Most “content curation” advice is basically: share articles you like. That works until you try to do it consistently. Then you run into operational reality:
- you forget what you saved
- you can’t find the link later
- you don’t know what’s worth posting
- you end up reposting headlines because it’s fast
A real curation system behaves like a pipeline: capture → classify → score → draft → review → publish → log. Make.com is useful here because it’s built for routing and scheduling, not just one-time actions. Templates like Social Assistant News Bot Template for Make.com can give you a starting structure—but the value comes from the operating rules.
Define what “good curation” means for your brand
Good curation is not “posting links.” It’s filtering information for a specific audience and adding value. Decide the promise:
- Curate for relevance: “Only items that affect your decisions this month.”
- Curate for education: “Here’s what this means in practice.”
- Curate for speed: “Here are the top 3 things worth reading today.”
Without a promise, your feed becomes random, and random doesn’t build authority.
Step 1: build a capture layer (so links don’t disappear)
Your capture layer should be easy. If it’s not easy, you won’t use it. Common capture channels:
- RSS feeds (industry publishers, your own blog) (Make: RSS app documentation)
- a “save link” form (webhook)
- a Slack/Teams channel where you drop URLs
Webhook capture is useful when you want to force metadata: why you saved it, what audience it’s for, and what angle you think matters (Make: webhooks).
Step 2: normalize and store links with a status model
A curation system needs state. Store each link with:
- URL (normalized)
- source name
- publish date
- topic tags
- audience tag
- status (new → triaged → drafted → approved → posted)
Make’s Data Stores are a practical lightweight database for this (Make: data stores). The point is traceability: you should always know what stage a link is in.
Step 3: score links so you don’t drown in inputs
Scoring turns curation from “infinite reading” into decision-making. A simple scorecard:
- Relevance (0–3): does this affect your audience’s decisions?
- Credibility (0–3): is the source reliable?
- Novelty (0–3): is this new information, not repeated?
- Actionability (0–3): can you give a next step?
Set a threshold (e.g., 8/12) for “draft a caption.” Everything else stays archived for reference.
Step 4: draft captions with templates (so you add value consistently)
Captions should be templates, not improvisation. Three caption templates that work:
Template A: “What happened → what it means”
- 1 sentence: what happened (with source link)
- 1 sentence: why it matters to your audience
- 1 sentence: your recommended action or question
Template B: “Operator takeaway”
- headline: “Operator takeaway:”
- 2–3 bullets with implications
- link to the original
Template C: “Contrarian angle” (use sparingly)
- “Most people will focus on X. The real change is Y.”
- 1 example
- link + attribution
These templates make your posts about your judgment, not about copying someone else’s reporting.
Attribution and rights: the curation system must be safe by design
Two rules keep you out of trouble and build trust:
- Name the source and link to it.
- Don’t recreate the entire article in new words.
Fair use is context-dependent and there’s no universal “safe” word count (U.S. Copyright Office: Fair Use FAQ). The safest posture for most brands is to publish commentary and let the original source do the full reporting.
Step 5: add a review gate before publishing
Review gates prevent two common failures:
- posting misinformation or outdated updates
- publishing low-value captions that sound like scraped headlines
Batch review is easiest: a daily or twice-weekly review window. Make scheduling makes batching straightforward (Make: schedule a scenario).
Step 6: publish on a cadence your audience can tolerate
Curation frequency should match your promise. For most brands:
- Daily digest: 1–3 posts/day
- Weekly roundup: 3–7 posts/week
If you’re curating news as part of a larger content engine, align it with your editorial calendar so posts don’t collide or repeat topics. A simple cadence system like Ukiyo’s Monthly Content Calendar can help keep curation and original content coherent.
Error handling: keep the workflow reliable
In curation pipelines, failures often happen at ingestion (RSS timeouts) or at publishing (API failures). Make supports error handlers to retry, route to manual review, or alert owners (Make: overview of error handling).
Taxonomy: the invisible structure that makes curation scalable
Without a taxonomy, your curated library becomes a pile of URLs. Build a simple tagging system:
- Topic tags: 10–20 stable categories (e.g., “privacy,” “ads,” “creator economy”).
- Audience tags: who this impacts (founders, marketers, operators, etc.).
- Use-case tags: why it matters (risk, opportunity, how-to, update).
Keep tags limited. Too many tags creates inconsistency and makes automation useless.
Handling duplicates and updates (news is not static)
Publishers update stories. Feeds republish. Your system needs rules:
- Duplicate link: suppress and log.
- Same story, new URL: group under a “story ID” if possible.
- Update/correction: if you already posted, decide whether to publish an update or a correction note.
This is why storing URL + publish date + source + your post ID matters. It gives you a trail.
Make.com implementation detail: the “curation record”
A single record in your datastore (or database) should be able to drive the whole workflow. Fields that help in practice:
- url_clean (normalized link)
- headline
- source
- published_at
- tags
- score_total
- summary_internal (your notes)
- caption_draft
- approved_by + approved_at
- posted_url or post ID
Once your record is stable, building new workflows becomes easier because everything maps to the same object.
UTM and tracking: keep measurement simple
If you’re sharing links regularly, add simple tracking parameters to understand what your audience clicks. Do this carefully:
- don’t break URLs with messy parameters
- keep source/medium naming consistent
- store the final “shared URL” in your record
Measurement isn’t about vanity; it’s about learning what your audience values.
What to measure (EEAT for curation)
- Share-to-save ratio: are people saving your curated posts?
- Reply quality: do replies ask follow-ups, or is it empty engagement?
- Source credibility: how often do you need to correct a post?
- Time-to-publish: how long from ingest to approved post?
These metrics help you improve the system, not just post more.
Why review gates matter more than “smart summarization”
AI can draft captions, but it can’t own accuracy. Humans can. A review gate is your trust mechanism: it’s where you verify dates, check the source, and ensure the caption adds value instead of copying. It’s also where you maintain a consistent voice across all curated posts.
Source hygiene: review your feeds like you review vendors
Every quarter, audit your source list:
- Remove sources that repeatedly publish sensational or misleading headlines.
- Add primary sources when possible (official docs, standards, platform announcements).
- Balance viewpoints if the topic is debated, so your curation doesn’t become an echo chamber.
This is an EEAT move. Over time, your audience learns what you consider credible based on what you share.
Daily mode vs weekly mode: pick one based on capacity
If you have limited review capacity, run weekly mode: ingest links all week, score them automatically, and only review the top items on Friday for a scheduled batch. If you’re in a fast-moving industry and your audience expects timely updates, run daily mode: one review window per day, with a hard cap on posts. Either way, capacity should drive cadence—not FOMO.
Closing perspective
A curation system is not a posting trick—it’s an information workflow. When you capture links reliably, score them, draft captions with templates, and require review before publishing, you build a feed that feels intentional and trustworthy. That trust compounds because your audience learns: if you shared it, it matters.
If you want a structured starting point for implementing this in Make, Social Assistant News Bot Template for Make.com is meant to support exactly this workflow: raw links → reviewed captions → published posts with attribution.