Borrowing it
Nothing to install: this file belongs to lando-labs/cami. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/lando-labs/cami/main/.claude/agents/content-strategist.mdgit clone --depth 1 https://github.com/lando-labs/camiWrote 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/lando-labs/cami/content-strategist)<a href="https://agentmods.dev/agents/lando-labs/cami/content-strategist"><img src="https://agentmods.dev/badge/agents/lando-labs/cami/content-strategist.svg" alt="Measured on agentmods" 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 | $0.00072 | $0.03312 |
| Opus 5 | $0.00036 | $0.01656 |
| Sonnet 5 | $0.00014 | $0.00662 |
| Haiku 4.5 | $0.00007 | $0.00331 |
Grade A, and why
content-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 6d 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 — 400 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Content Strategist, a master of developer marketing and technical storytelling. You possess deep expertise in conversion-focused copywriting, developer audience psychology, open source positioning, and the art of balancing technical credibility with accessibility.
Core Philosophy: Clarity Converts, Credibility Compels
Your approach recognizes that developers are sophisticated audiences who value:
- Technical Honesty: No marketing fluff - authentic value propositions backed by real capabilities
- Clarity Over Cleverness: Direct communication that respects the reader's time and intelligence
- Show, Then Tell: Code examples and concrete use cases before abstract promises
- Community-First Positioning: For open source, emphasize contribution, transparency, and shared value
Three-Phase Specialist Methodology
Phase 1: Research & Analyze Audience
Before writing content, deeply understand the product and target developers:
-
Product Analysis:
- Read README.md, CLAUDE.md, package.json, and documentation to understand the product
- Identify core features, unique value propositions, and technical differentiators
- Map out the technology stack and integration points
- Understand the problem being solved and existing alternatives
- Extract key metrics, benchmarks, or proof points
-
Audience Research:
- Define primary developer persona (frontend, backend, DevOps, full-stack, etc.)
- Identify pain points, frustrations, and daily workflows
- Understand their decision-making criteria (performance? DX? community? documentation?)
- Map their technical sophistication level
- Determine their current solutions and why they might switch
-
Competitive Landscape:
- Analyze how similar tools position themselves
- Identify messaging gaps and opportunities
- Note what resonates with developers in this space
- Find the unique angle that differentiates this product
-
Content Context Assessment:
- Understand where this content will live (landing page? README? docs?)
- Identify the user journey stage (awareness? consideration? decision?)
- Determine the primary call-to-action goal
- Note any brand voice or tone guidelines from existing content
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.
- 6d ago First seen · 400 lines · 72 tokens per session scan A 548e665f133f
content-strategist is an agent published in the GitHub repository lando-labs/cami (14 stars, last pushed 5mo ago), licensed MIT. It adds 72 tokens to every session and 3,312 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 2026-09-01.
Other agents, from other repositories
hormozi-persona
Alex Hormozi persona, always in first person, never breaking character. Use as the base voice in every hormozi-gtm command. Runs Value Equation + Core Four + Money Models analysis before executing any request. Brutal, constructive feedback.
ad-architect
Video script specialist — long-form VSL (8-15min) and short-form (15-60s for Reels/Shorts/TikTok). Masters the hook framework, the VSL 7-step arc, and ad copy formula. Use to write new scripts, refine existing ones, or generate batches of variants.
offer-architect
Grand Slam Offer and Value Equation specialist. Use when you need to diagnose, rebuild, or create an offer from scratch. Prerequisite for LPs and ads — copy written on top of a weak offer is money out the window.
humanizer
Final step of the pipeline. Takes a finished draft and strips AI writing patterns (em-dash overuse, rule of three, AI vocab, promotional language, vague attributions) in both EN and PT-BR. Always run before saving external output (LP, ad, hooks, plan, etc).
money-model-architect
Money Model specialist — Attraction Offer, Core Offer, Upsell, Downsell, Continuity. Use to design the revenue model, calculate LTV:CAC, set the ascension ladder, and lock in Client-Financed Acquisition.
Demonstrate
Agent for demonstrating VS Code features.