Borrowing it
Nothing to install: this file belongs to raghavwahi/semdex-mcp-server. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/raghavwahi/semdex-mcp-server/main/.claude/skills/sdx-init/SKILL.mdgit clone --depth 1 https://github.com/raghavwahi/semdex-mcp-serverWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/raghavwahi/semdex-mcp-server/sdx-init)<a href="https://agentmods.dev/skills/raghavwahi/semdex-mcp-server/sdx-init"><img src="https://agentmods.dev/badge/skills/raghavwahi/semdex-mcp-server/sdx-init/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/raghavwahi/semdex-mcp-server/sdx-init"><img src="https://agentmods.dev/badge/skills/raghavwahi/semdex-mcp-server/sdx-init.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00042 | $0.00333 |
| Opus 5 | $0.00021 | $0.00167 |
| Sonnet 5 | $0.00008 | $0.00067 |
| Haiku 4.5 | $0.00004 | $0.00033 |
Grade A, and why
sdx-init scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Initialize Semdex
First-Time Setup
# Index the entire repo
sdx init
# Index only specific directories (skip tests, fixtures)
sdx init --scope src/ --scope lib/
# Index with preview (show what would be indexed without storing)
sdx init --dry-run
# Force re-download of embedding model
sdx init --force-model-download
What It Does
- Creates
.repoidentity/directory structure - Downloads embedding model (
Xenova/all-MiniLM-L6-v2, ~45 MB q8) with progress bar - Scans repo for source files (TypeScript + Python in MVP)
- Parses each file with Tree-sitter WASM grammars
- Extracts semantic chunks (functions, classes, interfaces, etc.)
- Computes XXH3 content hashes for each chunk
- Generates embeddings for each chunk (cached — skips if content hasn't changed)
- Stores everything in
.repoidentity/index.db(SQLite + sqlite-vec) - Generates manifest with detected languages and frameworks
After Init
- Run
sdx serveto start the MCP server - Run
sdx inspect --statsto verify the index - Run
sdx bench --quickto check performance
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 43 lines · 42 tokens per session scan A a62f801cc6ca
sdx-init is a skill published in the GitHub repository raghavwahi/semdex-mcp-server (0 stars, last pushed 1mo ago), licensed MIT. It adds 42 tokens to every session and 333 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
agent-platform-rag-engine-management
Manage and query Agent Platform RAG Engine Corpora and retrieve grounded contexts using the Google GenAI SDK. Use when listing RAG corpora or files, inspecting a corpus, retrieving contexts, or generating content grounded in a RAG corpus. Do not use for standard database queries (use SQL/Spanner skills), Google…
llm-app-patterns
Production-ready patterns for building LLM applications. Covers RAG pipelines, agent architectures, prompt IDEs, and LLMOps monitoring. Use when designing AI applications, implementing RAG, building agents, or setting up LLM observability.
9router-embeddings
Generate vector embeddings via 9Router /v1/embeddings using OpenAI / Gemini / Mistral / Voyage / Nvidia / GitHub embedding models for RAG, semantic search, similarity. Use when the user wants embeddings, vectors, RAG, semantic search, or to embed text.
azure-search-documents-dotnet
Azure AI Search SDK for .NET (Azure.Search.Documents). Use for building search applications with full-text, vector, semantic, and hybrid search. Covers SearchClient (queries, document CRUD), SearchIndexClient (index management), and SearchIndexerClient (indexers, skillsets). Triggers: "Azure Search .NET"…
browserwing-admin
Manage and operate BrowserWing — an intelligent browser automation platform. Install dependencies, configure LLM, create/manage/execute automation scripts, use AI-driven exploration to generate scripts, browse the script marketplace, and troubleshoot issues.
similarity-search-patterns
Implement efficient similarity search with vector databases. Use when building semantic search, implementing nearest neighbor queries, or optimizing retrieval performance.