# Changelog > Write a new LLM Gateway changelog entry. Use when the user says "changelog", "changelog entry", "write a changelog", "add a changelog", "announce this feature", or asks to document a shipped feature for the public changelog. Produces the dated markdown file under apps/ui/src/content/changelog plus a gpt-image-2 prompt for the OpenGraph image. - Skill: `theopenco/changelog-2` (Agent Skill) - Install (CLI): `npx skillmds@latest add theopenco/changelog-2` - Raw SKILL.md: https://api.skillmd.com/api/skills/theopenco/changelog-2/raw - Safety review: pending (external: skill-scanner PASS, skillspector PASS) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - Author: theopenco (https://skillmd.com/u/theopenco) - Updated: 2026-09-22 - Page: https://skillmd.com/skills/theopenco/changelog-2 --- # Changelog Write a public changelog entry for LLM Gateway, in the house style, and hand back a ready-to-run gpt-image-2 prompt for its OpenGraph image. > Paths below assume the [LLM Gateway monorepo](https://github.com/theopenco/llmgateway). Adapt them if your changelog lives elsewhere — the format, voice, and image guidance carry over. ## What you need first Before writing, make sure you understand the feature concretely. If the user only gave a feature name, find the facts — don't guess: - Read the relevant docs page under `apps/docs/content/` (e.g. `features/.mdx`). - Inspect the shipping commit/PR if one is referenced: `git show --stat`, then read the changed UI/API/gateway files for the exact user-facing behavior. - Confirm plan gating (free vs Pro vs Enterprise), exact field names, error codes, and any limits. The changelog must be accurate — never invent prices, limits, or capabilities. ## Where entries live - Entries: `apps/ui/src/content/changelog/-.md` - Images: `apps/ui/public/changelog/.png` - Schema is enforced by `apps/ui/content-collections.ts` — all frontmatter fields below are required (except `draft`). ## Step 1 — Pick the date, id, and slug - **Date**: today, `YYYY-MM-DD`. Entries sort by date descending, so this puts the entry at the top. - **id**: the next integer after the current highest. Find it with: ```bash grep -h '^id:' apps/ui/src/content/changelog/*.md | sed 's/[^0-9]//g' | sort -n | tail -1 ``` Use that number + 1, as a string. - **slug**: short kebab-case, feature-focused (e.g. `custom-model-catalog`). The slug must match the filename suffix and the `image.src` filename, and becomes the URL `/changelog/`. ## Step 2 — Write the markdown file Frontmatter (YAML), then the body. Entries are plain Markdown — **no MDX/JSX components** (no ``); use bold inline notes instead. ```markdown --- id: "" slug: "" date: "" title: "" summary: "<1–3 sentences: what shipped, the concrete benefit, and the plan if gated. This is the OG description and the listing blurb.>" image: src: "/changelog/<slug>.png" alt: "<Descriptive alt text: the feature and what the image shows>" width: 1536 height: 1024 --- <Opening paragraph: the problem this solves, then the one-line statement of what shipped. Bold the feature name once.> ## <Section header — verb-led or outcome-led> <Body. Prefer a table for field/option references and a fenced code block for an API example.> --- **[<Docs link> →](https://docs.llmgateway.io/...)** | **[<Secondary CTA> →](https://llmgateway.io/...)** ``` ### House style (match existing entries) Read the two or three most recent files in `apps/ui/src/content/changelog/` before writing, and mirror their tone: - **Lead with the problem, then the fix.** First paragraph names the pain; the next sentence states what shipped. - **Benefits over features, specific over vague.** "about 50% cheaper", "rejected with `400` before any data leaves the gateway" — not "improved efficiency". - **Confident and plain.** Active voice. No exclamation points. No "very/really/simply". No buzzwords ("streamline", "seamless", "revolutionary"). - **Show the API.** Include a realistic `curl` or JSON example when there's a request-level change. Use `https://api.llmgateway.io/v1/...` and `$LLM_GATEWAY_API_KEY`. - **Use a table** for fields, options, strategies, or tiers. - **State plan gating explicitly** (e.g. "Available on the **Enterprise plan**"). - **Close with a footer link line**: a docs link and one secondary CTA, separated by `|`, each as `**[Label →](url)**`. - Keep section headers in `##`. Keep it scannable — short paragraphs, bullets for lists of behaviors. ## Step 3 — Produce the OpenGraph image prompt Hand the user a single, ready-to-paste **gpt-image-2** prompt that produces the OG image, plus where to save it. **Resolution.** Target **1536×1024** (3:2 landscape). This is the recommended OpenGraph size for gpt-image-2: the dimensions are divisible by 16 (a gpt-image-2 requirement) and crop cleanly to the ~1.91:1 social card. Match the `width`/`height` in the frontmatter to whatever you generate. (Square `1024×1024` is acceptable for icon-style art but crops more on social cards — prefer landscape for OG.) **Prompt guidance.** Write a _small summary_ prompt — 2–4 sentences — that: - Describes a clean, modern, abstract tech illustration that conveys the feature's concept (e.g. a catalog/ledger of model cards with price tags and guard rails for the model catalog). Concept over literalism. - States the LLM Gateway brand feel: minimal, premium, soft gradients, subtle depth, plenty of negative space, suitable as a backdrop behind a title. - **Says "no text, no words, no letters, no UI chrome"** — AI image text is unreliable; the title lives in the page, not the image. - Specifies the aspect: "wide 3:2 landscape composition, 1536×1024". Output the prompt in a fenced block, then the save path, e.g.: ```` Prompt for gpt-image-2 (1536×1024): ``` A clean, modern abstract illustration of <concept>, in the LLM Gateway brand style: minimal and premium, soft gradients, subtle depth and glow, generous negative space, balanced as a backdrop behind a headline. Wide 3:2 landscape composition, 1536×1024. No text, no words, no letters, no UI chrome. ``` Save the result to: apps/ui/public/changelog/<slug>.png ```` Generate the image with gpt-image-2 (LLM Gateway playground, the Images API, or any gpt-image-2 client), then drop the PNG at that path. The entry references it via `image.src`; until the file exists the entry builds fine but the image 404s. ## Step 4 — Validate ```bash pnpm format turbo run build --filter=ui ``` `pnpm format` normalizes the markdown; the `ui` build fails if the frontmatter doesn't match the content-collections schema. Then commit (conventional commit, ≤50-char title), e.g. `docs(changelog): add custom model catalog entry`.