mo-feed — Tech Intelligence Pipeline for Developers

One skill. Fetch from everywhere. Classify. Display cards. Ingest to memory. Done.

Twitter ──┐
HN ───────┤
GitHub ───┤──→ Classify (P0-P3) ──→ TUI Cards ──→ Knowledge Base Ingest
arXiv ────┤
HF ───────┤
Lobsters ─┘

What It Does

1. FETCH — pulls from 7+ sources in parallel (Twitter timeline, HN, GitHub trending, arXiv, HuggingFace, Lobsters, Reddit)
2. CLASSIFY — sorts every item into P0-P3 priority tiers using keyword matching
3. DISPLAY — renders beautiful TUI cards in terminal, grouped by tier, sorted by engagement
4. TRACK — maintains a reading list with unread/read status (

   ~/.secondmem/reading-list.md

   )
5. INGEST — writes P0 + high-signal P1 items into a markdown knowledge base (

   ~/.secondmem/knowledge/

   )
6. INDEX — updates a chronological timeline for date-based recall (

   ~/.secondmem/timeline.md

   )

When to Use

• "catch me up" / "what's interesting" / "daily digest" / "feed me"
• "what's new in [topic]" / "scan [source]" / "tech scan"
• "fetch and store" / "fetch and ingest" / "mo feed"
• Any request that implies: get content from internet + show it + remember it

Prerequisites

# Required: headless-twitter for Twitter fetching (Chrome CDP, no API keys)
which headless-twitter || npm install -g headless-twitter

# Required: jq for JSON processing
which jq || sudo apt install jq

# Knowledge base directory (auto-created on first run if missing)
mkdir -p ~/.secondmem/knowledge ~/.secondmem/logs

Pipeline — Execute in Order

Phase 1: FETCH

Fetch from multiple sources in parallel. Default: Twitter timeline + top cross-reference sources. If user specifies a topic, add targeted searches.

Default fetch (no topic specified):

# Twitter timeline (primary) — requires headless-twitter + logged-in Chrome
headless-twitter twitter timeline '' 50 --lang en --json

# Cross-reference sources (parallel curl — no auth needed)
curl -s "https://hn.algolia.com/api/v1/search?tags=show_hn&numericFilters=points>30" | jq '.hits[0:10]'
curl -s "https://huggingface.co/api/models?sort=trending&limit=10" | jq '.[] | {modelId, likes, pipeline_tag, lastModified}'
curl -s "https://lobste.rs/hottest.json" | jq '.[0:10]'
curl -s "https://api.github.com/search/repositories?q=stars:>50+created:>$(date -d '3 days ago' +%Y-%m-%d)&sort=stars&per_page=10" | jq '.items[] | {full_name, stargazers_count, language, description}'

Topic-specific fetch (user says "what's new in [topic]"):

"agent framework" OR "agent SDK" OR "MCP" OR "tool-use"

"open source model" OR "fine-tuning" OR "inference" OR "transformer"

"GPU" OR "CUDA" OR "RISC-V" OR "FPGA" OR "NVIDIA"

"database" OR "B-tree" OR "storage engine" OR "PostgreSQL" OR "SQLite"

"distributed" OR "latency" OR "consensus" OR "architecture"

"microVM" OR "eBPF" OR "kubernetes" OR "Docker" OR "CLI tool"

"just shipped" OR "just launched" OR "YC" OR "users"

"React" OR "Next.js" OR "Svelte" OR "CSS" OR "web components"

"CVE" OR "zero-day" OR "vulnerability" OR "exploit" OR "pentest"

"terraform" OR "ansible" OR "CI/CD" OR "deployment" OR "SRE"

Source-specific fetch (user says "scan [source]"):

headless-twitter twitter timeline '' 50 --lang en --json

headless-twitter twitter search "QUERY" 30 --lang en --json

headless-twitter twitter user "@handle" 20 --lang en --json

curl -s "https://hn.algolia.com/api/v1/search?tags=front_page" | jq '.hits[0:15]'

curl -s "https://hn.algolia.com/api/v1/search?tags=show_hn&numericFilters=points>30" | jq '.hits[0:15]'

curl -s "https://api.github.com/search/repositories?q=stars:>50+created:>$(date -d '3 days ago' +%Y-%m-%d)&sort=stars&per_page=15" | jq '.items[]'

curl -s "http://export.arxiv.org/api/query?search_query=cat:cs.AI+OR+cat:cs.LG&sortBy=submittedDate&sortOrder=descending&max_results=10"

curl -s "https://huggingface.co/api/models?sort=trending&limit=10" | jq '.[]'

curl -s "https://lobste.rs/hottest.json" | jq '.[0:15]'

curl -s "https://www.reddit.com/r/programming/hot.json?limit=15" -H "User-Agent: mo-feed/1.0" | jq '.data.children[].data'

curl -s "https://www.reddit.com/r/LocalLLaMA/hot.json?limit=15" -H "User-Agent: mo-feed/1.0" | jq '.data.children[].data'

Phase 2: CLASSIFY

Classify ALL fetched content into priority tiers using keyword matching.

Default Priority Tiers

Customization: Edit the tiers below to match YOUR interests. These defaults are tuned for a full-stack developer interested in AI, systems, and infrastructure. Swap keywords, rename tiers, add new domains — the classifier just does keyword matching against text + author.

Classification Rules

1. Scan text + author for keyword matches
2. Assign highest matching tier (P0 wins over P1)
3. Within each tier, sort by engagement (likes + retweets + points + stars)
4. Remove exact duplicates and RTs of already-shown items
5. Extract links from P0 items as action items

Key Accounts (always surface when they appear)

Customization: Replace with accounts YOU follow that are high-signal for your interests.

# AI / LLM Engineering
@hwchase17 @AnthropicAI @karpathy @swyx @jxnlco @simonw @tom_doerr

# Systems / Infra / Tooling
@rauchg @cramforce @mitchellh @kelseyhightower @ThePrimeagen @antirez

# AI Research / Models
@_lewtun @vllm_project @huggingface @GoogleDeepMind

# Hardware / Science
@elonmusk @dfrobotcn @LensScientific

# Builders
@kepano @DanielleFong @levelsio @zenorocha

Phase 3: DISPLAY — TUI Cards

ALL content rendered as cards. Never plain tables or bullets for content items.

Tweet Card

┌──────────────────────────────────────────────────────────────────────────┐
│ ○ #N  @author                                        [P0] Agentic AI    │
│       ♥ 10.7k   ↺ 723   ◎ 184          Apr 12, 2026 · 3h ago          │
│                                                                          │
│  Tweet text wrapped at ~70 chars, max 4 lines                            │
│  Truncate with … if longer                                               │
│                                                                          │
│  → https://x.com/i/web/status/ID                                        │
└──────────────────────────────────────────────────────────────────────────┘

HN Card

┌──────────────────────────────────────────────────────────────────────────┐
│ ○ #N  source: Hacker News                            [P1] Databases     │
│       ▲ 203 points   💬 54 comments     Apr 11, 2026 · 1d ago          │
│                                                                          │
│  Show HN: Postgres extension for BM25 full-text search                  │
│                                                                          │
│  → https://github.com/timescale/pg_textsearch                            │
└──────────────────────────────────────────────────────────────────────────┘

GitHub Card

┌──────────────────────────────────────────────────────────────────────────┐
│ ○ #N  source: GitHub                                 [P1] Infra         │
│       ⭐ 1.2k stars   🍴 89 forks   lang: Go        Apr 10, 2026 · 2d ago │
│                                                                          │
│  owner/repo — Description text here                                      │
│                                                                          │
│  → https://github.com/owner/repo                                         │
└──────────────────────────────────────────────────────────────────────────┘

arXiv Card

┌──────────────────────────────────────────────────────────────────────────┐
│ ○ #N  source: arXiv                                  [P0] ML Research   │
│       📄 cs.AI                                  published: Apr 11, 2026  │
│                                                                          │
│  Paper Title Here                                                        │
│  Authors: First, Second, Third                                           │
│                                                                          │
│  → https://arxiv.org/abs/2604.12345                                      │
└──────────────────────────────────────────────────────────────────────────┘

HuggingFace Card

┌──────────────────────────────────────────────────────────────────────────┐
│ ○ #N  source: HuggingFace                            [P0] Models        │
│       ❤️ 542 likes   ⬇ 12.4k downloads   task: text-generation         │
│                                                                          │
│  org/model-name — 7B param, Apache 2.0                                  │
│                                                                          │
│  → https://huggingface.co/org/model-name                                 │
└──────────────────────────────────────────────────────────────────────────┘

Lobsters / Reddit Card

┌──────────────────────────────────────────────────────────────────────────┐
│ ○ #N  source: Lobste.rs                              [P1] Systems       │
│       ▲ 45 score   🏷 rust, cli             Apr 12, 2026 · 5h ago      │
│                                                                          │
│  Title of the post                                                       │
│                                                                          │
│  → https://lobste.rs/s/abc123                                            │
└──────────────────────────────────────────────────────────────────────────┘

Card Rules

1. Box width: 76 inner (78 with border). Fixed.
2. Header: read-status icon + source/author left,

   [tier] topic

   right-aligned
3. Date line: engagement stats LEFT, date + relative time RIGHT (e.g.,

   Apr 12, 2026 · 3h ago

   )
4. Engagement: K/M suffixes for >999
5. Text: wrap ~70 chars, max 4 lines, truncate with …
6. Link: always

   → https://FULL_URL

   at bottom (MUST include

   https://

   prefix so terminals render clickable links)
7. Tier section headers:

   ━━━ P0: AGENTIC AI ━━━━━━━━━━━━━━━━━━━━━━━━━━━

Date Display Rules

• Twitter: use the

  time

  field from JSON, convert to

  MMM DD, YYYY · Nh ago

  or

  Nd ago

• HN: use

  created_at

  field
• GitHub: use

  created_at

  field from repo
• Lobsters: use

  created_at

  field
• HuggingFace: use

  lastModified

  field
• arXiv: use

  published

  field
• Relative time:

  Xm ago

  if <1h,

  Xh ago

  if <24h,

  Xd ago

  if <30d, just date if older

Read Status Icons

• ○

  = unread (not yet read/actioned)

• ●

  = read (seen/actioned)

Default: all items start as

○

●

Action Items Box (after all cards)

┌─── ACTION ITEMS ──────────────────────────────────────────────────────┐
│  📄 @author — description → https://URL                                │
│  ⭐ repo — description → https://URL                                   │
│  🔧 tool — description → https://URL                                   │
└──────────────────────────────────────────────────────────────────────┘

Summary Footer

━━━ 42 items | P0: 10 · P1: 6 · P2: 8 · P3: 18 | ○ 38 unread · ● 4 read | 3 action items ━━━

Phase 3.5: READING LIST — Track Read Status

After displaying cards, save/update a reading list at

~/.secondmem/reading-list.md

Reading List File Format

# Reading List

## Fetched: 2026-04-12 22:30

### Unread (○)
| # | Status | Tier | Source | Author/Repo | Summary | URL | Date |
|---|--------|------|--------|-------------|---------|-----|------|
| 1 | ○ | P0 | GitHub | hermes-agent-orange-book | Agent framework guide | github.com/... | Apr 10 |
| 2 | ○ | P0 | Twitter | @sharbel | AI agents hijacked by websites | x.com/... | Apr 12 |

### Read (●)
| # | Status | Tier | Source | Author/Repo | Summary | URL | Date | Read On |
|---|--------|------|--------|-------------|---------|-----|------|---------|
| 4 | ● | P0 | Twitter | @tom_doerr | 1000+ agent skills | x.com/... | Apr 12 | Apr 12 |

Reading List Rules

1. On every fetch: Append new items to

   Unread (○)

   section. Don't duplicate (match by URL).
2. Mark as read: "mark #N read", "done with #N", "read #N" → move from Unread to Read, add

   Read On

   date.
3. Mark batch: "mark all P0 read", "done with [topic]" → move matching items.
4. Show unread: "what's pending", "unread items" → display ○ items as cards.
5. Show read: "what did I read", "reading history" → show ● items.
6. Auto-mark: When user discusses a specific item in depth, mark it ●.
7. Cleanup: Items older than 30 days in Read section → archive to

   reading-list-archive.md

   .

Phase 4: INGEST into Knowledge Base

After displaying cards, automatically ingest P0 and P1 items into

~/.secondmem/knowledge/

Knowledge base structure: Topic-first directories with month-scoped content files. Creates the directory structure automatically on first run.

Domain → Directory Mapping

/ai-ml/

agentic-ai-YYYY-MMM.md

/ai-ml/

ml-models-YYYY-MMM.md

/engineering/

gpu-hardware-landscape.md

/engineering/

database-internals-YYYY-MMM.md

/engineering/

/startups/

/research/

/people-insights/

/engineering/

frontend-YYYY-MMM.md

/engineering/

security-YYYY-MMM.md

Ingest Rules

1. Read target directory's

   hierarchy.md

   first (create if missing)
2. Check if relevant file exists — upsert if yes, create if no
3. Use month-scoped filenames for rolling content (

   database-internals-2026-apr.md

   )
4. Write content in structured markdown format (Topic, Source, Ingested, Tags, sections)
5. Tweet format:

   > "text" — @author, date

   + "Why this matters" + extracted links
6. Repo format: name, stars, language, description, why it matters
7. Paper format: title, authors, key claims, link
8. Every item MUST carry per-item dates in the source blockquote:

   > **Posted:** YYYY-MM-DD · **Ingested:** YYYY-MM-DD
   

   • Posted = original publish/tweet date (from API

     time

     ,

     created_at

     , or page date)
   • Ingested = today's date when written to knowledge base
   • Place immediately after the engagement line in the blockquote
9. Update directory

   hierarchy.md

   after writes
10. Update root

    hierarchy.md

    if new files created
11. Update

    ~/.secondmem/timeline.md

    — append new items to current month section
12. Log to

    ~/.secondmem/logs/ingest.log

13. Max 1116 lines per file — split if exceeded
14. Cross-reference new files with related existing files (3-8 refs)

Date Organization Strategy

• Primary axis: topic-first — files live in topic directories (

  /ai-ml/

  ,

  /engineering/

  )
• Secondary axis: month-scoped filenames — rolling content uses

  topic-YYYY-mmm.md

• Chronological index:

  ~/.secondmem/timeline.md

  — reverse-chronological index for date-based recall
• "What did I learn last week?" → read

  timeline.md

• "What do I know about databases?" → read topic directory
• Both paths lead to the same content files — timeline is an index, not a copy

Timeline Index Format (

~/.secondmem/timeline.md

)

## 2026-04 (April)

| Date | Topic | Title | File | Source |
|------|-------|-------|------|--------|
| Apr 12 | Agentic AI | Agent web hijacking | ai-ml/agentic-ai-2026-apr.md | @sharbel |
| Apr 11 | Databases | Postgres BM25 extension | engineering/database-internals-2026-apr.md | timescale |

• Grouped by month, reverse chronological within each month
• One row per ingested item (not per file)
• Keep last 6 months; archive older to

  timeline-archive-YYYY.md

What gets ingested vs skipped

• Always ingest: P0 items, P1 items with significant engagement (>50 points/likes)
• Selectively ingest: P2 items that are repos, papers, or tool launches
• Skip: P3 items, engagement bait, generic motivation, duplicate RTs
• Always extract: Links from P0 tweets → separate entries for papers/repos

Knowledge Base Init (first run)

If

~/.secondmem/knowledge/hierarchy.md

mkdir -p ~/.secondmem/knowledge/{ai-ml,engineering,startups,research,people-insights}
mkdir -p ~/.secondmem/logs
# Create root hierarchy.md and per-directory hierarchy.md files

Phase 5: CONFIRM

After all phases complete, show summary:

━━━ mo-feed complete ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Fetched:  Twitter (50) + HN (10) + GitHub (10) + Lobsters (10) = 80 items
Unique:   62 after dedup
Classified: P0: 12 · P1: 18 · P2: 14 · P3: 18
Ingested: 24 items into knowledge base (12 P0 + 12 P1)
Files:    engineering/database-internals-2026-apr.md (updated)
          ai-ml/agentic-ai-2026-apr.md (created)
Reading:  24 new items added to reading list (○ unread)
Action:   5 links to check
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Modes

Agent Instructions

1. ALWAYS fetch with

   --json

   for Twitter (for classification)
2. Run cross-reference fetches in PARALLEL (independent curl calls)
3. Classify ALL items before displaying any cards
4. Display cards grouped by tier, sorted by engagement within tier
5. After displaying: ingest P0 + high-engagement P1 into knowledge base
6. Every ingested item MUST have

   > **Posted:** YYYY-MM-DD · **Ingested:** YYYY-MM-DD

7. Update hierarchy.md files after ingest
8. Append new items to

   ~/.secondmem/timeline.md

   under the current month section
9. Log all operations to

   ~/.secondmem/logs/ingest.log

10. Save catch-up file to

    ~/Documents/mo-feed-catchup-YYYY-MM-DD.md

    for >20 items
11. Default to

    --lang en

    for Twitter
12. If a fetch fails (timeout, no Chrome), skip that source and continue with others
13. Never block the whole pipeline on one source failure
14. On first run, create

    ~/.secondmem/

    directory structure if it doesn't exist

Customization Guide

Adding Your Own Interest Tiers

Edit the Priority Tiers table in Phase 2. Add keywords that matter to you:

| **P0** | Your Domain | keyword1, keyword2, keyword3 |

Adding Your Key Accounts

Replace the Key Accounts list with Twitter handles you want to always surface.

Adding New Sources

Add a new entry to the Source-specific fetch table with the API/curl command. The classifier works on any text content — just feed it JSON with a

text

title

Changing the Knowledge Base Path

The default knowledge base path is

~/.secondmem/knowledge/

~/.secondmem/

Disabling Ingest

For a read-only feed (no knowledge base writes), use Quick peek mode: say "quick feed" or "headlines" instead of "catch me up".