Daily Dev Agentic

Daily Dev Agentic

When to Use

Trigger phrases:

• "daily dev agentic"
• "Help me with daily dev agentic"

Use cases:

• When the task matches this skill's domain expertise

When NOT to use:

• For tasks outside this skill's scope

name description metadata

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".

clawdbot

requires primaryEnv

env

DAILY_DEV_TOKEN

DAILY_DEV_TOKEN

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.

🧠 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

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_.

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.

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

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.

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.

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/ ├── agentic-learning.md # Config, state, evolving goals └── learnings/ ├── 2024-01-15.md # Daily notes └── ...

See references/memory-format.md for format.

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.

When NOT to Use

• When the code change is in a frozen release branch under change management
• When the task requires access to production systems the agent cannot reach
• When the task is too trivial to warrant this skill
• When a more appropriate skill exists

Overview

Daily Dev Agentic supports coding practices with best practices and proven patterns.

Workflow

# Example: TDD workflow
def test_user_creation():
    user = create_user(name="Alice", email="alice@example.com")
    assert user.name == "Alice"
    assert user.email == "alice@example.com"
    assert user.created_at is not None

def test_user_creation_invalid_email():
    with pytest.raises(ValidationError):
        create_user(name="Alice", email="invalid")

1. Understand requirements — Clarify acceptance criteria and constraints
2. Design solution — Plan architecture and identify patterns
3. Implement — Write code following project conventions
4. Test — Unit tests, integration tests, edge cases
5. Review — Code review for quality, security, and performance
6. Document — Update relevant docs and changelogs

Quality Gates

• All tests passing
• No lint errors or warnings
• Code coverage meets threshold (≥70%)
• No security vulnerabilities detected
• Documentation updated

Best Practices

• Follow SOLID principles and KISS
• Write self-documenting code with clear naming
• Handle errors explicitly — no silent failures
• Keep functions small and focused (<50 lines)
• Use immutable data patterns where possible

Anti-Rationalization Table

Process

1. Prepare — Gather requirements, verify prerequisites, set up environment
2. Execute — Run daily dev agentic workflow with configured parameters
3. Verify — Validate output meets requirements, document results

Verification

• All steps executed successfully
• Results validated against acceptance criteria
• Error handling tested with edge cases
• Documentation updated with findings