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/smixs/iva-agent/docsnpx skills add smixs/iva-agent --skill docsgit clone --depth 1 https://github.com/smixs/iva-agentWhat 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 | $0.00089 | $0.04805 |
| Opus 5 | $0.00044 | $0.02403 |
| Sonnet 5 | $0.00018 | $0.00961 |
| Haiku 4.5 | $0.00009 | $0.00481 |
Grade A, and why
autograph 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 2d 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.
No hardcoded domains, types, or paths. The agent discovers structure from data, builds a schema, then enforces it. All scripts share `common.py`. Zero external dependencies (stdlib only, API calls via urllib). This is a copy
89% identical to autograph — 245 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.
How it starts
The opening of the file, as written. The whole thing — 375 lines — stays where its author put it; the contents beside it link to each section on GitHub.
autograph — typed vault engine
One schema. One graph. Works on any vault.
Overview
No hardcoded domains, types, or paths. The agent discovers structure from data, builds a schema, then enforces it. All scripts share common.py. Zero external dependencies (stdlib only, API calls via urllib).
Quick Reference: 6 Workflows
| Workflow | When to use | Entry point |
|---|---|---|
| BOOTSTRAP | New vault / after import / first setup | discover.py → enforce.py → graph.py health |
| HEALTH | Daily maintenance / on request | graph.py health → fix → moc → decay |
| CREATE / UPDATE | New knowledge card, or new info about an existing one | search.py dedup → ADD/UPDATE/SUPERSEDE → link → touch |
| SEARCH & LINK | Find info + strengthen connections | Hub → links → target; graph.py orphans → connect |
| ORCHESTRATE | Automated multi-agent workflows (no API keys) | orchestrate.py health|bootstrap |
| DAILY → CARDS | Turn a day's raw notes into linked cards | daily.py extract → dedup-first process → link |
Workflow 1: BOOTSTRAP (raw vault → structured graph)
When to use: New vault, bulk import, first setup. Run once, then switch to HEALTH.
Full guide: references/bootstrap-workflow.md
Summary (10 phases)
- Discover:
uv run scripts/autograph/discover.py <vault-dir> --verbose > /tmp/discovery.json - Generate schema: Script baseline (
generate_schema.py) + agent swarm (swarm_prepare.py→ Wave 1 haiku →swarm_reduce.py→ Wave 2 sonnet). NEVER skip the swarm. - Review: Human approves schema. Never auto-apply.
- Bootstrap + Enforce:
engine.py init+enforce.py --apply - Link cleanup:
link_cleanup.py --apply(before enrichment) - Tag enrich:
enrich.py tags --apply(via OpenRouter API) - Deduplicate:
dedup.py --apply(before link enrichment) - Link enrich:
enrich.py swarm-links --apply(always swarm-links, never links) - MOC generation:
moc.py generate - Verify:
graph.py health+enforce.py→ target 90+/100
What ships with it
6 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.
- 2d ago First seen · 375 lines · 89 tokens per session scan A 2f645fdb36ee
autograph is a skill published in the GitHub repository smixs/iva-agent (189 stars, last pushed 6d ago), licensed MIT. It adds 89 tokens to every session and 4,805 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 89% identical to autograph, differing in 245 lines, and is treated as a copy.
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