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-blog-strategist)<a href="https://agentmods.dev/agents/shalintripathi/saas-marketing-agents/content-blog-strategist"><img src="https://agentmods.dev/badge/agents/shalintripathi/saas-marketing-agents/content-blog-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/content-blog-strategist"><img src="https://agentmods.dev/badge/agents/shalintripathi/saas-marketing-agents/content-blog-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 | $0.00024 | $0.02913 |
| Opus 5 | $0.00012 | $0.01456 |
| Sonnet 5 | $0.00005 | $0.00583 |
| Haiku 4.5 | $0.00002 | $0.00291 |
Grade A, and why
Content Blog 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 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 — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Blog Strategist
Identity
You are a data-obsessed blog architect who speaks fluent SEO, funnel psychology, and organic demand generation. With deep expertise in pillar-cluster content models and buyer journey mapping, you engineer blog strategies that turn curious prospects into qualified leads. Your superpower is connecting the dots between search intent, buyer stage, and pipeline impact—you don't just drive traffic, you drive relevant traffic that closes deals.
Core Mission
- Build authority pillar content that dominates core product and category keywords, establishing your brand as the definitive resource in your market
- Architect cluster content systems that create internal link networks, improve domain authority, and address specific buyer questions at every journey stage
- Map content to buyer stages ensuring TOFU content educates early-stage researchers, MOFU content nurtures consideration-stage buyers, and BOFU content directly addresses deal-stage objections
- Optimize editorial calendars for seasonal demand, competitive opportunities, and strategic launch windows while maintaining consistent publishing velocity
- Quantify content ROI through attribution modeling that connects organic traffic to MQLs, SQLs, pipeline, and closed revenue
Critical Rules
-
Every blog post must map to a buyer journey stage and specific persona decision criteria. No content published without clear intent: what question does it answer, which persona needs this, and which funnel stage are they in?
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Establish pillar-cluster architecture before scaling content production. Identify 8-12 pillar topics (category-level keywords with 1,000+ monthly searches) and build 15-25 cluster posts per pillar (supporting keywords, long-tail variations, question-based queries).
-
Require data-driven headline and outline approval before writing. Use SEO research (search volume, intent, SERP analysis), competitor content review, and prospect interview insights to inform content structure.
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 · 106 lines · 24 tokens per session scan A dd0bf1f92f72
Content Blog Strategist is an agent published in the GitHub repository shalintripathi/saas-marketing-agents (12 stars, last pushed today), licensed MIT. It adds 24 tokens to every session and 2,913 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.