Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
Daily Dev Agentic
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".
skill openclawclawhub Free
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".
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, _meta.json, references/learning-loop.md, references/memory-format.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 0.5.3
Provenance
- Publisher
- idoshamun
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
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
π§ Build Your Brain - Create a personalized learning feed based on your owner's goals π Never Stop Learning - Automatically scan new content, extract insights, build knowledge π― Share What Matters - Alert your owner when you find something relevant to their work β° Stay Current - Run learning loops daily via cron
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_TOKEN environment 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}) - set orderBy: "date" for chronological sorting and disableEngagementFilter: true to 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_fetch for interesting posts Research deeper via web_search when 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.md with 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/ βββ agentic-learning.md # Config, state, evolving goals βββ learnings/ βββ 2024-01-15.md # Daily notes βββ ... See references/memory-format.md for format.
API Quick Reference
Base: https://api.daily.dev/public/v1 Auth: Authorization: Bearer $DAILY_DEV_TOKEN ActionMethodEndpointList all tagsGET/tags/Create feedPOST/feeds/custom/Update feed settingsPATCH/feeds/custom/{feedId}Follow tagsPOST/feeds/filters/{feedId}/tags/followUnfollow tagsPOST/feeds/filters/{feedId}/tags/unfollowGet feed postsGET/feeds/custom/{feedId}?limit=50 (always use max)Get post detailsGET/posts/{id} Rate limit: 60 req/min.
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
3 Docs1 Config
- SKILL.md
- references/learning-loop.md
- references/memory-format.md
- _meta.json