AgentFrame: Marketing

A full-stack marketing workspace inside your AI coding agent. File-native. Built for solo operators. Evolves with your workflow. Two AGENTS.md modes carry the work — CMO ships campaigns, Builder evolves the system. Plan a campaign and publish your first post in an hour, without leaving your IDE.

agentframe-trailer-v0.1.mp4

Jump to: Quick start · Why · Walkthrough · Architecture · Roadmap

Table of contents

• Quick start
• Why this exists
• A real campaign, step by step
• At a glance
• Six architectural principles
• Recommended connectors
• Architecture
• Repository structure
• Customizability
• Preview server
• Auditability and state
• Roadmap
• Status
• Contributing
• References and lineage
• License
• Contact

Quick start

1. Clone the repo:

   git clone https://github.com/situhacks/agentframe-marketing.git
   cd agentframe-marketing

2. Open the folder in your coding agent — Claude Code, Codex, Cursor, VS Code, Antigravity, anything that respects AGENTS.md.

3. Setup. Copy .env.example to .env and drop in optional connector keys for Gemini and Composio (both have generous free tiers and are optional — the system still runs without them, you just lose Deep Research and direct publishing). If you plan to use Open Design locally, run corepack pnpm install inside system/skills/open-design/source/.

4. Start your first campaign. Tell the agent "Start a new campaign" and run it end-to-end.

Mode swaps

AgentFrame ships with two AGENTS.md modes. You swap depending on what you're doing:

• Swap to CMO when you're running a campaign — drafting copy, generating images, publishing, doing a retro. CMO is scoped to workspace/campaigns/ so it can't accidentally edit your templates or processes mid-campaign.
• Swap to Builder when you're improving the system itself — editing a template, adding a process, swapping a skill, applying retro patches. Builder is scoped to system/ and library/.

You don't run shell commands by hand. Just tell the agent swap to Builder or swap to CMO. It handles the file swap and logs the transition to the audit DB.

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Why this exists

I used to run my marketing campaigns out of Claude Chat. For a while I tried doing it all in chat sessions: write the post here, paste the voice rules there, ask for a rewrite, lose the thread, start over tomorrow. It works for something small, but for multi-post campaigns, things get lost and context starts to degrade. The voice rules I'd "saved" were forgotten by next session. State lived in scrollback. I spent more time retyping my instructions than I wanted.

I looked around for alternatives. What I found was prompt wrappers sitting on top of the same models I'm already paying for, and marketing repos with horrible token efficiency — one of them burned through my whole session before the first post was even done.

I didn't like what I saw. So I built my ideal system myself.

AgentFrame Marketing is a file-native marketing workspace that sits inside the coding agent I already use. Two AGENTS.md modes carry the work — CMO ships campaigns, Builder evolves the system. Campaign state lives in markdown files under workspace/campaigns/. Voice rules, templates, and processes live in library/. Skills and connectors are swappable; when something sharper ships, I replace the skill and the system keeps working. See the walkthrough below for what an end-to-end campaign actually looks like.

I've been dogfooding AgentFrame for a while and it's gone through multiple major revisions. The repo evolves with my workflow, not on a release schedule. It's free to fork — take what's useful.

Stands on the shoulders of:

• Composio — all-in-one MCP hub. One connection exposes 100+ workplace and publishing tools (Gmail, Calendar, Drive, LinkedIn, X, Instagram, TikTok, etc.) instead of installing a separate MCP server for each.
• Gemini Deep Research — detailed research artifacts at campaign start. Runs through the Gemini API so it doesn't burn coding-agent session credits.
• Gemini image generation (Nano Banana 2 / Pro) — raster image generation, fast variants and high-fidelity hero visuals.
• nexu-io/open-design — local-first runtime for images, decks, and template-style visual work. AgentFrame stages the handoff by setting up the project, first prompt and design language; OD owns the generation UI and exports.
• heygen-com/hyperframes — HTML-to-video composition for motion deliverables.
• blader/humanizer — copy humanization pass before lock.

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A real campaign, step by step

A solo-flow walkthrough using the example campaign at workspace/campaigns/example-ai-automation-pov/. One operator, six moves, no team handoffs.

01 · CMO kickoff — Tell your coding agent start a new campaign. CMO reads your operator profile, scaffolds the campaign folder, and calls Composio to pull workplace context — recent emails, meeting notes, doc activity — so the campaign starts from what you actually care about that week, not a cold prompt.	02 · Gemini Deep Research — Deep Research runs against your chosen direction and lands a structured artifact at phase-1-research/research-artifact-v{N}.md.
03 · Post copy in your voice — Drafts inherit your locked voice rules from library/context/operator/voice.md, then run through the humanizer skill before lock to strip AI tells. Every revision snapshots into version_history so you can roll back, compare, or read why the copy changed.	04 · Media creation, your pick — Pick the path that fits the deliverable: HTML render in your coding agent for slide-shaped visuals, Gemini Nano Banana 2/Pro for raster image variants, Open Design for higher-fidelity decks and carousels, or HyperFrames for HTML-to-video. For Open Design specifically, AgentFrame stages the project for you — design language, selected mode, and first prompt already loaded. Just open it and press send. (I usually take the OD export into Figma to clean it up. Optional — most people finish inside OD and ship.)
05 · Published via Composio — Composio's connector to LinkedIn (or X, Instagram, TikTok) sends or schedules the post. Live URL and shipped frontmatter land back in the post folder.	06 · Retro — The agent suggests patches to voice rules, templates, processes, and skill behavior based on what actually happened during the run. You approve or reject each one. AgentFrame tracks the small details throughout the campaign so you don't have to remember them.

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At a glance

In the box: 11 deliverable templates, 13 process files, 11 skill bundles, 2 campaign flows, a two-mode persona model, a local preview server, and a two-layer audit trail (activity.md + SQLite DB).

Campaign flows

Add or edit any flow under library/process/campaign-flows/ to match how you actually ship.

Flow	Purpose
solo-flow (default)	Lightweight campaign workflow for one operator moving fast
open-flow	Flexible build-as-you-go workflow where the operator sets the deliverables and tempo interactively
standard-flow	Heavier flow with broader deliverable coverage and more review gates — closer to an enterprise-style campaign

Deliverable templates

Edit, duplicate, or add new deliverable types under library/deliverables/.

Template	Output
business-brief	Business context and objective framing
research-artifact	Research synthesis with sources and implications
messaging-architecture	Core message map and audience framing
design-language	Visual and style direction
campaign-brief	Campaign-level strategy and constraints
post-copy	Platform-ready post copy
carousel-spec	Slide-by-slide carousel plan
video-spec	Video concept, scenes, and production plan
campaign-retro	Campaign-level learnings and improvements
template-retro	Template quality review and updates
system-retro	System-level process and architecture improvements

Process files

Process files load on demand — only when the workflow they describe is in play. They stay out of context until they're needed.

Process	Purpose
campaign-flow-authoring	How to design or evolve campaign flows
process-authoring	How to design or evolve process files
video-production	Video workflow from spec to renders
image-production	Image generation workflow
preview-server	When and how to use the local preview hub
lock-event	Lock-state transitions and quality gates
humanizer-integration	Humanization pass integration
campaign-frontmatter	Frontmatter schema and state handling
browser-fallback	Browser automation fallback strategy
composio-notes	Connector usage notes and caveats
voice-mini-retro	Lightweight voice quality feedback loop
deliverable-versioning	Surgical-vs-replacement rule and version-bump procedure for *-v{N}.md deliverables
research-and-signals	Shared kickoff for campaign research: workspace-context definition, live MCP scan, research-method offer

Skills

My current production stack. Swap any of them for a sharper tool without touching templates or processes.

Skill	Source
agentframe-structure	Project skill
deliverable-scaffolding	Project skill
system-improvement	Project skill
docx	Project skill
pptx	Project skill
humanizer	Vendored from blader/humanizer
hyperframes	Vendored from heygen-com/hyperframes
hyperframes-cli	Vendored from heygen-com/hyperframes
gsap	Vendored animation skill for HyperFrames workflows
open-design	Vendored local-first runtime from nexu-io/open-design for image/deck/template-style visual production, with AgentFrame setup, staging, and lock-time import rules in system/skills/open-design/SKILL.md
browser-harness	Vendored from browser-use/browser-harness for CDP-driven browser workflows; routed through Edge with AgentFrame boundary notes in system/skills/browser-harness/AGENTS.md

Everything else that ships in the box

• Two-mode routing via AGENTS.cmo.md and AGENTS.builder.md
• YAML frontmatter and campaign artifacts under workspace/campaigns/
• activity.md per campaign for human-readable history, plus an append-only SQLite audit DB at system/audit/agentframe.db
• Local preview server at system/server/ for HTML, image, video, PDF, PPTX, and DOCX previews
• Browser harness at system/browser/ using browser-use, with documented fallbacks when a workflow needs a hand-driven Chromium session

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Six architectural principles

P1 — File-native state

Campaign state lives in markdown files: frontmatter, deliverables, activity.md. Not in a chat window. Change models, change machines, come back next week — the campaign picks up where it left off.

P2 — Token efficiency at its core

I designed AgentFrame so context loads only when it's needed, not all at once. AGENTS.md is the only always-on router. Flows, processes, templates, and skills are pulled in on demand based on the task — most of the time you're working with a small, focused context. That means longer sessions before hitting limits, fewer tokens burned per campaign, and less of the "agent forgets what we were doing" drift you get when the whole library is loaded upfront.

P3 — The library is the product

Templates, processes, campaign flows, and personas are the durable layer — they capture how you actually run campaigns and they improve over time. Skills and connectors (Composio, Gemini, Open Design, HyperFrames) are swappable. Replace a skill when something sharper ships; the campaign system is untouched.

P4 — Two modes, one operator

CMO ships campaigns. Builder evolves the system. The split means CMO can't accidentally edit library/ mid-campaign, and Builder can't accidentally touch a locked deliverable mid-refactor.

P5 — Retros patch the system

Every campaign ends with a retro. The agent surfaces specific patches to templates, processes, and skill behavior based on what actually happened, and you approve them. The library evolves campaign by campaign.

P6 — Auditable and traceable

Two layers capture history:

• activity.md per campaign for the human-readable timeline.
• Append-only SQLite audit DB at system/audit/agentframe.db for system events (mode_swap, system_changes, retro outcomes).

Useful when you want to reconstruct what happened, time how long a phase took, or trace why a template changed.

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Recommended connectors

External services AgentFrame integrates with. Recommended for the full loop, but all optional — both Gemini and Composio have generous free tiers, and the system still runs campaigns without any of them. You just lose the automation each connector provides.

Gemini Deep Research

• Deep research artifacts at campaign start — sources, implications, audience signals — saved as structured markdown under phase-1-research/.
• Free credits from Google AI Studio cover solo-operator usage.
• Key: GEMINI_API_KEY.

Gemini image generation (Nano Banana 2 / Pro)

• Fast A/B/C variants for standard illustrations (Nano Banana 2: gemini-3.1-flash-image-preview).
• High-fidelity hero and text-in-image visuals (Nano Banana Pro: gemini-3-pro-image-preview).
• Routed through system/server/lib/image_generate.py; per-post records save as image-prompt-v{N}.md.
• Shares the same GEMINI_API_KEY as Deep Research.

Composio

• All-in-one MCP hub. One connection exposes 100+ tools (Gmail, Calendar, Drive, LinkedIn, X, Instagram, TikTok, etc.) instead of installing a separate MCP server for each.
• Workplace signal collection (email, calendar, docs, notes) feeds campaign research and retros.
• Publishing — schedule or send directly to LinkedIn, X, Instagram, TikTok, and others.
• Analytics pullback to feed performance data into campaign retros.
• Get started at composio.dev.

Open Design

• Bundled local-first visual runtime at system/skills/open-design/source/.
• Used for higher-fidelity images, carousels, decks, and template-style visual work.
• Fresh clones may need runtime dependency setup (corepack, pnpm install, Node 24). Not a separate Open Design product install.
• Uses a local code-agent CLI on PATH (Claude Code, Codex, Gemini CLI, etc.), or BYOK provider keys as a fallback.
• AgentFrame stages the handoff through the OD daemon API: campaign design system, selected OD mode/skill, project creation, and the first unsent prompt.
• Operator flow: open the prepared OD project, press Send, revise or export inside OD, then bring the locked asset back into the campaign.

.env shape

GEMINI_API_KEY=
COMPOSIO_API_KEY=
COMPOSIO_MCP_URL=https://connect.composio.dev/mcp

Your coding agent provides the LLM. These keys power the non-LLM tools (research generation, image generation, publishing).

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Architecture

Mode boundary

                                  ┌─── owns ──▶  workspace/campaigns
                  ┌──── CMO ─────┤
                  │              └─── reads ─▶  system + library
   Operator ──────┤
                  │              ┌─── owns ──▶  system + library
                  └─── Builder ──┤
                                 └─── reads ──▶  workspace/campaigns

   ── swap AGENTS.md to flip between modes ──

Load path for a task

   AGENTS.md
       │
       ▼
   campaign-flow
       │
       ▼
   process file ──────────────┐
       │                      │
       ├──▶ deliverable template
       │         │
       │         ▼
       │     campaign artifact
       │         │
       │         ▼
       │     activity.md
       │
       ├──▶ skill
       │
       └──▶ audit DB

File-memory data flow

                          ┌──▶ artifact frontmatter ──┐
                          │                           │
                          ├──▶ deliverable markdown ──┤
   Operator Input ──▶ Agent                           │
   (CMO or Builder)       ├──▶ activity.md ───────────┤
                          │                           │
                          └──▶ audit writer ──▶ audit DB
                                                      │
                                                      ▼
                                              Retro deliverables
                                                      │
                                                      ▼
                                       Template / process / skill patches
                                              (library evolves)

Architecture summary:

• AGENTS.md is the only always-on router.

• Everything else is loaded on demand to preserve context efficiency.

• Campaign state and outputs live in files; system events are append-only in SQLite.

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Repository structure

agentframe-marketing/
├── AGENTS.md
├── AGENTS.cmo.md
├── AGENTS.builder.md
├── README.md
├── .env.example
├── library/
│   ├── deliverables/
│   ├── process/
│   │   └── campaign-flows/
│   └── context/operator.example/
├── system/
│   ├── skills/
│   ├── server/
│   ├── audit/
│   ├── browser/
│   └── builder-backlog.md
└── workspace/
    └── campaigns/
        └── example-ai-automation-pov/

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Customizability

Everything in the library and skills layer is meant to be edited:

• Add or evolve templates under library/deliverables/
• Add or evolve processes under library/process/
• Swap skill bundles under system/skills/
• Set voice and positioning once in library/context/operator/ (copy from operator.example/ on first run), reuse everywhere

Open Design is a concrete example of the swap pattern. AgentFrame owns campaign state, templates, and the staged handoff. Open Design owns generation, revisions, and exports. Locked OD assets return to the calling deliverable's visuals/imports/ folder.

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Preview server

Show preview server details

• Local preview hub at system/server/
• Previews HTML, images, video, PDF, PPTX, and DOCX
• Folder-tree navigation with hide rules to keep noise down
• Run with py -3 system/server/run.py

Auditability and state

Show auditability details

• Campaign layer: activity.md in each campaign for the human-readable timeline.
• System layer: append-only SQLite audit DB at system/audit/agentframe.db.
• Writer: system/audit/writer.py.
• Useful for reconstructing what happened, timing a phase, or tracing why a template changed.

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Roadmap

• Preview server v2: improved search, nested live reload, stronger video UX

• Additional campaign flows beyond solo/standard (newsletter, short-form video series, podcast launch)

Status

The full loop runs today — kickoff, research, drafting, image/video production, publication, and retro all working end-to-end. I run real campaigns through it.

Contributing

• PRs for templates, processes, and skills are welcome.

• Open an issue first for major architecture changes.

References and lineage

• Composio

• heygen-com/hyperframes

• nexu-io/open-design (Apache-2.0, vendored under system/skills/open-design/source/)

• GreenSock GSAP

• Google AI Studio / Gemini

• blader/humanizer

License

MIT. See LICENSE.

Contact

Built by Brandon Situ over many weekends — and likely many more.

• LinkedIn: linkedin.com/in/brandonsitu
• Email: brandonzsitu@gmail.com

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