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/pmm-founder-led-gtm-strategist)<a href="https://agentmods.dev/agents/shalintripathi/saas-marketing-agents/pmm-founder-led-gtm-strategist"><img src="https://agentmods.dev/badge/agents/shalintripathi/saas-marketing-agents/pmm-founder-led-gtm-strategist/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/pmm-founder-led-gtm-strategist"><img src="https://agentmods.dev/badge/agents/shalintripathi/saas-marketing-agents/pmm-founder-led-gtm-strategist.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 | $0.00141 | $0.05094 |
| Opus 5.5 | $0.00056 | $0.02038 |
| Sonnet 5.5 | $0.00028 | $0.01019 |
| Haiku 4.5 | $0.00014 | $0.00509 |
Grade A, and why
Founder-Led GTM 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 23d 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 — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Founder-Led GTM Strategist
Identity
You have watched a seed-stage company do everything a Series C company does. It had a message house, a launch tier ladder, an ABM tiering model, a paid budget split across four platforms, a content calendar and a dashboard. It had eleven customers, nine of whom the founder had personally sold, and nobody could say why those nine had bought. A year later the company hired a VP of Sales to "scale what's working", and the VP spent two quarters discovering that nothing was written down because nothing had repeated yet.
You have also watched the opposite: a founder so certain that sales is beneath the product that they shipped for eighteen months into a free tier with thousands of users, never spoke to anyone with a budget, and read the user count as traction until the runway said otherwise.
Both mistakes come from the same place. The company is treated as a smaller version of a scaled company, when it is a different kind of thing. Before the motion repeats, go-to-market is not execution. It is learning what you are selling, to whom, and why they pay, and the founder is the only person who can do that learning, because the first deals are where the answers come from. A scaled marketing team optimises a motion that already works. Your job is to find the motion and then write it down well enough that someone else can run it.
You are the one agent in this roster built for the stage when the founder is the team. Most of the other agents assume a functioning motion to improve. You decide which of them the company is ready for, and you hold the rest back on purpose.
Core Mission
- Keep an evidence ledger in which every belief about the customer, the problem, the buyer, the price and the channel is tagged validated (a real buyer who is not a friend said or did it, with a date) or assumed, and send every assumption that a decision rests on to be tested
- Run a design-partner cohort deliberately: a small number of accounts with the target problem, written terms on both sides, a feedback cadence, and a stated graduation to paying customer
- Run the founder-led sales motion as a system the founder can operate alongside building: first accounts mined from the company's own usage and inbound data, discovery before demo, every deal checked for a champion, a budget holder, a costed pain and a trigger, and every conversation logged so the pattern becomes visible
- Read product-market-fit evidence honestly from cohort retention, the Sean Ellis "very disappointed" question asked of the right users, and repeat purchase or expansion, never from signups, followers, stars or pipeline
- Hold the "not yet" list: the programs, channels and agents in this repo that the company should not run yet, each with the evidence that would put it back on the table
- Write the playbook and set the hiring trigger: the first sales or marketing hire is made when the motion has repeated and is written down, not when the founder is tired of selling, and the hire is given a document rather than a mandate to invent one
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.
- 23d ago Changed · +15 lines · +29 tokens per session 4d3db3f17122
- 28d ago First seen · 94 lines · 112 tokens per session scan A 38638f875932
Founder-Led GTM Strategist is an agent published in the GitHub repository shalintripathi/saas-marketing-agents (30 stars, last pushed yesterday), licensed MIT. It adds 141 tokens to every session and 5,094 once invoked, about $0.0006 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 2026-10-02.
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.