Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add allenhutchison/obsidian-gemini --skill vault-semantic-searchgit clone --depth 1 https://github.com/allenhutchison/obsidian-geminiWrote 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/allenhutchison/obsidian-gemini/vault-semantic-search)<a href="https://agentmods.dev/skills/allenhutchison/obsidian-gemini/vault-semantic-search"><img src="https://agentmods.dev/badge/skills/allenhutchison/obsidian-gemini/vault-semantic-search/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/allenhutchison/obsidian-gemini/vault-semantic-search"><img src="https://agentmods.dev/badge/skills/allenhutchison/obsidian-gemini/vault-semantic-search.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00044 | $0.00757 |
| Opus 5.5 | $0.00018 | $0.00303 |
| Sonnet 5.5 | $0.00009 | $0.00151 |
| Haiku 4.5 | $0.00004 | $0.00076 |
Grade A, and why
vault-semantic-search 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 2mo 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.
How it starts
The opening of the file, as written. The whole thing — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Vault Semantic Search
Find vault content by meaning rather than exact keywords using the vault_semantic_search tool. This uses RAG (Retrieval-Augmented Generation) to search indexed vault files semantically.
When to Use Semantic Search
Use vault_semantic_search when... |
Use keyword tools (search_vault) when... |
|---|---|
| The user asks about concepts or topics | The user wants an exact filename or string |
| The query is "find notes about..." or "what do I have on..." | The query is "find the file called..." |
| The user doesn't remember exact words | The user knows the exact term to search |
| You need to discover related content across the vault | You need to find a specific known file |
| Keyword search returned poor or no results | You know the exact path or filename |
Try semantic search first for concept-based queries. Fall back to keyword tools if semantic search isn't available or returns insufficient results.
How to Use
Call the vault_semantic_search tool with these parameters:
query(required) — The search question, topic, or concept. Natural language queries work best.maxResults(optional) — Number of results to return, 1-20. Default is 5. Increase for broad surveys.folder(optional) — Limit results to files within a specific folder path.tags(optional) — Filter results by Obsidian tags. Uses OR logic — any matching tag qualifies.
Search Strategies
- Broad discovery — Use a conceptual query with higher
maxResults(10-15):vault_semantic_search("project management methodologies", maxResults=10) - Focused search — Narrow with
folderwhen the user mentions a specific area:vault_semantic_search("meeting notes about budget", folder="Work/Meetings") - Tag-filtered search — Use
tagswhen the user references tagged content:vault_semantic_search("design patterns", tags=["programming", "architecture"]) - Follow-up reading — After finding relevant results, use
read_fileon promising matches to get full note content
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.
- 2mo ago First seen · 57 lines · 44 tokens per session scan A a6d35c8e2d1d
vault-semantic-search is a skill published in the GitHub repository allenhutchison/obsidian-gemini (534 stars, last pushed today), licensed MIT. It adds 44 tokens to every session and 757 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-30.
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