Agent skill

web-rag

(ePost) Use when searching web codebase for components, design tokens, Next.js patterns, or any luz_next implementation via vector search

View SKILL.md on GitHub Repository
Stars 163
Forks 31

Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/other/web-rag

Metadata

Additional technical details for this skill

keywords
rag vector-search klara-theme luz-next web components design-tokens patterns implementation
triggers 
[
    "search components",
    "find component",
    "klara-theme",
    "design token",
    "luz_next",
    "web pattern",
    "implementation"
]
platforms 
[
    "web"
]
connections 
{
    "enhances": [
        "web-frontend"
    ]
}
agent affinity 
[
    "epost-muji",
    "epost-fullstack-developer",
    "epost-planner",
    "epost-researcher"
]

SKILL.md

Web RAG Skill

Purpose

Vector search for the web codebase. Semantic search across luz_next application code, klara-theme component libraries, design tokens, and implementation patterns via MCP tools.

MCP Tools

Tool Purpose
query Semantic search — returns code chunks with relevance scores
status Health check, indexed modules, document counts
catalog List available components/hooks/styles per module (no vector search)
navigate O(1) shortcut to known code locations
expansions Component alias mappings + synonym groups for query planning

Tool parameters are self-describing — check inputSchema for current options.

Discovery Protocol

Before querying, discover what's indexed:

  1. Call status — returns available modules, document counts, health
  2. Call catalog (optional) — lists components/hooks/styles for discovery
  3. Call expansions (once per session) — get component aliases and synonym groups

Use discovered values for module, filters.scope, and filters.component params.

When to Use

Scenario RAG Grep/Glob Context7
Find component by concept yes if know filename no
Search design tokens yes yes no
Library API docs no no yes
Pattern across codebase yes exact match only no
Discover available components catalog no no

Query Strategy

  1. Known component or file? -> query + component filter (get canonical name from expansions)
  2. Known topic area? -> query + topic/file_type filters (discover valid values via status)
  3. Conceptual/cross-cutting? -> Smart query with HyDE (see references/smart-query.md)
  4. < 3 results or low scores? -> Broaden: remove filters, try synonyms, alternate casing
  5. Still nothing? -> Fall through to Grep/Glob (codebase search)

Rules

  1. Start broad, refine with filters — not longer queries
  2. Natural language works best — "button with loading state" over "btn loading"
  3. Low relevance scores suggest rephrasing needed
  4. If server offline, fall back to Grep/Glob
  5. stale_sidecar: true in results — trust code chunks, ignore metadata fields
  6. Do NOT generate synonym variants — server handles expansion automatically

Integration

Priority level 2 in knowledge-retrieval chain:

  1. docs/ files -> 2. RAG -> 3. Skills/codebase -> 4. Context7

Related Skills

  • knowledge-retrieval — Orchestrates source priority
  • web-frontend — Frontend patterns (enhanced by this skill)
  • docs-seeker — External documentation lookup

References

  • references/smart-query.md — HyDE + multi-query retrieval strategy
  • references/sidecar-workflow.md — AI-generated metadata enrichment
  • references/component-mappings.md — Get canonical names via expansions MCP tool
  • references/synonym-groups.md — Get synonym groups via expansions MCP tool

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