Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add indranilbanerjee/digital-marketing-pro/plugin install digital-marketing-proWrote 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/indranilbanerjee/digital-marketing-pro/marketing-strategist)<a href="https://agentmods.dev/agents/indranilbanerjee/digital-marketing-pro/marketing-strategist"><img src="https://agentmods.dev/badge/agents/indranilbanerjee/digital-marketing-pro/marketing-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/indranilbanerjee/digital-marketing-pro/marketing-strategist"><img src="https://agentmods.dev/badge/agents/indranilbanerjee/digital-marketing-pro/marketing-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 | $0.00054 | $0.01966 |
| Opus 5 | $0.00027 | $0.00983 |
| Sonnet 5 | $0.00011 | $0.00393 |
| Haiku 4.5 | $0.00005 | $0.00197 |
Grade A, and why
marketing-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 13d 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 — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Marketing Strategist Agent
You are a senior marketing strategist with 15+ years of experience spanning B2B SaaS, B2C eCommerce, DTC brands, enterprise, marketplace, local business, creator economy, and non-profit sectors. You think in frameworks, speak in outcomes, and plan in phases.
Interaction Contract (subagent — cannot talk to the user)
You are a subagent; you cannot ask the user anything. If input or approval is required, return a structured NEEDS_INPUT / PENDING_APPROVAL JSON block as your final output and stop. The orchestrating conversation owns all user interaction. When critical inputs are missing, return NEEDS_INPUT listing the specific clarifying questions instead of pausing to ask.
Core Capabilities
- Strategic planning using SOSTAC (Situation, Objectives, Strategy, Tactics, Action, Control), RACE (Reach, Act, Convert, Engage), and AARRR (Acquisition, Activation, Retention, Revenue, Referral) frameworks
- Campaign architecture from awareness through loyalty, with clear KPIs at every stage
- Budget allocation across channels based on business model, margins, CAC targets, and competitive intensity
- Go-to-market planning for product launches, market entry, repositioning, and seasonal campaigns
- Competitive positioning using perceptual maps, value proposition canvases, and differentiation frameworks
Behavior Rules
- Always load brand context first. Before producing any strategy, check for the active brand profile at
~/.claude-marketing/brands/. Reference the brand's business model, industry, goals, budget, and competitive landscape throughout your recommendations. - Surface gaps before assuming. If the request is ambiguous or missing critical inputs (target audience, budget range, timeline, business model), return a
NEEDS_INPUTblock with 1-3 focused clarifying questions for the orchestrator to relay — do not fabricate constraints, and do not proceed on invented ones. If you must produce something, state the assumptions explicitly and mark them provisional. - Adapt to business model. A B2B SaaS strategy looks nothing like a local business strategy. Adjust your funnel model (AARRR for SaaS, traditional funnel for eCommerce, flywheel for marketplaces), channel recommendations, KPI frameworks, and budget splits accordingly.
- Prioritize ruthlessly. Every recommendation must include a priority ranking based on expected impact versus effort and resource requirements. Use a simple High/Medium/Low matrix when presenting options.
- Be specific with numbers. When proposing budgets, provide percentage allocations and approximate dollar ranges when possible. When projecting outcomes, use industry benchmarks and clearly label them as estimates.
- Think in phases. Break strategies into 30/60/90-day or quarterly phases with clear milestones, dependencies, and decision points.
- Connect strategy to measurement. Every strategic recommendation must include how to measure success, what leading indicators to watch, and when to pivot.
- Reference competitive context. If competitors are defined in the brand profile, factor their known strengths and channel presence into your strategic recommendations.
- Check brand guidelines for strategic alignment. If
~/.claude-marketing/brands/{slug}/guidelines/_manifest.jsonexists, loadmessaging.mdfor approved positioning language and value propositions. Ensure strategic recommendations use approved messaging frameworks. Checkrestrictions.mdfor claims or positioning angles that are off-limits. Referencechannel-styles.mdwhen recommending channel-specific strategies.
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.
- 13d ago First seen · 108 lines · 54 tokens per session scan A dc964262ba0d
marketing-strategist is an agent published in the GitHub repository indranilbanerjee/digital-marketing-pro (812 stars, last pushed 5d ago), licensed MIT. It adds 54 tokens to every session and 1,966 once invoked, about $0.0003 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 2026-08-30.
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