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 agentmods add skills/thoreinstein/obsidian-rag/indexnpx skills add thoreinstein/obsidian-rag --skill indexgit clone --depth 1 https://github.com/thoreinstein/obsidian-ragWrote 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/thoreinstein/obsidian-rag/index)<a href="https://agentmods.dev/skills/thoreinstein/obsidian-rag/index"><img src="https://agentmods.dev/badge/skills/thoreinstein/obsidian-rag/index.svg" alt="Measured on agentmods" 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 | $0.00036 | $0.00181 |
| Opus 5 | $0.00018 | $0.00090 |
| Sonnet 5 | $0.00007 | $0.00036 |
| Haiku 4.5 | $0.00004 | $0.00018 |
Grade A, and why
index 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 4d 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.
This is a copy
100% identical to index — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Index Vault
Trigger vault indexing for semantic search (RAG).
Default Action
Call obsidian_rag_index with no special arguments. This runs an incremental index — only changed files are re-embedded.
Force Reindex
If the user says "force" or "rebuild from scratch":
- Call
obsidian_rag_indexwithforce_reindex: true
Single File
If the user specifies a file:
- Call
obsidian_rag_indexwithfile_pathset to the relative path
After Indexing
Report the result: how many chunks were indexed, whether it was incremental or full.
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.
- 4d ago First seen · 29 lines · 36 tokens per session scan A 59ee6a426076
index is a skill published in the GitHub repository thoreinstein/obsidian-rag (2 stars, last pushed 1mo ago), licensed MIT. It adds 36 tokens to every session and 181 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to index, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
laravel-ai-sdk
Use when integrating AI agents, tool calling, embeddings, structured output, or streaming in Laravel 13 via the laravel/ai package.
laravel-vector-search
Use when implementing semantic/vector search in Laravel 13 with PostgreSQL + pgvector.
query
Use when retrieving from a project knowledge-base/ — multi-channel RAG recall (vector plus lexical plus metadata, RRF-fused) returning locate-pointer cards; multi-round and multi-angle querying allowed. Trigger /ragkit:query, or called by name by workflows like specode. Building or refreshing the index instead uses…
embed
Use when building or refreshing the RagKit index for a project knowledge-base/ (e.g. after distill added or updated knowledge points). Trigger /ragkit:embed. Querying instead uses ragkit:query; index health uses ragkit:status.
eval
Use when measuring or tuning RagKit retrieval accuracy — runs the golden evalset, reports recall@k and MRR per bucket. Trigger /ragkit:eval. Run before or after any retrieval-param change to keep a baseline.
using-ragkit
Overview of the ragkit plugin and how to use it — knowledge-base multi-channel retrieval and its four skills. On Kimi Code this is loaded at session start via the manifest's sessionStart.skill; on hosts with a SessionStart hook the same advisory is injected by the hook instead.