Carlos Arias
2c969c0753
Adopt the agents/ architecture proven on medellin.co (reference impl): - Move the content engine to a top-level agents/ dir: orchestrators, prompts, config, run.sh, admin console, shared libs. All content-pipeline literals repointed (config paths, scripts, admin, LLM-facing prompts/image.md string, configure.mjs, new-site.sh, astroagent tokenFile, .gitignore runtime block). - Every script carries a parseable @agent-manifest header: name, title, class (content|operational|runtime|plumbing), trigger, model, prompts, skills (MCP), tools, reads/writes tables. 5 content agents + 3 plumbing scripts. - New agents/catalog.mjs generates the catalog from the headers: agents/AGENTS.md (human, grouped by class) + agents/agents.json (machine manifest — a clone diffs it against a source to find missing tools/tables/MCP before running). configure.mjs regenerates the catalog on every identity stamp. No DB table, no watcher. - config.json gains paths.stateDir/newsDir; publish-tick, write-daily, and news-radar read them instead of hardcoding. - Full cut: content-pipeline/ deleted (the seed has no live crons, so no hybrid period needed). Docs updated (AGENTS.md structure + pipeline section, README paths). Clones migrating from content-pipeline/: see medellin.co's .memory/handoffs/agents-directory-migration.md for the cutover playbook (one cron set active at a time; migrate drafts/state after repointing cron). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01FMQeUnUrAeexcZ7P2Hxa6G
37 lines
2.1 KiB
Markdown
37 lines
2.1 KiB
Markdown
# Cover image generation (Higgsfield MCP)
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The cover is an **illustrative editorial image** — appetizing and on-topic, but never
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implying a real photograph of a specific named restaurant, dish-as-served, or identifiable
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person.
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## Flow (use the Higgsfield claude.ai MCP tools)
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1. **Pick a model:** call `mcp__claude_ai_Higgsfield__models_explore` with
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`action:"recommend"` and a goal like "editorial food/lifestyle photography cover image",
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to get a suitable `model` id and its valid `aspect_ratios`. If that fails, default to the
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`preferredModel` from config (`soul_2`).
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2. **Generate:** call `mcp__claude_ai_Higgsfield__generate_image` with
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`params: { model, prompt, aspect_ratio, count: 1 }`. Use a valid aspect ratio close to
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3:2 landscape. This returns a job id.
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3. **Wait for the result:** call `mcp__claude_ai_Higgsfield__job_status` with
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`{ jobId, sync: true }`; repeat (respecting `poll_after_seconds`) until the job is
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terminal. Read the resulting image URL from `results`.
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4. **Download:** use Bash `curl -fsSL "<image_url>" -o "<draftDir>/cover.jpg"` to save the
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image as `cover.jpg` in the draft directory. Verify the file exists and is non-empty.
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If image generation fails after a reasonable retry, continue without it and record
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`imageGenerated: false` in `sources.json`.
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## Style guardrails (put these in the prompt)
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- Editorial food/lifestyle photography aesthetic, natural light, shallow depth of field.
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- Medellín / Colombian context where relevant (tropical, warm, Paisa setting) but generic.
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- No real logos, no readable signage, no recognizable real people, no text overlays.
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- High detail, web-quality, landscape orientation.
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## Prompt skeleton
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```
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Editorial food photography, {subject relevant to the article topic}, {Medellin/Colombian
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ambience if relevant}, natural window light, shallow depth of field, warm tones, appetizing,
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clean composition, no text, no logos, no people's faces. Photorealistic, high detail.
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```
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Fill `{subject}` from the article topic (e.g. "a vibrant brunch spread on a cafe table",
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"specialty coffee being poured", "a colorful arepa plate"). Keep it generic and illustrative.
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