# Process Links > Process all queued links from the web capture queue into Obsidian notes. Use when the user wants to process their captured links. Use when this capability is needed. - Skill: `tomevault-io/process-links` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/process-links` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/process-links/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/process-links --- # process-links Process all queued links from the web capture queue. ## Usage ``` /process-links /process-links --limit 5 /process-links --topic ai-ml ``` ## Options - `--limit N` - Process only the first N links - `--topic TOPIC` - Only process links that would go to this topic - `--dry-run` - Show what would be processed without doing it ## Instructions When the user invokes `/process-links`, follow these steps: ### Step 0: Load Configuration Read `config.json` from the engram project root to get the vault path: ```json { "vault_path": "~/Documents/Obsidian/WebCapture" } ``` Use the `vault_path` value as `{VAULT_PATH}` in all paths below. Expand `~` to the user's home directory. ### Step 1: Read Queue and Vault Context Read both files: - `data/queue.json` - `{VAULT_PATH}/_system/index.json` (for connection discovery) ### Step 2: Filter Links and Deduplicate - Only process links with `status: "pending"` - **Deduplicate against vault**: For each pending link, check if its URL (normalized: strip trailing slash, fragment, tracking params like utm_*, ref, fbclid) already exists in `index.json` notes. If a match is found, mark the queue item as `status: "processed"` with `note_path` pointing to the existing note and `skipped_reason: "duplicate"`, then skip it. Report skipped duplicates in the summary. - Apply `--limit` if specified - Apply `--topic` filter after determining topic (if specified) ### Step 3: Process Each Link For each pending link: 1. Report: "Processing: {title} ({url})" 2. Use the same logic as `/capture`: - Fetch content with WebFetch - Determine type and topic - Generate summary, key points, and **enriched tags** (6-12 tags, analyzing content beyond user-provided tags) - **Find related notes** - search index for notes sharing 2+ tags, same topic, or overlapping themes. Select top 3. - **Add bidirectional wiki-links** - in the new note's `## Connections` section, add wiki-links with prose context. Read each related note file and append a backlink. - Create note file with `## Connections` section - Update index (including `related` array on new note AND on related notes' entries) - Update topic page `## Notes` section 3. If `user_context` is present in the queue item, use it to guide summarization **Intent detection** (per-link): - If queue item has `share_twitter: true`, add tag `share-twitter` and set `share_intent: "twitter"` on the index entry - If queue item has `deep_learn: true`, add tag `deep-learn` and set `deep_learn: true` on the index entry - **Auto-detection fallback**: If `user_context` contains phrases like "post on X", "post on twitter", "share on twitter", "postable on X", "tweet this", "share this", set `share_intent: "twitter"`. If it contains "learn", "study", "deep dive", "important", "reread", "want to learn", "understand this", set `deep_learn: true` 4. After successful processing: - Update the queue item's status to "processed" - Add `processed_at` timestamp - Add `note_path` with the created note path 5. If processing fails: - Update status to "failed" - Add `error` field with reason - Continue to next link ### Step 4: Save Updated Queue Write the updated queue back to `data/queue.json` ### Step 5: Regenerate Views After all links are processed (not per-link), regenerate the 4 view files once from `index.json` data: 1. **`views/by-date.md`** - List all notes sorted by capture date (newest first). Group by date. Each entry: `- [{type}] [[{note_path}|{title}]] - {summary snippet}` 2. **`views/by-type.md`** - Group notes by content type (article, video, x_post, photo, tool, research, quick). Under each heading, list notes sorted by date. 3. **`views/unread.md`** - List only notes where `read: false`, sorted by date. Each entry includes title, type, topic, and capture date. 4. **`views/favorites.md`** - List only notes where `favorite: true`, sorted by date. 5. **`views/twitter-queue.md`** - Notes with `share_intent: "twitter"` and `twitter_posted != true`. Each entry: title with source URL link, 1-2 sentence summary, suggested tweet angle based on key_points/user_context, tags for hashtag inspiration. Header shows count. 6. **`views/learnings.md`** - Notes with `deep_learn: true`, grouped by topic. Each topic group shows: topic name with note count, each note with title/summary/connections to other learning resources. Footer suggests reading order. Read `{VAULT_PATH}/_system/index.json`, filter/sort the `notes` array, and write each view file. Use Obsidian wiki-links (`[[path|title]]`). ### Step 5b: Git Sync Vault After all links are processed and views regenerated, push vault changes to git: ```bash cd {VAULT_PATH} git add -A git commit -m "vault: processed N links (YYYY-MM-DD)" git push origin main ``` If the vault is not a git repo yet, skip this step silently. ### Step 6: Report Summary Tell the user: ``` Processed X links: - [title1] -> content/topic/note.md (connected to: note-a, note-b) - [title2] -> content/topic/note.md (connected to: note-c) Failed: Y links - [title3]: error reason Remaining in queue: Z links ``` ## Dry Run Mode If `--dry-run` is specified: 1. Fetch and analyze each link 2. Show what would be created (type, topic, enriched tags, likely connections) 3. Don't create files or update queue 4. Report the plan ## Error Handling - If queue file doesn't exist, create it with empty array - If a link fails, log the error and continue with remaining links - Report all failures at the end ## Notes - Queue file: `data/queue.json` - Vault: `{VAULT_PATH}/` - Use the capture skill logic for each link, including connection discovery - Always read the vault CLAUDE.md at `{VAULT_PATH}/CLAUDE.md` for vault conventions --- > Converted and distributed by [TomeVault](https://tomevault.io/claim/tomashrdlicka) — claim your Tome and manage your conversions.