Agent
Plan Location: plans/0041-limps-improvements/0041-limps-improvements-plan.md.
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original MIT
Agent
Plan Location: plans/0041-limps-improvements/0041-limps-improvements-plan.md.
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original MIT
Agent
Plan Location: plans/0041-limps-improvements/0041-limps-improvements-plan.md.
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original MIT
Agent
This feature has been moved to a separate plan for cleaner scope separation.
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original MIT
Agent
Plan Location: plans/0041-limps-improvements/0041-limps-improvements-plan.md.
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Agent
Define entity and relationship types in TypeScript. Implement SQLite storage layer with efficient indexing.
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original MIT
Agent
Extract entities and relationships from markdown using regex patterns and lightweight NLP. No LLM calls.
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Agent
Detect duplicate and similar entities across plans using embedding similarity + fuzzy matching. No LLM reasoning.
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original MIT
Agent
Route queries deterministically with regex patterns. Fuse results with RRF. No LLM in the retrieval loop.
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original MIT
Agent
Watch for file changes, auto-index, and surface conflicts proactively. No query needed — system detects problems automatically.
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Agent
Build the primary CLI interface. CLI is the source of truth. MCP and Obsidian wrap CLI.
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Create thin MCP wrappers around CLI commands. MCP tools are just exec('limps ...').
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Document the system-intelligent architecture, CLI reference, and integration with Plan 0028 (Obsidian).
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Build the core skill loading infrastructure that reads SKILL.md files from dist/skills/ with progressive disclosure support.
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original MIT
Agent
Implement CLI commands for skill management: list, show, read.
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Agent
Export skills to any supported AI agent's directory structure (Claude, Cursor, Codex, etc.).
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Agent
Auto-install skills when @sudosandwich/limps is installed via npm.
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Agent
Scaffold new skills from templates with limps skill create.
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Agent
Create MCP tools that wrap skill CLI commands (CLI-first pattern).
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Agent
Define the .limps/ workspace structure and implement initialization.
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Agent
Build the context inheritance engine that resolves cascading context from workspace → project → plan → agent.
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Agent
Implement persistent memory for agents that survives across sessions.
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original MIT
Agent
Implement plan-level shared memory for cross-agent learnings.
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original MIT
Agent
Detect stale context files and surface freshness warnings.
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original MIT