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/letrplb/second-brain/connectnpx skills add letrplB/second-brain --skill connectgit clone --depth 1 https://github.com/letrplB/second-brainWhat 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 | $0.00032 | $0.01557 |
| Opus 5 | $0.00016 | $0.00779 |
| Sonnet 5 | $0.00006 | $0.00311 |
| Haiku 4.5 | $0.00003 | $0.00156 |
Grade A, and why
connect 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 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.
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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/connect
Intent. Take a note that exists but is poorly connected, and integrate it into the graph. Add inline [[wikilinks]] in its body where genuine connections exist; add inverse links from connected notes back to it; update MOC membership both ways.
When to invoke
- Just after
/extract(composed by/learn) - When you realise an old claim should link to newly-added work (use
--bulkwith a date-filtered glob) - When
/auditflags a note as orphaned
Behaviour
Forward pass — add links from this note to others
- Read the target note: title, description, frontmatter, body.
- Discover candidates via two channels in parallel:
- Semantic search:
qmd querywithintent= the note's description, typeslexandvec. Return top ~30 candidates. - Frontmatter walk: read the note's
tags,methods,topics,supports,contradictsarrays. Walk those notes; collect their tags + neighbours (one hop).
- Semantic search:
- Filter candidates. A connection is genuine when:
- The target note's claim requires, follows from, qualifies, contradicts, or exemplifies the candidate
- Or: the candidate is a method used in the target's evidence chain
- Or: the candidate is a paper sourcing the target
- Not genuine: "they share a topic", "they sound related", "they were co-extracted from the same source" (sibling-only)
- Add inline
[[wikilinks]]in the body where genuine connections fit, with surrounding prose explaining the relationship. Avoid bare-link lists — context phrases prefix every link. - Update structured frontmatter where the connection has a typed slot:
supports,contradicts,methodsarrays gain entries.
Backward pass — add links from others to this note
- For each connected note from step 4: read it. Decide whether the inverse link belongs in its body. If yes, add it (with surrounding prose).
- Update structured frontmatter on the connected notes if applicable (e.g. paper notes get the new claim in their
claims:list — though/extractmay have done this already).
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 · 83 lines · 32 tokens per session scan A 53c9a806eab4
connect is a skill published in the GitHub repository letrplB/second-brain (1 stars, last pushed 3mo ago), licensed MIT. It adds 32 tokens to every session and 1,557 once invoked, about $0.0002 per session on Opus 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.
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