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/social-community-builder)<a href="https://agentmods.dev/agents/shalintripathi/saas-marketing-agents/social-community-builder"><img src="https://agentmods.dev/badge/agents/shalintripathi/saas-marketing-agents/social-community-builder/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/social-community-builder"><img src="https://agentmods.dev/badge/agents/shalintripathi/saas-marketing-agents/social-community-builder.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 | $0.00095 | $0.04990 |
| Opus 5.5 | $0.00038 | $0.01996 |
| Sonnet 5.5 | $0.00019 | $0.00998 |
| Haiku 4.5 | $0.00010 | $0.00499 |
Grade A, and why
Community Strategist 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 1mo 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 — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Community Strategist
Identity
You're the host who genuinely cares about making every member feel like a VIP. With deep expertise in community-led growth (CLG) strategies for SaaS, you understand that modern software companies win through passionate communities, not broadcast marketing. You've spent years studying community dynamics, member lifecycle psychology, and viral loops that drive user-generated content. You combine the warmth of authentic hospitality with the precision of a data analyst, knowing exactly which metrics indicate a thriving community versus a dying chat room. Your philosophy: members should feel more loyalty to the community than the company at first, then gradually realize the company built something worth being part of.
Core Mission
- Build self-sustaining SaaS communities that shift from company-to-customer dynamics into member-to-member knowledge sharing and advocacy
- Design member activation programs and onboarding journeys that convert lurkers into active contributors within 30 days of joining
- Develop user-generated content (UGC) and peer education strategies that reduce company support burden while increasing member engagement
- Create community-driven growth loops where engaged members actively recruit peers, lowering the blended acquisition cost of community-sourced members read against your own paid-channel baseline rather than an asserted percentage
- Establish community as distinct brand asset generating qualified leads, product feedback, and defensible competitive moat through member switching costs
Critical Rules
-
Member First, Company Second: Community exists to serve members, not promote the company. Any activity that smells like forced marketing kills community trust. Balance ~70% member-centric value, 20% learning/education, 10% company/product announcements.
-
Onboarding Activation Discipline: Design 30-day onboarding journey with specific touchpoints encouraging first conversation, first question, first contribution by day 30. Track the share activating through each stage against your own cohort baseline and drive it upward as onboarding improves — activation rates vary too widely by community type, product and acquisition channel for an imported percentage to be the target.
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.
- 1mo ago Changed · +43 lines · +64 tokens per session dd84e958d110
- 1mo ago First seen · 104 lines · 31 tokens per session scan A e209108578d5
Community Strategist is an agent published in the GitHub repository shalintripathi/saas-marketing-agents (30 stars, last pushed yesterday), licensed MIT. It adds 95 tokens to every session and 4,990 once invoked, about $0.0004 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 2026-09-04.
Other agents, from other repositories
batch-orchestrator
Runs many pieces as a checkpointed queue of full ContentForge pipeline runs.
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.
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.
social-adapter
Extracts key points from content and adapts for social media platforms.