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autograph — typed vault engine · smixs | DecimalAI

documentationby smixs

autograph — typed vault engine

smixs/autograph

Source smixs/agent-second-brain ↗License MIT

Schema-as-code enforcement for any Obsidian vault. Zero hardcoded domains.

SkillScore86Maintained

Automatic

Knowledge Management pack

Last verified 8/21/2026

What it changes

Passed 16 of 19 test cases with the skill, and 4 of 19 without it.

Without skill23%

With skill86%

Checks it passed that the model alone missed

Rejects the deprecated links subcommand.
Prescribes using the swarm-links subcommand.
Specifies a decay rate of 0.005 for contact notes.

and 16 more in the full report

14 fixed5 passed either way3 still failing0 broke

Pass-rate lift: +64 pp
Tokens: +139%
Agent turns: 0%
Response time: -59%

Model gemini-3.6-flashMeasured 8/21/2026v119 of 22 cases passed with skill · 19 comparable

Tokens, turns and time describe resource use, not a dollar price.

Use this skill

Save it into your project's skills folder. Claude Code picks it up in its next session.

curl -fsSL --create-dirs -o .claude/skills/smixs-autograph/SKILL.md https://app.decimal.ai/s/smixs-autograph/SKILL.md

Want it pinned and updatable? pip install "decimalai>=0.15", then decimalai skills add smixs-autograph, and start Claude Code with claude --plugin-dir "$(git rev-parse --show-toplevel)/.agents"

1 · One-time — install the CLI (docs ↗)

pip install "decimalai>=0.15"

2 · Get the skill — writes .agents/skills/smixs-autograph/ and pins it in .decimal/skills.lock

decimalai skills add smixs-autograph

No CLI? Get the same file — curl · raw file

curl -fsSL --create-dirs -o .claude/skills/smixs-autograph/SKILL.md https://app.decimal.ai/s/smixs-autograph/SKILL.md

Raw file: /s/smixs-autograph/SKILL.md ↗ · machine-readable summary at /s/smixs-autograph.json ↗

Safety checks: 3 of 3 passed

Code scan CleanIntent PassedContent Clean

See it in action

One of 14 test cases the skill fixed. Same model, same prompt, with and without the skill.

1 of 14

Prompt

When running `enrich.py swarm-links` without explicit model arguments, which model is selected by default for batch link analysis?

What was checked, without and with the skill
Checked	Without skill	With skill
Identifies google/gemini-2.0-flash-001 as the default model for swarm-links enrichment.	Missed	Passed

case-17 · gemini-3.6-flash · 8/21/2026 · answers are capped and redacted

What's inside

The instructions your model reads when the skill loads.

SKILL.md324 lines19 filesincludes scripts

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: 5 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	New knowledge card	Schema lookup → write file → 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`

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/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

Critical Rules

Track record

Benchmark

16 / 19

test cases passed, vs 4 / 19 without

Adoption

Users: 0
Times used: 0

Safety and source details

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 8/3/2026

View 15 scanner checks

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

smixs / agent-second-brain

vault/.claude/skills/autograph/SKILL.md

View on GitHub ↗

License MITImported 8/3/2026Version v1Bundled 18 files · scripts

More skills from the same source and nearby in the registry, with their headline benchmark lift.

Ready to supercharge your AI agents?

See it in action

What's inside

autograph — typed vault engine

Overview

Quick Reference: 5 Workflows

Workflow 1: BOOTSTRAP (raw vault → structured graph)

Summary (10 phases)

Critical Rules

Track record

Benchmark

Adoption

SkillSafety

Source

Related skills