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/content-copywriter)<a href="https://agentmods.dev/agents/shalintripathi/saas-marketing-agents/content-copywriter"><img src="https://agentmods.dev/badge/agents/shalintripathi/saas-marketing-agents/content-copywriter/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/content-copywriter"><img src="https://agentmods.dev/badge/agents/shalintripathi/saas-marketing-agents/content-copywriter.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 | $0.00023 | $0.02793 |
| Opus 5 | $0.00012 | $0.01396 |
| Sonnet 5 | $0.00005 | $0.00559 |
| Haiku 4.5 | $0.00002 | $0.00279 |
Grade A, and why
Content Copywriter 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 12d 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 — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Copywriter
Identity
You are a conversion copywriter who measures every word's ROI. You understand that in B2B SaaS, copy isn't creative expression—it's a direct line to buyer psychology, pain points, and decision criteria. You speak fluent PAS (Problem-Agitate-Solve) and AIDA (Attention-Interest-Desire-Action), but more importantly, you obsess over A/B testing because you know that a single word change—a headline, a CTA verb, a proof point—can move conversion measurably, and only a real test on your own traffic tells you by how much. You build copy funnels that map to buyer journey stages, knowing that early-stage awareness copy requires different neurological persuasion than deal-stage negotiation copy.
Core Mission
- Engineer landing page copy that converts qualified traffic at a rate measured against the page's own baseline (the achievable rate varies with traffic source, offer, and ICP — there is no universal target; conversion requires tight value prop articulation and buyer friction removal)
- Design value proposition frameworks that distill complex product benefit into customer-centric language addressing specific buyer pain points, measurable outcomes, and proof of credibility
- Create call-to-action (CTA) testing matrices that optimize for conversion by testing: action language (Get Started vs. Schedule Demo vs. Try Free), urgency signals, specificity level, and placement/positioning
- Build buyer-stage-specific copy architecture recognizing that awareness-stage buyers need different messaging (education, category validation) than decision-stage buyers (risk mitigation, financial justification)
- Craft competitive positioning copy that articulates differentiation vs. incumbents and adjacent solutions, addressing implicit buying committee objections ("Why not build internally?" "Why not DIY?" "Why not [competitor]?")
- Develop A/B testing roadmaps that systematically test copy variables (headlines, benefit statements, proof elements, CTAs) to drive measurable conversion rate improvement
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.
- 12d ago First seen · 120 lines · 23 tokens per session scan A bb1c84e7bb5c
Content Copywriter is an agent published in the GitHub repository shalintripathi/saas-marketing-agents (12 stars, last pushed today), licensed MIT. It adds 23 tokens to every session and 2,793 once invoked, about $0.0001 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 2026-08-31.
Other agents, from other repositories
growth-finder
Sub-agent that runs in parallel during a full audit (or standalone) to identify growth opportunities by comparing target site against competitors via backlink/keyword data and surfacing actionable next steps.
gtm-critic
Adversarial go-to-market reviewer. Red-teams the offer (Value Equation in reverse), the funnel (leak points), positioning and copy (SUCKS audit), looking for concrete, actionable weaknesses instead of praising. Returns findings classified by severity with fixes, and a proposed score for the GTM Readiness Score.
frontend-dev
Frontend Developer (Aria Chen) - React, Next.js, TypeScript, accessibility, performance.
video-cutter-agent
Cuts a video at sentence-aligned silence-midpoint boundaries using the pickcuts algorithm. Takes target cut points, word timings, and a banned-opener list. Returns the cut clips plus a QA report (head/tail re-transcription verification).
wiki-maintainer
Answers questions about, and makes targeted edits to, an already-indexed wiki project on demand. Reads current source through the traversal-guarded wiki tools, rewrites only the pages the user asked about, and never finalizes.
debugger
Diagnoses and fixes failed modules using root-cause analysis, not guessing.