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 commands/mnott/pai/zettelgit clone --depth 1 https://github.com/mnott/PAIWhat 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 | $0.00000 | $0.01317 |
| Opus 5 | $0.00000 | $0.00659 |
| Sonnet 5 | $0.00000 | $0.00263 |
| Haiku 4.5 | $0.00000 | $0.00132 |
Grade A, and why
zettel 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 — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.
pai zettel
Zettelkasten intelligence: explore, surprise, converse, themes, health, suggest
Synopsis
pai zettel <subcommand> [options]
Subcommands
| Command | Description |
|---|---|
pai zettel explore <note> |
Follow link chains from a starting note |
pai zettel health |
Vault structural health audit: dead links, orphans, connectivity |
pai zettel surprise <note> |
Find semantically similar but graph-distant notes (surprising connections) |
pai zettel suggest <note> |
Suggest new wikilink connections for a note |
pai zettel converse <question> |
Ask the vault a question and get a synthesis prompt with relevant notes |
pai zettel themes |
Detect emerging theme clusters in recently edited notes |
pai zettel explore
Follow link chains from a starting note
Arguments
| Argument | Kind |
|---|---|
<note> |
required |
Options
| Option | Description | Default |
|---|---|---|
--depth <n> |
Maximum traversal depth (1-10) | 3 |
--direction <d> |
Link direction: forward | backward | both | both |
--mode <m> |
Edge mode: sequential | associative | all | all |
pai zettel health
Vault structural health audit: dead links, orphans, connectivity
Options
| Option | Description | Default |
|---|---|---|
--scope <s> |
Scope: full | recent | project | full |
--project <path> |
Project path prefix (requires --scope project) | |
--days <n> |
Look-back window in days (requires --scope recent) | 30 |
--include <types> |
Comma-separated subset: dead_links,orphans,disconnected,low_connectivity |
pai zettel surprise
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 · 152 lines · 0 tokens per session scan A f54c4b8c801c
zettel is a command published in the GitHub repository mnott/PAI (45 stars, last pushed 8d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,317 tokens. 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 2026-08-30.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.