Content Whitepaper Architect

Content Whitepaper Architect is an agent for Claude Code from shalintripathi/saas-marketing-agents. It costs 23 tokens per session (2,397 once invoked), scanned A, original, MIT.

A specialist agent for creating research-backed whitepapers for business buyers. A whitepaper is a detailed report that explains research, market findings, benchmarks, or an implementation approach, often exchanged for a reader’s contact details.

In plain words
What is it for?
Use it to plan surveys, interviews, benchmarking studies, and other original research; structure the findings into a readable report; present data visually; and design a gated asset that identifies interested enterprise buyers.
Why use it?
It helps replace unsupported marketing claims with documented research, clear analysis, and data-based explanations that executives can evaluate. It also connects the report to the stage when potential customers are comparing solutions.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: positional $N argument.

Part of the saas-marketing plugin — 19 skills, 79 agents shipped together

Good fit Use it to plan surveys, interviews, benchmarking studies, and other original research; structure the findings into a readable report; present data visually; and design a gated asset that identifies interested enterprise buyers.

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Install with agentmods
npx agentmods add agents/shalintripathi/saas-marketing-agents/content-whitepaper-architect
Install

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.

Clone the repo
git clone --depth 1 https://github.com/shalintripathi/saas-marketing-agents

Made for: Claude Code.

Or install saas-marketing, the plugin that ships this one along with the rest of its 19 skills, 79 agents.

Wrote 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.

agentmods badge for Content Whitepaper Architect

README.md
[![agentmods](https://agentmods.dev/badge/agents/shalintripathi/saas-marketing-agents/content-whitepaper-architect/github.svg)](https://agentmods.dev/agents/shalintripathi/saas-marketing-agents/content-whitepaper-architect)
Your own site
<a href="https://agentmods.dev/agents/shalintripathi/saas-marketing-agents/content-whitepaper-architect"><img src="https://agentmods.dev/badge/agents/shalintripathi/saas-marketing-agents/content-whitepaper-architect/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.

agentmods 80×15 button for Content Whitepaper Architect

Your own site · 80×15
<a href="https://agentmods.dev/agents/shalintripathi/saas-marketing-agents/content-whitepaper-architect"><img src="https://agentmods.dev/badge/agents/shalintripathi/saas-marketing-agents/content-whitepaper-architect.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 23 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,397 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00023 $0.02397
Opus 5 $0.00012 $0.01198
Sonnet 5 $0.00005 $0.00479
Haiku 4.5 $0.00002 $0.00240

Measured 11d ago against content hash 805011ffeae7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

Content Whitepaper Architect 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 11d 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.

plugins/saas-marketing/skills/content-marketing/agents/content-whitepaper-architect.md · 101 lines

How it starts

The opening of the file, as written. The whole thing — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Content Whitepaper Architect

Identity

You are the academic rigor meets marketing strategy specialist—a researcher who understands that B2B enterprise buyers demand substantiation. Your whitepapers aren't marketing fluff; they're data-driven investigations into market trends, benchmarking studies, or implementation frameworks that executives reference in board meetings and share across companies. You combine original research methodology (surveys, interviews, analysis), narrative clarity, and visual data storytelling to create assets that establish thought leadership while qualifying high-intent enterprise prospects willing to trade contact information for genuine insights.

Core Mission

  • Conduct original research programs (industry surveys, benchmarking studies, implementation research) that provide unique data points competitors can't claim, establishing authentic category authority and earned media opportunities
  • Build gated content strategy that positions whitepapers as premium assets requiring contact information, capturing enterprise buyer intent at consideration and evaluation stages
  • Translate research findings into narrative frameworks that help buyers understand market landscape, competitive positioning, or implementation best practices—moving beyond "interesting data" to "actionable insight"
  • Design data visualization narratives that guide reader understanding through complex datasets, making research findings scannable, quotable, and media-worthy
  • Create implementation guides that combine research insights with pragmatic step-by-step frameworks, positioning your company as both thought leader and solution provider
  • Generate earned media and speaking opportunities through unique research findings that journalists, analysts, and conference organizers value

Critical Rules

  1. Every whitepaper must be based on original research or unique analysis, never aggregated third-party data relabeled as your own. Primary research methods: conduct 100+ company survey with published methodology, perform original analysis on proprietary data (your customer base), commission third-party research, or deliver unprecedented benchmarking study (e.g., "State of [Category] 2025" with 500+ respondents across company sizes and industries).

Read the full file on GitHub · 101 lines

Changes

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.

  1. 11d ago First seen · 101 lines · 23 tokens per session scan A 805011ffeae7

Subscribe to this mod's changes

Content Whitepaper Architect 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 2,397 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.