Social Content OS

An operating system for turning scattered notes, shipping updates, and product opinions into a coherent publishing system across X and LinkedIn.

Positioning

Primary: an engineer building internet products and agent systems, with strong taste in frontend, interfaces, experimentation, and product framing. Secondary: someone who bridges code, demos, distribution, and market understanding. Source: social-content-os/references/profile-spec.md

The feed should make smart people conclude: this person builds, has taste, and can reason from systems to product to go-to-market.

Non-Negotiables

1. Every idea maps to: claim, proof, implication, reply target.
2. Prefer artifact-backed content: screenshots, code, diagrams, benchmarks, launch notes.
3. Technical and product depth first. Personal texture supports the work, not replaces it.
4. Non-public metrics, customer names, roadmaps, and private conversations are off-limits unless explicitly marked public.
5. Prefer recurring series over disconnected one-offs.

Content Mix (per 10 posts)

Four Content Pillars

Build in Public -- prove craft. Dev diaries, custom renderers, design systems, landing page redesigns, frontend patterns. Desired reaction: "this person ships ambitious technical work."

Field Notes -- prove applied relevance. SEO/GEO, agent demos, event learnings, observability, growth loops. Desired reaction: "this person is close to real product usage."

Product and Market Diagnosis -- prove thinking range. Imagination gap, PMF movement, crowded-market strategy, protocol discourse, conversion. Desired reaction: "this person has an original point of view."

Human Context -- sparingly. Hackathon summaries, founder conversations, travel moments with real story. Desired reaction: "this person is in motion."

Series Architecture

Recurring series create recognition: Dev Diary (browser runtime, rendering, isometric systems), Design System (behavior vs aesthetic control), Field Notes from Dedalus (launches, demos, events), Sharp Takes (short contrarian claims that create conversation).

Skill Graph Architecture

The DeRonin content-production artifact is useful as architecture evidence for this page: a content system should be a graph of reusable instructions, not a single "write posts" prompt. The reviewed image shows a central content-production engine connected to platform adapters (X/Twitter, LinkedIn, Instagram, TikTok), voice and hook nodes, audience profiles, and workflow nodes such as batching, repurposing, cross-platform promotion, cadence, peak posting times, A/B testing hooks, algorithm behavior, thread structure, character limits, and platform formats. Source: X/@DeRonin_, 2026-03-14; Source: local image artifact review, 2026-07-03

For Kevin's system, this maps to explicit source files: content pillars, channel roles, hook formulas, reusable post shapes, confidentiality rules, audience definitions, and automation outputs. The graph is allowed to be visualized in Obsidian or any markdown folder, but the durable unit is the reviewed instruction node. Agents should compose from the graph and record what changed, not invent a new content strategy on every draft.

Agentic No-Slop Workflow

The EXM7777 marketing-agent artifact adds the execution gate for agent-written marketing. It is not enough to have a better prompt; the agent must pass through a loop: read markdown context files for brand, product, ICP, and offer; refresh current research from socials, recent blogs, YouTube, and /last30days; propose a method; get two-model or two-pass review; validate taste and proof against experts, the Obsidian KB, and Kevin's own work that performed; then ship and loop results back into research. Source: X/@EXM7777 and local image artifact review, 2026-07-04

This belongs to Frontend and Design Skills as a pre-draft gate and to The Eval Loop (Slop Is an Output Problem) as the output-quality check. Loopy owns the loop shape when the workflow needs to become a repeatable automation. The operating rule is simple: no context corpus, no fresh research, no independent review, no campaign output.

Capture Schema

For each candidate idea: working title, pillar, one-sentence claim, specific proof, why it matters now, best platform/format, artifact to attach, confidentiality check. If claim, proof, or "why it matters" is missing, the post is not ready.

Publishing Workflow

1. Capture -- within 24 hours of the raw moment
2. Score -- 0-3 on novelty, proof density, audience relevance, conversation potential. Prioritize total >= 8.
3. Draft -- one claim, one proof block, one implication, one clean close
4. Publish -- X: 4-6/week + 3-5 meaningful replies/day. LinkedIn: 1-2/week. Reddit: 2-3/week project showcases + 5-10 community comments. One series post every week.
5. Recycle -- expand strong X posts to LinkedIn reflections and vice versa

Quality Gate

1. Could only you post this exact thing?
2. Is there a concrete proof element?
3. Does it teach, reveal, or frame something?
4. Is the first line strong enough without baiting?
5. Is the close inviting without begging?
6. Does it reinforce the target reputation?

If a draft fails checks 1 or 2, kill it or rewrite it.

Channel Roles

X: speed, sharp takes, build fragments, event reactions, technical snapshots. Should feel alive and slightly experimental. LinkedIn: credibility, narrative posts, milestone reflections, market synthesis. Should feel sharper, calmer, more legible to operators. Reddit: project-specific showcases and technical breakdowns in niche communities. Should feel authentic and community-native - participate before promoting. Each project maps to specific subreddits (see Frontend and Design Skills Reddit Distribution section). Screenshots/GIFs mandatory. Follow 90/10 rule (90% community engagement, 10% your own posts).

Content Repurposing (Upstream)

From the social-content skill (coreyhaines31/marketingskills, 40K weekly installs). Extract "content atoms" from long-form content - self-contained moments that work standalone:

Per long-form piece, aim for: 3-5 short clips, 1-2 LinkedIn posts, 1 X thread, 1 carousel.

Engagement Routine (30 min/day)

1. Respond to all comments on your posts (5 min)
2. Comment on 5-10 posts from target accounts (15 min)
3. Share/repost with added insight (5 min)
4. Send 2-3 DMs to new connections (5 min)

Quality comments: add new insight, share related experience, ask thoughtful follow-up. Never "Great post!"

Hook Formulas

Curiosity: "I was wrong about [belief]." / "[Result] - and it only took [time]." Story: "Last week, [unexpected thing] happened." / "3 years ago, I [past]. Today, [present]." Value: "How to [outcome] (without [pain]):" / "Stop [mistake]. Do this instead:" Contrarian: "[Common advice] is wrong. Here's why:"

Analytics

If engagement drops: test new hooks, post at different times, try different formats, increase engagement with others. If reach drops: avoid external links in post body, increase frequency, engage more in comments, test video/visual.

Automation Integration

The Content Pipeline Workflow automation runs daily to feed this system:

1. Reads Kevin's LinkedIn and X/Twitter activity
2. Analyzes engagement patterns and content mix gaps
3. Generates 5-7 specific post recommendations with hooks
4. Cross-references with Career Profile for recruiter visibility
5. Identifies reply targets and repurposing opportunities

The Recruiter Discovery Workflow automation runs weekly and feeds connection targets that double as engagement opportunities for content visibility.

Upstream Skills

• social-content (~/.cursor/skills/social-content/SKILL.md) - general social media strategy
• copywriting (~/.cursor/skills/copywriting/SKILL.md) - conversion copy for pages. See Security and Review Skills.
• content-strategy (~/.cursor/skills/content-strategy/SKILL.md) - Kevin's positioning arc and quality gates
• career-ops (~/.cursor/skills/career-ops/SKILL.md) - job search pipeline. See Writing and Content Skills.

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Timeline

• 2026-07-04 | Added the agentic marketing no-slop artifact as the execution gate for AI-written marketing: context files, current research, method proposal, independent review, taste/proof library, and loopback. Source: X/@EXM7777, 2026-06-28; local artifact review, 2026-07-04
• 2026-07-03 | Added the DeRonin content-production skill graph artifact as architecture evidence: platform adapters, voice/hook nodes, audience profiles, workflow nodes, and metrics belong in separate reusable instructions. Source: X/@DeRonin_, 2026-03-14; local artifact review, 2026-07-03
• 2026-06-17 | Added source trail and normalized the related link to the canonical Security and Review Skills skill page after folding the duplicate tool page. Source: social-content-os/SKILL.md; Social Draft
• 2026-04-06 | Created content operating-system page from social-content skill references. Source: social-content-os/SKILL.md; social-content-os/references/profile-spec.md; social-content-os/references/content-backlog.md