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 dodo-reach/hermes-link-curator --skill skill-obsidiangit clone --depth 1 https://github.com/dodo-reach/hermes-link-curatorWrote 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/dodo-reach/hermes-link-curator/skill-obsidian)<a href="https://agentmods.dev/skills/dodo-reach/hermes-link-curator/skill-obsidian"><img src="https://agentmods.dev/badge/skills/dodo-reach/hermes-link-curator/skill-obsidian/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/dodo-reach/hermes-link-curator/skill-obsidian"><img src="https://agentmods.dev/badge/skills/dodo-reach/hermes-link-curator/skill-obsidian.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 | $0.00013 | $0.02875 |
| Opus 5 | $0.00006 | $0.01437 |
| Sonnet 5 | $0.00003 | $0.00575 |
| Haiku 4.5 | $0.00001 | $0.00287 |
Grade A, and why
obsidian scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
TAB=$(curl -s -X POST http://localhost:9377/tabs \ How it starts
The opening of the file, as written. The whole thing — 237 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Obsidian Vault — Link Curator Skill
Behavior — do not summarize, archive
When the user sends a URL or asks to save/archive something: archive it immediately, do not summarize. Your job is that of a librarian: receive → process → file. Not a chatbot to give impressions.
Do NOT respond with a summary of the content unless the user explicitly asks for one. Archive first, then say only "Salvato." (or the error, if any).
Vault
<profile-dir>/vault/
Entry format
### [Title]
- **URL**: https://...
- **Type**: `github` | `x-post` | `article` | `tool` | `video` | `paper` | `other`
- **Tags**: #tag1 #tag2 #tag3
- **Added**: YYYY-MM-DD
- **Summary**: What is this? Why does it matter? What do you do with it?
---
[next entry]
--- between every entry. No --- = merged entry in dashboard. Parse splits on \n---\n.
Save workflow
Use save_entry.py — atomic read+patch, never overwrites INDEX.md.
python3 <profile-dir>/skills/note-taking/obsidian/scripts/save_entry.py \
--url "https://..." \
--title "Entry Title" \
--type "article" \
--tags "ai dev-tools" \
--added "2026-06-04" \
--summary "What it is and why it matters."
The script:
- Reads INDEX.md in memory (never overwrites without reading)
- Finds the first
---separator - Inserts the new entry AFTER the first
---separator (each entry gets its own chunk) - Also appends to the daily note
vault/YYYY-MM-DD.md - Runs validate.py automatically
⚠️ Prepend bug (fixed): Old versions of
save_entry.pyinserted new entries BETWEEN the header and the first---. When two entries from the same day were saved consecutively, they ended up in the same chunk. The dashboard parser usesre.findall(r'\*\*URL\*\*', chunk)[0]— only the first URL per chunk was read. Symptoms: entry appears in INDEX.md but not in dashboard (or dashboard shows fewer entries than vault count). Fix was to changelines[:sep_idx]→lines[:sep_idx+1]so insertion happens AFTER the separator, not before. Runrebuild_index.pyto fix retroactively affected vaults.
What ships with it
2 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.
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.
- 12d ago First seen · 237 lines · 13 tokens per session scan A 4210f8e1b6d8
obsidian is a skill published in the GitHub repository dodo-reach/hermes-link-curator (136 stars, last pushed 3mo ago), licensed MIT. It adds 13 tokens to every session and 2,875 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
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mnemosyne
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mnemosyne-memory-override
Hard rule override that forces Mnemosyne for all durable memory storage. The legacy memory tool is DEPRECATED for user preferences, credentials, and project conventions. Use memory ONLY for ephemeral session state.
knowledge-ingestion
A skill for saving links, social posts, videos, podcasts, screenshots, PDFs, local files, or text into an Obsidian knowledge base, a personal collection of searchable notes. The ingestion tools analyse and format the material for storage.
personal-knowledge-ingestion
A skill for saving links, videos, social posts, local files, screenshots, PDFs, or text into an Obsidian vault, a folder used for personal notes and knowledge. It uses connected knowledge tools to process and format the saved item.
hunt-fastapi
Hunt FastAPI-specific vulnerabilities: dependency injection gaps, Pydantic coercion, and OpenAPI mining.