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.
npx skills add rajitsaha/100xprism --skill product-marketing-contextgit clone --depth 1 https://github.com/rajitsaha/100xprismWrote 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/skills/rajitsaha/100xprism/product-marketing-context)<a href="https://agentmods.dev/skills/rajitsaha/100xprism/product-marketing-context"><img src="https://agentmods.dev/badge/skills/rajitsaha/100xprism/product-marketing-context/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/skills/rajitsaha/100xprism/product-marketing-context"><img src="https://agentmods.dev/badge/skills/rajitsaha/100xprism/product-marketing-context.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00072 | $0.01509 |
| Opus 5 | $0.00036 | $0.00754 |
| Sonnet 5 | $0.00014 | $0.00302 |
| Haiku 4.5 | $0.00007 | $0.00151 |
Grade A, and why
product-marketing-context 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 — 192 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product Marketing Context
Create and maintain .agents/product-marketing-context.md — the foundational positioning/messaging document all other marketing skills read, so users don't repeat themselves.
Workflow
Step 1: Check for Existing Context
Check .agents/product-marketing-context.md; also .claude/product-marketing-context.md (older setups) — if found only there, offer to move it to .agents/.
Exists: read it, summarize what's captured, ask which sections to update, gather info only for those.
Doesn't exist — offer two options:
- Auto-draft from codebase (recommended, faster): study the repo — README, landing pages, marketing copy, package.json, etc. — and draft a V1 for the user to review, correct, and fill gaps.
- Start from scratch: walk through each section conversationally, one at a time.
Most users prefer option 1. After presenting the draft, ask: "What needs correcting? What's missing?"
Step 2: Gather Information
Auto-drafting: read the codebase (README, landing pages, marketing copy, about pages, meta descriptions, package.json, existing docs), draft all sections, present, ask what needs correcting or is missing, iterate until satisfied.
From scratch: one section at a time — don't dump all questions at once. Per section: briefly explain what you're capturing, ask, confirm accuracy, move on.
Push for verbatim customer language — exact phrases reflect how customers actually think and speak, making copy more resonant.
Sections to Capture
1. Product Overview
One-liner; what it does (2-3 sentences); category (the "shelf"—how customers search for you); type (SaaS, marketplace, e-commerce, service, etc.); business model and pricing.
2. Target Audience
Target company type (industry, size, stage); decision-makers (roles, departments); primary use case (main problem solved); jobs to be done (2-3 things customers "hire" you for); specific use cases/scenarios.
3. Personas (B2B only)
If multiple stakeholders buy, capture for each — User, Champion, Decision Maker, Financial Buyer, Technical Influencer — what they care about, their challenge, the value you promise.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 192 lines · 72 tokens per session scan A 0554c84347c2
product-marketing-context is a skill published in the GitHub repository rajitsaha/100xprism (10 stars, last pushed 12d ago), licensed MIT. It adds 72 tokens to every session and 1,509 once invoked, about $0.0004 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.
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