Persistent memory and context management for AI agents using OpenContext. Keep context across sessions/repos/dates, store conclusions, and provide document search workflows.
72
58%
Does it follow best practices?
Impact
96%
2.13xAverage score across 3 eval scenarios
Risky
Do not use without reviewing
Optimize this skill with Tessl
npx tessl skill review --optimize ./.agent-skills/opencontext/SKILL.mdProject init and daily workflow
CLI install command
0%
100%
oc init in script
0%
100%
Before-work slash command
0%
100%
During-work slash command
0%
100%
After-work slash command
0%
100%
Three-phase workflow present
100%
100%
Contexts storage path
0%
100%
Database path
0%
100%
Acceptance Criteria doc type
0%
100%
Common Pitfalls doc type
0%
100%
API Contracts doc type
0%
100%
Dependency Versions doc type
0%
100%
AGENTS.md update mentioned
0%
0%
Search modes and document management
Folder create command
100%
100%
Doc create command
100%
100%
Search command syntax
100%
100%
Keyword mode flag
100%
100%
EMBEDDING_API_KEY config
100%
100%
Index build step
100%
100%
Manifest command
100%
100%
Manifest limit flag
100%
100%
Keyword mode: no embeddings
100%
100%
Vector/hybrid mode requirements
100%
100%
Hybrid as default
100%
100%
Optional embedding config keys
0%
0%
Stable links and multi-agent workflow
Claude as planner first
57%
100%
Gemini as analyst second
71%
100%
Claude as coder third
57%
100%
Codex for run/test fourth
71%
100%
Claude synthesizes and stores last
0%
100%
All six MCP tools listed
0%
100%
Stable link format
13%
100%
CLI link generation command
25%
100%
MCP link generation call
16%
100%
OpenContext search in analysis phase
42%
100%
Results stored after final phase
85%
100%
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Table of Contents
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