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Gives coding agents decision-time memory of validated traps, fixes, and dead ends.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "app.twiceshy/twiceshy" MCP server from askskill: Run: claude mcp add --transport http 'app-twiceshy-twiceshy' 'https://api.twiceshy.app'
Please turn this debugging session into experience memory: include validated causes, dead-end attempts, and the final fix so future coding agents can use it during similar decisions.
A structured experience record separating traps, validated fixes, and dead ends.
Before changing this feature, retrieve past experience related to this module and list known traps, recommended fixes, and attempts to avoid.
A decision-focused experience summary that helps avoid repeating mistakes.
Capture the key decisions made by multiple coding agents in this task as experience memory, marking which approaches were validated and which directions proved unworkable.
Reusable collaboration experience entries for future agents.
Developers or coding agents can review previously validated traps and failed paths before tackling similar issues. This reduces repeated trial and error and focuses effort on more promising fixes.
When an agent must decide how to change code, investigate an issue, or choose an approach, this tool can supply historical experience as reference. It is especially useful when past conclusions should inform current decisions.
It is an experience-memory tool for coding agents that provides validated traps, fixes, and dead ends at decision time. Its focus is bringing past lessons into current coding decisions.
Based on the description, it is more about experience memory for coding agents than direct code generation. Its value is helping agents avoid detours and reuse validated conclusions.
The provided material does not include installation steps, runtime details, or key requirements. Please see the source repository for prerequisites.
Gives coding agents a deterministic call graph to reduce breakage and token waste.
Provide durable, local-first memory for AI coding agents across MCP hosts.
Give AI coding agents persistent, verifiable memory tied to a codebase.
Give coding agents local structural memory for leaner, refactor-safe development.
Provide persistent, verified memory and guardrails for AI coding agents.
Store coding history, decisions, and fixes for AI agents in your repo.