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 vasilyu1983/AI-Agents-public --skill docs-notes-retrievalgit clone --depth 1 https://github.com/vasilyu1983/AI-Agents-publicWrote 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/vasilyu1983/ai-agents-public/docs-notes-retrieval)<a href="https://agentmods.dev/skills/vasilyu1983/ai-agents-public/docs-notes-retrieval"><img src="https://agentmods.dev/badge/skills/vasilyu1983/ai-agents-public/docs-notes-retrieval/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/vasilyu1983/ai-agents-public/docs-notes-retrieval"><img src="https://agentmods.dev/badge/skills/vasilyu1983/ai-agents-public/docs-notes-retrieval.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 | $0.00040 | $0.03342 |
| Opus 5.5 | $0.00016 | $0.01337 |
| Sonnet 5.5 | $0.00008 | $0.00668 |
| Haiku 4.5 | $0.00004 | $0.00334 |
Grade A, and why
docs-notes-retrieval 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 20d 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 — 225 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Notes Retrieval
Quick Start — Concrete Commands
Three common scenarios using the scripts in scripts/.
Scenario 1: Vault inventory
Before indexing or packaging, understand what is in the vault.
# Full inventory as JSON — one record per note with title, frontmatter, wikilinks, tags, word count, mtime
python scripts/scan_vault.py inventory /path/to/vault > vault-inventory.json
# Tag summary sorted by note count
python scripts/scan_vault.py tags /path/to/vault
# CSV for spreadsheet review
python scripts/scan_vault.py inventory /path/to/vault --format csv > vault-inventory.csv
Scenario 2: Packaged context for an LLM session
Build a markdown bundle ready to paste into a Claude or GPT session.
# Keyword search — include all notes matching "weekly review", budget 40k chars
python scripts/build_context_pack.py /path/to/vault \
--query "weekly review" \
--max-chars 40000 > context-pack.md
# Specific notes with heading-level chunking
python scripts/build_context_pack.py /path/to/vault \
--notes "Projects/Alpha.md" "Projects/Beta.md" \
--chunk-strategy heading \
--max-chars 60000 > project-alpha-pack.md
# Most recent notes first, paragraph chunking, written to file
python scripts/build_context_pack.py /path/to/vault \
--query "architecture decision" \
--order-by recency \
--chunk-strategy paragraph \
--out session-context.md
# Filter on status before recency: drop superseded and archived notes
python scripts/build_context_pack.py /path/to/vault \
--query "pricing" --exclude-status superseded archived --order-by recency
The pack keeps conflicting notes side by side under a conflict block (path, status, mtime for each) when they declare conflicts_with: [[Other Note]] in frontmatter or share a title under different paths; a group is included or omitted whole. It does not detect contradictions in prose, so still read for them. The footer lists wikilinks in included notes that resolve to no file.
What ships with it
11 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- agents/openai.yaml 349 B
- data/sources.json 4.0 KB
- learnings.consolidated.md 596 B
- learnings.md 1.5 KB
- references/ai-curated-wiki-pattern.md 7.0 KB
- references/context-packaging-patterns.md 6.9 KB
- references/obsidian-and-local-vaults.md 5.2 KB
- references/retrieval-anti-patterns.md 8.7 KB
- scripts/build_context_pack.py 27 KB runs code
- scripts/scan_vault.py 16 KB runs code
- scripts/test_vault_regressions.py 4.3 KB runs code
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.
- 20d ago Changed · -30 lines c7a8eb77ad3c
- 1mo ago Changed · +5 lines f52de87c8cc2
- 1mo ago First seen · 250 lines · 40 tokens per session scan A fe656c163844
docs-notes-retrieval is a skill published in the GitHub repository vasilyu1983/AI-Agents-public (101 stars, last pushed 9d ago), licensed MIT. It adds 40 tokens to every session and 3,342 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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