LAP: 1,500+ API Specs Compiled for LLM Consumption to Reduce Claude Hallucinations
What LAP Does
LAP addresses the problem where AI coding agents like Claude hallucinate API endpoints when given vague instructions like "use the Stripe API to create a charge." Instead of guessing or relying on stale training data, LAP provides compiled API specifications specifically structured for LLM consumption.
The core issue is that standard OpenAPI specs are built for humans, not agents. For example, Stripe's OpenAPI spec contains 1.2 million tokens of what the source describes as "noise." LAP compiles these specs 10x smaller while maintaining verified endpoints, correct parameters, and actual authentication requirements.
Technical Implementation
LAP was built primarily with Claude's assistance:
- Claude Code wrote approximately 99.9% of the Python compiler, the TypeScript port, and the benchmark harness
- The registry pipeline (processing 1,500+ specs) was built iteratively with Claude handling parsing, validation, and edge case handling
- The lean output format was co-designed with Claude, optimized for what actually helps agents make correct API calls
- The compilation process is deterministic with no AI in the compilation loop
Workflow Integration
LAP provides several commands for integration:
lap initsets up LAP skills and hooks into automatic update checkinglap checktells you when installed specs are outdatedlap diffshows exactly what changed in updated specs
In practice, you can tell Claude: "Integrate Discord into the project, use LAP to fetch the spec" → Claude will invoke the LAP skill, install the right API-skill, and start coding with verified endpoints instead of guessing.
Performance Benefits
According to the source, LAP delivers:
- 35% cheaper runs
- 29% faster responses
- The primary benefit: agents stop making up endpoints
Getting Started
LAP is open source with PRs, features, and spec requests welcome:
- Initialize with:
npx @lap-platform/lapsh init - GitHub: https://github.com/Lap-Platform/LAP
- Registry (1,500+ APIs): https://registry.lap.sh
📖 Read the full source: r/ClaudeAI
👀 See Also
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