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 mycelium-hq/ai-brain-starter --skill second-brain-mappinggit clone --depth 1 https://github.com/mycelium-hq/ai-brain-starterWrote 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/mycelium-hq/ai-brain-starter/second-brain-mapping)<a href="https://agentmods.dev/skills/mycelium-hq/ai-brain-starter/second-brain-mapping"><img src="https://agentmods.dev/badge/skills/mycelium-hq/ai-brain-starter/second-brain-mapping/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/mycelium-hq/ai-brain-starter/second-brain-mapping"><img src="https://agentmods.dev/badge/skills/mycelium-hq/ai-brain-starter/second-brain-mapping.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 | $0.00116 | $0.04501 |
| Opus 5.5 | $0.00046 | $0.01800 |
| Sonnet 5.5 | $0.00023 | $0.00900 |
| Haiku 4.5 | $0.00012 | $0.00450 |
Grade A, and why
second-brain-mapping 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 1mo 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 — 350 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/second-brain-mapping
{SKILL_DIR}= this skill's own folder (locally: the directory this SKILL.md lives in; a served brain substitutes the real absolute path before you read this). Shared starter files live at the repo root two levels up:{SKILL_DIR}/../... If a path does not resolve, name the missing file and stop — never guess another location.
Your vault is a database. This skill makes it queryable.
What it does
| Phase | Tool | LLM cost | Always runs? |
|---|---|---|---|
| 1 | vault-metadata-extract.py (dispatcher → type-specific extractors) |
0 tokens | Yes |
| 2 | /graphify (optional) |
~100k–1M tokens | No — asks first |
| 2b | graphify_report_sanitize.py --check — keeps the graph report from flooding the vault's graph view |
0 tokens | Yes, whenever a report exists |
| 3 | Wikilink gaps + interactive apply | ~5k tokens | If graph exists |
| 4 | vault-insight-engine.py — cross-type surprise finder |
0 tokens | Yes |
Phases 1, 2b and 4 are free. Phase 2 is expensive and opt-in. Phase 3 needs interactive approval so it skips gracefully in non-TTY contexts. 2b runs even when 2 is skipped — a report left by an earlier run is the thing it protects against.
Setup
Run once after cloning ai-brain-starter:
/setup-vault-types
Interactive wizard asks which doc types you have (journal, book, article, meeting, person, project, podcast, client, etc.) and installs the matching extractors. You can add custom types later by editing scripts/extractors/schemas.yaml or running /setup-vault-types --add <name>.
Usage
/second-brain-mapping # full pipeline
/second-brain-mapping --metadata-only # skip graphify + wikilinks, keep insights
/second-brain-mapping --insights-only # only run Phase 4 on existing metadata
/second-brain-mapping --type book # only process files with `type: book`
/second-brain-mapping --dry-run # preview without writes
/second-brain-mapping --sample # preview 1 file per configured type (cold-start safe)
/second-brain-mapping --sample 3 # preview 3 files per configured type
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.
- 1mo ago First seen · 350 lines · 116 tokens per session scan A ff119a46ead1
second-brain-mapping is a skill published in the GitHub repository mycelium-hq/ai-brain-starter (48 stars, last pushed today), licensed MIT. It adds 116 tokens to every session and 4,501 once invoked, about $0.0005 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 2026-08-31.
Other skills, from other repositories
Promote
Take a slice of the current conversation and promote it to a durable vault artifact — concept note, project update, person profile, or doctrine entry. Pairs with /close. /close writes the daily note (transient outcome record); /promote elevates specific insights to permanent vault content the framework can refer back…
open
Boot the session, load context from the vault, and surface what matters.
capsule-compact
Compact a long capsule chain. Walks parentcapsuleid backward from a head capsule; if chain >= 5, summarizes oldest 3 into a chain-summary capsule. Manual invocation.
nightly
Canonical seven-leg nightly close-parity protocol. Eleven independently evidenced checkpoints cover synthesis, reconciliation, context hygiene, sweeps, heat, digest, runtime health, cognitive state, ledger capture/review, and vault sync.
close
Commit the session to durable vault memory and prepare a clean resume point.
context-capsule
The capsule verb, invoked explicitly — reconcile from the live memory, write a resume-ready capsule, then stop. Mid-session checkpoint or completion capsule; a rolling best-effort version of the same write also runs automatically on every Stop event via daemons/stop-capsule-writer.mjs.