Researcher

researcher

The single discovery pipeline. Three idea sources, one Notion output. Use this instead of separate /performance-check or /listening skills · they're folded in as modes here.

When to use

Trigger on:

• "Find me content ideas"
• "What's hot on X / LinkedIn"
• "What's working for me"
• "Pull from my user interviews"
• "What are customers saying"
• "Scan the GTM space"
• "Give me ten posts to write next week"
• User explicitly types /researcher
• Your Notion Content DB has ; do

curl -s "https://${UNIPILEDSN}/api/v1/users/${pid}/posts?accountid=${UNIPILEACCOUNTID}&limit=20" \ -H "X-API-KEY: ${UNIPILEAPIKEY}" \ -H "accept: application/json" \ -o /tmp/researcher/li_${pid}.json done

LinkedIn engagement score:

score = reactioncounter + 3commentcounter + 5share_counter

If a seed account in `seed-accounts.md` has profile ID `TBD`, resolve
it on first use:

```bash
curl -s "https://${UNIPILE_DSN}/api/v1/users?account_id=${UNIPILE_ACCOUNT_ID}&keyword=&limit=5" \
  -H "X-API-KEY: ${UNIPILE_API_KEY}"

Pick the right profile, copy the ID into seed-accounts.md (commit), continue.

Performance scan · your own content

Step 1: query the Notion Content DB for your recent Published rows.

Use mcp__claude_ai_Notion__notion-search with:
  data_source_url: collection://
  query: ""
  page_size: 25
  filters: { created_date_range: { start_date: "" } }

Filter to rows where Status = Published and Live URL is non-empty.

Step 2: fetch metrics per Live URL.

For LinkedIn URLs (pattern linkedin.com/posts/...):

# Fetch your own posts (your profile ID is cached)
curl -s "https://${UNIPILE_DSN}/api/v1/users//posts?account_id=${UNIPILE_ACCOUNT_ID}&limit=50" \
  -H "X-API-KEY: ${UNIPILE_API_KEY}" \
  -H "accept: application/json" \
  -o /tmp/researcher/li_self.json

Match each Notion row's Live URL against the response · use the post's reaction_counter, comment_counter, share_counter.

For X URLs (pattern x.com//status/):

# Extract tweet IDs from URLs
TWEET_IDS="1234567890,2345678901,..."  # comma-separated
curl -s --get "https://api.twitter.com/2/tweets" \
  --data-urlencode "ids=${TWEET_IDS}" \
  --data-urlencode "tweet.fields=public_metrics,created_at" \
  -H "Authorization: Bearer ${X_BEARER_TOKEN}"

If your X user ID is not yet cached in seed-accounts.md, the tweet lookup-by-ID still works without it · we just can't filter to your own without the ID. Note as soft-blocker if it limits the run.

Step 3: rank and pick.

Sort by engagement score (X formula above for tweets, LinkedIn formula for LI posts). Top 5 are double-down candidates. Bottom 3 are flop diagnostics (what didn't work · note for avoidance, not for ideation).

Step 4: generate double-down angles.

For each top-5 row:

• Follow-up: a continuation post answering "and then what

happened?" or "the next step after X"

• Deeper dive: pick one bullet from the original and make it the

whole post

• Counter-take: argue the opposite of the original (works if

the original was a popular take · creates contrast)

• Format flip: original was text → carousel; original was post → thread; etc.

Pick whichever fits the source. Multi-angle per row is fine if rich material exists.

Customer scan · HUMAN NOTES DB

Query the user-interview rows.

Use mcp__claude_ai_Notion__notion-search with:
  data_source_url: collection://
  query: ""
  page_size: 25
  filters: { created_date_range: { start_date: "" } }

Filter the response to Category in ("User Interview Meeting", "External Meeting"). Skip Co-Founder Meeting, Dev Notes, Reading List, Application categories · those aren't customer signal.

For each surviving row, fetch the page body via mcp__claude_ai_Notion__notion-fetch with the row ID. The body contains the transcript / notes.

For each interview, extract:

• Pain points: 2-4 bullets describing what's broken in the

customer's world (in their words, not yours)

• Direct quotes: 1-3 quotable lines (verbatim · with attribution

to interview date and customer if not under NDA)

• Recurring themes: themes that show up across multiple

interviews (note which · a theme in 1 interview is anecdote, in 3+ it's signal)

For each recurring theme (3+ occurrences), generate an angle:

• The pain stated as a question you have the answer to
• A framework that resolves the pain
• A contrarian take on common-but-wrong solutions in that space
• A customer-quote post (the verbatim line as the hook)

3. Filter (all modes)

• Drop posts older than the time window
• Drop banned-signal posts (see seed-accounts.md § "Banned signals")
• Drop URL-only / image-only posts with no text body
• Drop posts under the engagement floor (trend mode only · 50 likes

on X · 100 reactions on LinkedIn)

• For customer scan: drop interviews under 5 minutes (likely no-shows

or aborted) and skip the ones marked "private · do not use"

4. Cluster + angle (all modes)

Read all surviving inputs. Group by theme · expect 5-10. For each theme, pick the strongest representative (highest engagement for trends, top performer for performance, most-quoted for customer) and write:

• Angle: a one-sentence hook you could use, in your voice (terse,

contrarian, concrete, direct, no hype)

• Why it's hot / working / real: one sentence on why this matters
• Suggested Pillar: pick one of the six (Building in Public,

Educational / Tactical, Personal, Memes, Promotional, Trend Insights)

• Suggested Format + Channel: usually Text on LinkedIn or X

· sometimes Long-form Article for richer themes · sometimes Lead Magnet for customer-pain frameworks

5. Create Notion rows

For each idea card, call mcp__claude_ai_Notion__notion-create-pages with data source ``. Properties:

• Title: the one-sentence angle (max ~80 chars)
• Status: Idea
• Pillar: suggested multi-select (single value usually)
• Format: suggested
• Channel: suggested

Page body, branched by mode:

Trend mode body

Source: 
Mode: trend
Author: 
Engagement: 
Window: 

— Original post —
> 

— Why this is hot —

— Your angle —

Performance mode body

Source: 
Mode: performance · double-down
Original metrics: 
Pillar of original: 

— Original post —
> 

— Why this performed —

— Double-down angle —

Customer mode body

Source: 
Mode: customer · pain-point
Interview date(s): 
Customer(s): 
Theme recurrence:  interviews

— Customer quote(s) —
> ""
> ""

— The pain —

— Your angle —

6. Report back

One-line summary by mode plus the Notion URLs of created rows. Example:

Created 10 ideas (4 trend, 3 performance double-down, 3 customer-pain).
Pipeline view: 

Trend
  -  → notion.so/...
  -  → notion.so/...
  ...
Performance double-down
  -  (riff on "" · 47 reactions) → notion.so/...
  ...
Customer pain
  -  (3 interviews · A, B, C) → notion.so/...
  ...

If any mode soft-blocked (e.g. X user ID missing), mention it in the report.

Defaults

| Knob | Default | | --------------------------- | ------------------ | | Mode | Hybrid | | Time window (trend) | 7 days | | Time window (performance) | 30 days | | Time window (customer) | 60 days | | Cards to create | 10 | | Trend / performance / customer ratio (hybrid) | 4 / 3 / 3 | | X account scan | 3 cached creators | | LinkedIn account scan | Your profile + curated list as IDs are resolved | | Topic seeds | from seed-accounts.md | | Engagement floor (X trend) | 50 likes | | Engagement floor (LI trend) | 100 reactions | | Customer category filter | User Interview Meeting OR External Meeting |

Don'ts

• Don't paraphrase the original post into your voice as the Title.

The Title is the angle you would write · derived from the post, not copied. The original post text goes in the page body.

• Don't surface 30 ideas. Cap at 10-15 default. More creates

fatigue, not optionality.

• Don't skip the engagement floor on trend mode. Low-engagement

posts on these topics are usually slop, even from good accounts.

• Don't auto-spawn drafts. Status=Idea means just-an-idea.

Drafting is a separate step.

• Don't pollute the DB with duplicates. Before creating, do a

quick search of recent Idea rows for the same theme. If a similar idea exists, append the new source as another bullet in the existing row's body instead of creating a duplicate.

• Don't fabricate engagement numbers. If the API call fails or

returns empty, say so · don't fill in plausible-looking metrics.

• Don't quote customers under NDA verbatim. If the interview

notes mark a section private / off-record, paraphrase it in the pain framing and skip the direct quote. When in doubt, ask.

• Don't crawl outside X + LinkedIn + Notion. This skill stays

scoped. For blog / podcast / YouTube discovery, use WebSearch separately.

• Don't over-double-down on one performance winner. If the same

post drives 5 angles, you'll oversaturate one theme. Cap at 2 double-downs per source row.

See also

• Notion Content DB data source: ``
• Notion HUMAN NOTES DB data source: ``
• Seed accounts + topic list: [seed-accounts.md](./seed-accounts.md)
• API auth env: ./.env · ` (X) · `,

`, ` (LinkedIn)

• Downstream skills: /linkedin-copywriter, /x-copywriter,

/repurpose, /lead-magnet-creator, /long-form, /youtube-script

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: timscheuerai
• Source: timscheuerai/content-vault
• License: MIT

Install and usage instructions live in the source repository linked above.