ai-provenance/ai-dev-memory/devmemory-coordination

Claude Code and agent skill by ai-provenance/ai-dev-memory

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Universal agent coordination to share learnings, skills, and context across all AI agents (Claude, Cursor, Copilot, Mistral, Antigravity) running on this project.

Install

npx vskill@latest install ai-provenance/ai-dev-memory/devmemory-coordination

SKILL.md

Universal Agent Coordination System

This skill works with ANY AI coding agent (Cursor, Claude, Copilot, Mistral, Antigravity, etc.)

All agents share the same memory system. What one agent learns, all agents can use.

1. Memory Access Pattern (Universal)

python
# Get complete context for your task
from devmemory.agent_tools import get_universal_agent_tools
memory = get_universal_agent_tools()
context = memory.get_hierarchical_context("implement authentication system")

2. Cross-Agent Learning

python
# Store what you've learned (universal format)
memory.store_agent_learning(
learning="Use OAuth2 with PKCE for mobile auth to prevent token theft",
learning_type="semantic",
topics=["security", "authentication", "mobile"],
entities=["OAuth2", "PKCE"]
)

3. Reusable Skills System

python
# Check if skill exists
skill = memory.get_agent_skill("authentication_pattern")
if not skill:
# Store new skill for all agents to use
memory.store_agent_skill(
skill_name="authentication_pattern",
skill_description="Secure authentication pattern using JWT with refresh tokens",
implementation="1. Use short-lived access tokens...",
use_cases=["Web applications", "Mobile apps"]
)

4. Coordination Protocol

python
# Check who's working on what
coordination = memory.get_hierarchical_context("current work")
active_sessions = coordination["coordination"]["active_sessions"]
# Announce your work
memory.store_agent_learning(
learning="Currently implementing OAuth2 provider integration",
topics=["active-work", "coordination"],
entities=["authentication"]
)

Keep memories relevant

Store:

  • Architecture decisions with rationale
  • Patterns and conventions
  • Gotchas and workarounds
  • API quirks and limitations
  • Performance optimizations

Avoid:

  • Implementation details obvious from code
  • Temporary debugging notes
  • Personal preferences
  • Redundant copies of commit messages

Security

  • Security scanPassed, 100 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
74
Repository forks
1
7-day trend score
22

Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 21 Mar 2026, 7 months ago.

Works with

Any agent vskill installs to: 56 targets in all. These 39 have a page on this site.

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