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/indranilbanerjee/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/commands/indranilbanerjee/digital-marketing-pro/engagement)<a href="https://agentmods.dev/commands/indranilbanerjee/digital-marketing-pro/engagement"><img src="https://agentmods.dev/badge/commands/indranilbanerjee/digital-marketing-pro/engagement/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/commands/indranilbanerjee/digital-marketing-pro/engagement"><img src="https://agentmods.dev/badge/commands/indranilbanerjee/digital-marketing-pro/engagement.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 | $0.00053 | $0.02434 |
| Opus 5 | $0.00026 | $0.01217 |
| Sonnet 5 | $0.00011 | $0.00487 |
| Haiku 4.5 | $0.00005 | $0.00243 |
Grade A, and why
engagement 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.
How it starts
The opening of the file, as written. The whole thing — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/digital-marketing-pro:engagement — 12-Part Engagement Workflow
The engagement command family runs a complete marketing engagement using the 12-Part methodology. Every brand engagement runs through 12 parts in sequence, producing a canonical set of files at each stage.
This command is the entry point. It invokes the engagement-workflow skill, which delegates to part-specific skills (four-core-documents, client-validation-document, growth-plan, yearly-planner, continuous-improvement-loop).
Subcommands
/digital-marketing-pro:engagement start <brand-slug> <engagement-id>
Initialise a new engagement. Creates the directory tree, writes _engagement.json, walks the user through Part 1 Stone vs Opinion intake.
Example:
/digital-marketing-pro:engagement start acme-corp 2026-q2
Pre-condition: Brand profile must exist at ~/.claude-marketing/brands/{brand-slug}/profile.json. If not, run /digital-marketing-pro:brand-setup first.
Checkpointing & resume: The full checkpoint protocol — open a run on start, save each part as it completes, run /digital-marketing-pro:check --full before the Part 5 and Part 8 deliverables, then publish and finalize at the end — lives in the skill. See engagement-workflow/SKILL.md § Checkpointing & Resume (the single source of truth). Each part's checkpoint saves that part's own deliverable path (Part 3 saves the Four Core Documents, Part 8 saves the Growth Plan — never a placeholder for a different part). An interrupted run resumes with /digital-marketing-pro:resume, and the finished files land in the visible output folder (/digital-marketing-pro:output-folder {brand}).
/digital-marketing-pro:engagement status [brand-slug] [engagement-id]
Show the current engagement status. If brand and id are omitted, shows all active engagements.
Example:
/digital-marketing-pro:engagement status acme-corp 2026-q2
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.
- 11d ago First seen · 178 lines · 53 tokens per session scan A 263af6d418d9
engagement is a command published in the GitHub repository indranilbanerjee/digital-marketing-pro (806 stars, last pushed 3d ago), licensed MIT. It adds 53 tokens to every session and 2,434 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.
Other commands, from other repositories
brand-setup
Configure brand voice, terminology, compliance guardrails, and style guide for content production.
output-folder
Print the absolute path to the user-visible ContentForge output folder and open it in the OS file manager.
create-content
Run the full 10-phase content production pipeline — research, draft, fact-check, humanize, and publish.
audit-content
Audit your content library for freshness decay, coverage gaps, and optimization opportunities.
content-brief
Generate a research-backed content brief with keyword data, competitor analysis, search intent, and SEO strategy.
publish
Publish finished content to Webflow or WordPress with preview, verification, and HTML export fallback.