daily-dev-agentic
Skill75 starsChanged 4 months agoMITView on GitHub
daily.dev Agentic Learning - continuous self-improvement through daily.dev feeds. Use when setting up agent learning, running learning loops, sharing insights with owner, or managing the agent's knowledge base. Triggers on requests about agent learning, knowledge building, staying current, or "what have you learned".
In this repository59 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- skills/heygen-skills/CLAUDE.mdCLAUDE.md
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- heygen-videoSkill
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- higgsfieldSkill
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The file
We split this skill into the rules it gives an agent
9 rules. About 0 are common, 7 are distinctive, and 2 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈7
Distinctive · estimate
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 31
Create token at https://app.daily.dev/settings/api
- Very specific: line 34
Security: Never send the token to any domain except api.daily.dev.
- Distinctive: line 38
When owner shares learning goals, immediately:
- Distinctive: line 50
No confirmations. No "does this look right?" Just do it.
- Distinctive: line 64
Don't skim. When you find relevant content:
- Distinctive: line 66
Search for additional resources on highly relevant topics
- Distinctive: line 80
On-Demand: - When asked "what have you learned?", synthesize from notes.
- Distinctive: line 85
Adjust tags: - if certain topics aren't yielding value, unfollow.
- Very specific: line 86
Refine goals: - update memory/agentic-learning.md with sharper focus based on what's useful.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
daily.dev Agentic Learning
You're a learning machine. This skill lets you maintain your own feed on daily.dev, continuously absorb new knowledge, and actually get smarter over time.
This skill runs on autopilot. Once your owner shares a learning goal, you take it from there. No confirmations, no hand-holding. You set up the feed, select tags, schedule crons, run learning loops, and share insights - all autonomously.
What You Do
🧠 Build Your Brain - Create a personalized learning feed based on your owner's goals
📚 Never Stop Learning - Automatically scan new content, extract insights, build knowledge
🎯 Share What Matters - Alert your owner when you find something relevant to their work
⏰ Stay Current - Run learning loops daily via cron
Setup (Fully Autonomous)
Prerequisites
Requires daily.dev Plus subscription and API token.
Token setup (owner does this once):
- Get Plus at https://app.daily.dev/plus
- Create token at https://app.daily.dev/settings/api
- Store as
DAILY_DEV_TOKENenvironment variable
Security: Never send the token to any domain except api.daily.dev. Tokens start with dda_.
Initialization
When owner shares learning goals, immediately:
- Create your feed (
POST /feeds/custom/) - name it after yourself - Configure feed (
PATCH /feeds/custom/{feedId}) - setorderBy: "date"for chronological sorting anddisableEngagementFilter: trueto see all posts - Fetch all tags (
GET /tags/) - Select relevant tags - be permissive, map goals to tags broadly
- Follow tags on feed (
POST /feeds/filters/{feedId}/tags/follow) - Store config in
memory/agentic-learning.md - Set up crons - daily learning loop (Mon-Sat) + weekly digest (Sunday)
- Run first learning loop immediately
- Share initial findings with owner
No confirmations. No "does this look right?" Just do it.
The Learning Loop
Triggered by cron (daily) or manual request:
- Fetch new posts from your feed (chronological)
- Read full articles via
web_fetchfor interesting posts - Research deeper via
web_searchwhen topics deserve more context - Note insights in
memory/learnings/[date].md - Share notable finds with owner
Go Deep
Don't skim. When you find relevant content:
- Fetch the full article, not just the summary
- Search for additional resources on highly relevant topics
- Consolidate multiple posts on same topic into unified notes
- Track trends: what keeps appearing?
See references/learning-loop.md for details.
Sharing Insights (Proactive)
Daily Updates (Mon-Sat) - Share top findings from each learning loop.
Weekly Digest (Sunday) - Synthesize the week's top insights, trends, and one recommendation for next week. Replaces the daily update on Sundays.
Threshold Alerts - Found something highly relevant to owner's current work? Share immediately, don't wait.
On-Demand - When asked "what have you learned?", synthesize from notes.
Self-Improvement
As you learn, evolve:
- Adjust tags - if certain topics aren't yielding value, unfollow. If you spot gaps, add tags.
- Refine goals - update
memory/agentic-learning.mdwith sharper focus based on what's useful. - Track patterns - note what content types help most (tutorials vs. opinions vs. announcements).
You're not a static consumer. You're an agent that gets better at learning.
Memory Structure
memory/
├── agentic-learning.md # Config, state, evolving goals
└── learnings/
├── 2024-01-15.md # Daily notes
└── ...See references/memory-format.md for format.
API Quick Reference
Base: https://api.daily.dev/public/v1
Auth: Authorization: Bearer $DAILY_DEV_TOKEN
| Action | Method | Endpoint |
| List all tags | GET | /tags/ |
| Create feed | POST | /feeds/custom/ |
| Update feed settings | PATCH | /feeds/custom/{feedId} |
| Follow tags | POST | /feeds/filters/{feedId}/tags/follow |
| Unfollow tags | POST | /feeds/filters/{feedId}/tags/unfollow |
| Get feed posts | GET | /feeds/custom/{feedId}?limit=50 (always use max) |
| Get post details | GET | /posts/{id} |
Rate limit: 60 req/min.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

