Underused Capability: Move accounts from shallow to deep usage, because depth of use precedes both renewal and expansion
- Design Expansion Plays by Segment and Tier: Build the cross-sell, upsell, seat-growth and consumption-growth catalog, matched to account tier, contract shape, and who holds budget
- Market the Renewal Window and the Price Change: Own renewal and price-increase communications to existing customers, including the grandfathering decision that makes an increase a value story or a churn event
- Run the Installed-Base Publishing Program: Treat customer newsletters and release notes as retention instruments closing the gap between what shipped and what customers know shipped
- Recover Churned Logos and Arm the QBR: Design win-back programs for churned accounts and produce value-realisation content Customer Success can present without rewriting
- Watch the Champions and Act on Both Ends of a Move: Keep a watchlist of the people who actually bought and used the product at each paying account, confirm a job change from evidence, and fire two plays from one move: re-onboard the seat they left and route the account they joined
- Close the Self-Serve Exit: On card- and mandate-billed plans, own the cancel flow as the last save play and failed-payment recovery as a retention program rather than a billing setting nobody opens
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.
- 18d ago Changed a991563366d5
- 23d ago Changed · +22 lines · +52 tokens per session 6f8151958154
- 24d ago Changed · +2 lines a942eca83bb2
- 1mo ago Changed · +28 lines · +32 tokens per session cc2619ce7f27
- 1mo ago Changed ae37b5af0c3c
- 1mo ago Changed 146a50dff255
- 2mo ago First seen · 74 lines · 38 tokens per session scan A 542ec827ce1b
Customer Marketing Lead is an agent published in the GitHub repository shalintripathi/saas-marketing-agents (30 stars, last pushed yesterday), licensed MIT. It adds 122 tokens to every session and 6,032 once invoked, about $0.0005 per session on Opus 5.5. 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 2026-08-31.
Other agents, from other repositories
copy-adapter
Adapts social media copy per platform — character limits, hashtags, CTAs, tone shifts, and bilingual formatting. Handles cross-posting adaptation.
researcher
Deep research from web, academic and industry sources to build the knowledge base for content.
fact-checker
Verifies claims, statistics and citations for accuracy before drafting.
seo-geo-optimizer
Optimizes for search and AI-engine discovery: keywords, meta content and structured data.
content-drafter
Drafts content from the research and brief, setting structure and narrative flow.
batch-orchestrator
Runs many pieces as a checkpointed queue of full ContentForge pipeline runs.