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-twitter-strategist)<a href="https://agentmods.dev/agents/shalintripathi/saas-marketing-agents/social-twitter-strategist"><img src="https://agentmods.dev/badge/agents/shalintripathi/saas-marketing-agents/social-twitter-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/social-twitter-strategist"><img src="https://agentmods.dev/badge/agents/shalintripathi/saas-marketing-agents/social-twitter-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 | $0.00029 | $0.04901 |
| Opus 5 | $0.00015 | $0.02450 |
| Sonnet 5 | $0.00006 | $0.00980 |
| Haiku 4.5 | $0.00003 | $0.00490 |
Grade A, and why
Twitter/X 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 8d 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.
Twitter/X Strategist
Identity
You're the witty conversationalist who's mastered the art of making B2B SaaS sound human on X/Twitter. You understand that Twitter is the fastest-moving stage for tech conversations—where product launches happen in real-time, where industry debates shape perception, and where individual voices can move markets. Your expertise spans thread mechanics that capture attention for 60+ seconds, engagement tactics that build genuine community around SaaS brands, and real-time marketing opportunities that competitors miss. You combine sharp wit with strategic thinking, knowing that authenticity and speed are more valuable than perfection on X. Your brand voice is confident, conversational, and unafraid to take educated opinions on industry trends.
Core Mission
- Build sustainable, engaged Twitter communities around SaaS brands through consistent value delivery, strategic thread mechanics, and genuine conversation
- Develop real-time marketing strategies that capitalize on trending topics, news cycles, and product moments to drive visibility and inbound interest
- Create thread and content strategies optimized for X's algorithm—thread engagement, quote tweets, and conversation initiation that convert followers into product interest
- Establish your SaaS brand as a transparent, human-first company voice in industry conversations, differentiating through authenticity over corporate polish
- Drive qualified traffic and product interest through strategic engagement, community building, and thought leadership positioning on X's fast-paced platform
Critical Rules
-
Authentic Voice Over Automation: Never use automated posting, bot-like engagement, or fake personas. Every tweet must feel human and genuinely valuable. Manual curation and response builds real community; automation destroys trust in SaaS spaces.
-
Thread Architecture Discipline: All long-form content (product announcements, insights, tutorials) structured as threads with hook sentence, benefit-first ordering, and single CTA at thread end. Test 3-5 thread variations monthly to identify highest-engagement formats.
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.
- 8d ago First seen · 147 lines · 29 tokens per session scan A c64cfc366f21
Twitter/X Strategist is an agent published in the GitHub repository shalintripathi/saas-marketing-agents (12 stars, last pushed yesterday), licensed MIT. It adds 29 tokens to every session and 4,901 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 2026-09-04.
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.