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 Howie126313/obsidian-vault-kit --skill vault-querygit clone --depth 1 https://github.com/Howie126313/obsidian-vault-kitWrote 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/howie126313/obsidian-vault-kit/vault-query)<a href="https://agentmods.dev/skills/howie126313/obsidian-vault-kit/vault-query"><img src="https://agentmods.dev/badge/skills/howie126313/obsidian-vault-kit/vault-query.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 5.1 | $0.00057 | $0.00982 |
| Opus 5 | $0.00028 | $0.00491 |
| Sonnet 5 | $0.00011 | $0.00196 |
| Haiku 4.5 | $0.00006 | $0.00098 |
Grade A, and why
vault-query scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Vault Query — Karpathy-Style Knowledge Synthesis
Based on the "compile, don't retrieve" philosophy: look up the index first, read full text to synthesize, write back high-value answers.
Workflow
Step 1: Environment Detection & Query Parsing
1a. Detect vault root — follow ../../_shared/common-steps.md "Vault Detection" section.
1b. Parse user query intent:
Extract from user input:
query: core question or keywordsscope: whether a directory scope was specified (e.g., user mentions a topic that maps to a configured directory)depth: simple lookup ("which article covers X") vs deep synthesis ("compile everything about X")
Step 2: Index Lookup
2a. Read index.md:
Read("$VAULT_ROOT/index.md")
Scan all entries in index.md — titles, summaries, and tags — to find candidate articles related to the query (typically 3-8).
2b. Supplementary search:
index.md may miss content. Use Grep to supplement:
Grep("{keyword}", path="$VAULT_ROOT", glob="**/*.md")
Exclude results from .claude/, .git/, reviews/, index.md.
2c. Determine reading list:
Merge index lookup and Grep results, sort by relevance, finalize the list of articles to read in full.
Step 3: Deep Read & Synthesis
3a. Read relevant articles in full:
For each article on the reading list, use Read to get full text. Read in parallel for efficiency.
3b. Synthesize the answer:
Choose synthesis mode based on depth:
- Simple lookup: list relevant articles and their key points, point the user to read directly
- Deep synthesis:
- Extract key information from multiple articles
- Integrate into a complete knowledge picture, citing sources (
see [[article-name]]) - Surface connections, contradictions, or complementary relationships between articles
- Identify knowledge gaps ("no article covers aspect Y of topic X")
Step 4: Write-Back Decision
After synthesizing, evaluate whether writing back is warranted:
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 · 115 lines · 57 tokens per session scan A 999ea1acfc34
vault-query is a skill published in the GitHub repository Howie126313/obsidian-vault-kit (3 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 57 tokens to every session and 982 once invoked, about $0.0003 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.
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