lsap-api-design — community lsap-api-design, community, ide skills, Claude Code, Cursor, Windsurf

v1.0.0
GitHub

About this Skill

Ideal for AI Coding Agents requiring advanced Language Server interactions and LSAP protocol integration. LSAP (Language Server Agent Protocol) is an open protocol that defines how AI coding agents interact with Language Servers

lsp-client lsp-client
[12]
[0]
Updated: 2/27/2026

Agent Capability Analysis

The lsap-api-design skill by lsp-client is an open-source community AI agent skill for Claude Code and other IDE workflows, helping agents execute tasks with better context, repeatability, and domain-specific guidance.

Ideal Agent Persona

Ideal for AI Coding Agents requiring advanced Language Server interactions and LSAP protocol integration.

Core Value

Empowers agents to design and implement LSAP APIs, leveraging Pydantic for request/response models, Markdown templates, and semantic anchoring via Locate, while orchestrating LSP operations through the lsp-client library.

Capabilities Granted for lsap-api-design

Designing custom LSAP APIs for agent-specific use cases
Implementing business logic and capability composition using LSAP
Integrating LSAP with Language Servers for enhanced coding capabilities

! Prerequisites & Limits

  • Requires knowledge of LSAP protocol and Language Server architecture
  • Python-specific implementation using Pydantic and lsp-client library
  • Dependent on existing LSAP schema and capability layers for extension
Labs Demo

Browser Sandbox Environment

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Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

lsap-api-design

Install lsap-api-design, an AI agent skill for AI agent workflows and automation. Works with Claude Code, Cursor, and Windsurf with one-command setup.

SKILL.md
Readonly

LSAP API Design

Guide for adding new APIs to LSAP. Study existing code as needed.

Architecture

Three layers:

  1. Schema (src/lsap/schema/): Request/Response models (Pydantic), Markdown templates
  2. Capability (src/lsap/capability/): Business logic, LSP orchestration
  3. LSP (lsp-client library): Raw protocol operations

Key Principles: Agent-cognitive design, Markdown-first output, semantic anchoring via Locate, composed capabilities

Reference Implementations

Study these before implementing:

  • Simple: src/lsap/schema/definition.py + src/lsap/capability/definition.py
  • Paginated: src/lsap/schema/reference.py + src/lsap/capability/reference.py
  • Multi-mode: src/lsap/schema/rename.py + src/lsap/capability/rename.py
  • Complex: src/lsap/schema/symbol.py + src/lsap/capability/symbol.py

Implementation Steps

1. Define Schema (src/lsap/schema/<name>.py)

See src/lsap/schema/definition.py for complete example.

Key components:

  • Request Model: Inherit from Request, LocateRequest, or PaginatedRequest
  • Response Model: Inherit from Response or PaginatedResponse
  • Markdown Template: Liquid template in model_config.json_schema_extra["markdown"]

Template basics (see docs/liquid_cheatsheet.md):

  • Conditionals: {% if items.size == 0 %}...{% endif %}
  • Loops: {% for item in items %}...{% endfor %}
  • Filters: {{ mode | capitalize }}, {{ path | join: "." }}

2. Implement Capability (src/lsap/capability/<name>.py)

See src/lsap/capability/definition.py for complete example.

Pattern:

python
1from attrs import define 2from .abc import Capability 3 4@define 5class MyCapability(Capability[MyRequest, MyResponse]): 6 async def __call__(self, req: MyRequest) -> MyResponse | None: 7 # 1. Locate position (if needed) 8 if not (loc_resp := await self.locate(req)): 9 return None 10 11 # 2. Call LSP operations via ensure_capability() 12 # 3. Process results (use asyncer.create_task_group for parallelism) 13 # 4. Return response (or None on failure)

Important: Return None on failure, not empty response.

3. Register Exports

Add to src/lsap/capability/__init__.py and src/lsap/schema/__init__.py

4. Add Tests

See tests/test_definition.py for examples. Must test: success case, not found case.

5. Add Documentation

Create schema/<name>.md with usage examples.

Common Patterns

Pagination

See src/lsap/capability/reference.py for complete pattern with PaginationCache and paginate().

Reading Code Context

python
1from lsap.utils.document import DocumentReader 2 3content = await self.client.read_file(file_path) 4reader = DocumentReader(content) 5snippet = reader.read(context_range, trim_empty=True)

Symbol Information

python
1from lsap.utils.symbol import symbol_at 2 3symbols = await ensure_capability( 4 self.client, WithRequestDocumentSymbol 5).request_document_symbol_list(file_path) 6 7if symbols and (match := symbol_at(symbols, position)): 8 symbol_path, symbol = match

LSP Capability Check

python
1from lsap.utils.capability import ensure_capability 2 3result = await ensure_capability( 4 self.client, 5 WithRequestReferences, 6 error="Fallback instructions if not supported" 7).request_references(file_path, position)

Common Utilities

See src/lsap/utils/ for implementations.

Path handling:

  • client.from_uri(uri) - Returns relative path by default
  • client.from_uri(uri, relative=False) - Returns absolute path

Position conversion:

  • Position.from_lsp(lsp_pos) - LSP (0-based) → LSAP (1-based)
  • lsap_pos.to_lsp() - LSAP (1-based) → LSP (0-based)

Hover content:

  • clean_hover_content(hover.value) - Removes LSP formatting artifacts

Checklists

Files to create:

  • src/lsap/schema/<name>.py
  • src/lsap/capability/<name>.py
  • tests/test_<name>.py
  • schema/<name>.md

Files to update:

  • src/lsap/schema/__init__.py
  • src/lsap/capability/__init__.py

Must verify:

  • Returns None on failure (not empty response)
  • Uses ensure_capability() for LSP operations
  • Concurrent operations use semaphores
  • Tests cover success and failure cases
  • docs/locate_design.md - Position resolution patterns
  • docs/liquid_cheatsheet.md - Template syntax
  • CONTRIBUTING.md - Development workflow

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is lsap-api-design?

Ideal for AI Coding Agents requiring advanced Language Server interactions and LSAP protocol integration. LSAP (Language Server Agent Protocol) is an open protocol that defines how AI coding agents interact with Language Servers

How do I install lsap-api-design?

Run the command: npx killer-skills add lsp-client/LSAP/lsap-api-design. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for lsap-api-design?

Key use cases include: Designing custom LSAP APIs for agent-specific use cases, Implementing business logic and capability composition using LSAP, Integrating LSAP with Language Servers for enhanced coding capabilities.

Which IDEs are compatible with lsap-api-design?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for lsap-api-design?

Requires knowledge of LSAP protocol and Language Server architecture. Python-specific implementation using Pydantic and lsp-client library. Dependent on existing LSAP schema and capability layers for extension.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add lsp-client/LSAP/lsap-api-design. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use lsap-api-design immediately in the current project.

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