# Genfeed Connector > Detect Genfeed connectivity and expose the gf CLI for content-loop state, tokens, manifests, stage transitions, and feedback. - Skill: `genfeedai/genfeed-connector` (Agent Skill, multi-file: 9 files) - Install (CLI): `npx skillmds@latest add genfeedai/genfeed-connector` - Raw SKILL.md: https://api.skillmd.com/api/skills/genfeedai/genfeed-connector/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - License: MIT - Author: genfeedai (https://skillmd.com/u/genfeedai) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/genfeedai/genfeed-connector --- # Genfeed Connector You manage shared state and capability detection for the Genfeed content factory. Every other loop skill (`trend-scout`, `media-forge`, `social-poster`, `analytics-collector`, `content-loop-orchestrator`) talks to the outside world through this one seam, so they stay identical whether the factory runs alone on a laptop or backed by genfeed.ai. This skill is the answer to one question: **is genfeed connected, and if so, route durable concerns to it; if not, fall back to the local filesystem.** --- ## Core Principle: Skills Are Stateless Workers; The App Is The Control Plane Loop skills are pure workers — read a job, do work, emit a result, exit. They hold no state, no secrets, and no schedule. Everything durable lives behind this seam: | Concern | standalone backend | connected backend (genfeed.ai) | |---------|--------------------|--------------------------------| | Manifest state | `.genfeed/items/*.json` | genfeed content-items DB | | Scheduling | manual / harness `/loop` | genfeed cron (always-on) | | Platform tokens | env vars only | genfeed vault, short-lived, injected | | Analytics callbacks | manual fetch | genfeed webhook receiver | | Approval gate | ask in chat | genfeed approval UI | The same `gf` commands work in both modes. A skill never knows or cares which backend is live. --- ## Detection Order `gf detect` resolves the mode (first hit wins) and caches it to `.genfeed/ctx.json`: 1. `GENFEED_API_KEY` env set → **api** 2. `genfeed status` CLI exits 0 on PATH → **api** 3. `.genfeed/config.json` names an `apiKeyEnv` whose env var is set → **api** 4. otherwise → **standalone** `ctx.json` never stores a secret value — only the **name** of the env var holding the key. The key itself stays in the environment or the genfeed CLI keychain. This gives the "independent but upgradeable" property: the skills work for anyone with no genfeed account, and light up persistence + always-on scheduling + a managed token vault the moment a key is present. --- ## The Contract: Env Vars + stdin/stdout JSON Loop skills never import this skill's TypeScript. The seam is invoked as a CLI and communicates only through: - **stdin/stdout JSON** for manifest data - **environment variables** for tokens (the connector resolves and exports a token; the worker reads it from env, uses it in memory, and never writes it back) This keeps every skill independently installable — no cross-skill import paths to break. --- ## CLI Reference Run with `bun run gf.ts ` (Bun 1.1+, zero dependencies — uses only Node built-ins and global `fetch`). ```bash bun run gf.ts detect [--mode standalone|api] # resolve + cache runtime context bun run gf.ts create [--thesis "..."] [--stage selected] [--tags a,b] [< trend.json] bun run gf.ts get bun run gf.ts list [--stage ] [--tag ] [--limit ] bun run gf.ts save # full ContentItem JSON on stdin bun run gf.ts transition [--note "..."] bun run gf.ts next # oldest item waiting in bun run gf.ts record-metric # Metric JSON on stdin bun run gf.ts feedback # prior-performance multiplier (loop closure) bun run gf.ts token # resolve a token (env or vault) ``` All commands print JSON to stdout; errors print to stderr and exit non-zero. --- ## The Manifest (ContentItem) One row tracks an item through the whole loop. Stages: ``` trend_candidate -> selected -> briefed -> remixed -> producing -> awaiting_approval -> approved -> scheduled -> posted -> measured -> archived | killed ``` Key fields: `trend` (the originating signal), `thesis` (flagship angle), `brief`, `derivatives[]` (per-platform copy + media refs + postId), `artifacts[]` (generated media), `metrics[]` (performance), `feedbackScore` (0..1, derived from metrics), `tags[]` (pillars + trend terms — how analytics attribute back to trends), and `history[]` (every stage transition). See `lib/schema.ts` for the full type. --- ## Loop Closure `feedback ` averages `feedbackScore` across all `measured` items tagged with that term and returns a 0..1 multiplier. `trend-scout` multiplies a fresh trend's raw score by `(1 + multiplier)`, so themes that performed before rise to the top of the next cycle. That is the `analytic -> repeat` edge of the loop, implemented in data. --- ## Security - Standalone tokens are **read** from the environment and **never written** to any file. - Connected tokens are issued short-lived and scoped by genfeed.ai, used in memory, and never persisted by the connector. - `ctx.json` and `config.json` store only the **name** of the key's env var, never its value. - This skill never calls a content/social/model API itself — it only resolves state and tokens. Outbound API calls live in the worker skills, under their own approval gates. --- ## How Other Skills Use It ```bash # orchestrator picks the next job and hands it to a worker JOB=$(bun run ../genfeed-connector/gf.ts next selected) # worker emits a result; orchestrator advances the stage bun run ../genfeed-connector/gf.ts transition "$ID" remixed --note "atomized to 6 platforms" # poster resolves a token without ever seeing the long-lived credential export X_BEARER_TOKEN="$(bun run ../genfeed-connector/gf.ts token x)" ``` If `gf` is not resolvable as a sibling skill, a worker degrades to its own local `.genfeed/` directory using the same on-disk format.