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/laat/mor/notes-reviewnpx skills add laat/mor --skill notes-reviewgit clone --depth 1 https://github.com/laat/morWhat 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 | $0.00026 | $0.00886 |
| Opus 5 | $0.00013 | $0.00443 |
| Sonnet 5 | $0.00005 | $0.00177 |
| Haiku 4.5 | $0.00003 | $0.00089 |
Grade A, and why
notes-review 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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Audit the note store and produce a structured report of proposed changes. Do NOT apply changes — present proposals for user approval, then use /notes-consolidate or individual notes_update/notes_remove calls to execute approved changes.
Examples
/notes-review
/notes-review tag hygiene
/notes-review duplicates
/notes-review stale
Steps
1. Gather the full picture
notes_listwith a high limit to get all notes- Aggregate tag and type distributions from the full list (count occurrences across all notes)
- Note total count, tag distribution, type distribution
Success criteria: You have a complete inventory of all notes with their metadata.
2. Read and classify
Read notes in batches using notes_read (batch IDs). For each note, check:
| Issue | What to look for |
|---|---|
| Duplicates | Notes with very similar titles or overlapping content |
| Stale | Outdated information, references to things that may have changed |
| Tag inconsistencies | Similar tags that should be unified (e.g. "fs" vs "filesystem"), unused tags on single notes |
| Type mismatches | Notes whose type doesn't match their content (see type guidelines below) |
| Broken links | mor: links pointing to non-existent notes |
| Missing links | Notes that reference the same concepts but aren't cross-linked |
| Empty/thin | Notes with very little content that could be merged into related notes |
| Title quality | Vague titles that don't help with search |
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 · 90 lines · 26 tokens per session scan A a8069b0954f2
notes-review is a skill published in the GitHub repository laat/mor (2 stars, last pushed 2d ago), licensed MIT. It adds 26 tokens to every session and 886 once invoked, about $0.0001 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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