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/nel-neru/libraium/source-command-curate-reviewnpx skills add nel-neru/LibrAIum --skill source-command-curate-reviewgit clone --depth 1 https://github.com/nel-neru/LibrAIumWrote 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/nel-neru/libraium/source-command-curate-review)<a href="https://agentmods.dev/skills/nel-neru/libraium/source-command-curate-review"><img src="https://agentmods.dev/badge/skills/nel-neru/libraium/source-command-curate-review.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00027 | $0.00906 |
| Opus 5 | $0.00014 | $0.00453 |
| Sonnet 5 | $0.00005 | $0.00181 |
| Haiku 4.5 | $0.00003 | $0.00091 |
Grade A, and why
source-command-curate-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 4d 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 — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
source-command-curate-review
Use this skill when the user asks to run the migrated source command curate-review.
Command Template
Audit the LibrAIum library (data/entries/) for curation debt. This is a review of the content, not the code.
1. Baseline
Run the structural validator first — a broken file invalidates the rest of the audit:
node scripts/validate-data.mjs --data-dir data
Report and fix any structural failures before continuing.
2. Audit checks
Run the deterministic report first — it computes checks (a), (c) and (d) in one offline pass:
node scripts/curation-report.mjs # human-readable; --json for scripting
Interpret its sections, don't just paste them:
a) Freshness — entries in the 30d+/90d+/missing buckets have unrefreshed stars/push dates. Fix via /refresh-metadata (dry-run first) or node scripts/refresh-metadata.mjs --only <entry-id> --write.
c) Tag taxonomy drift — singleton tags are rename candidates ONLY when a near-synonym candidates pair names the same concept (vector-db ~ vectordb); genuinely new singletons are fine — judge each one, don't mass-delete. Apply approved renames atomically with node scripts/rename-tag.mjs <old> <new> [--merge] (dry-run first) — never by hand-editing N files.
d) Succession — UNCOVERED stale/archived entries are shelf holes: no active same-category entry shares a tag (the suggest_alternatives rule in src-tauri/src/search.rs / alternativesFor in mcp-server/lib/suggest.js). Research a replacement or add the succession note. Also flag stale entries whose notes don't name what superseded them.
Then do the one judgment-only check the report cannot compute:
b) Placeholder Reception — a ## Reception section that is missing, empty, or contains only bare stubs (a lone - bullet, "TODO", an unsourced claim, or a bullet that merely restates the summary/README). Reception — synthesized third-party signal with a source per claim — is the library's primary content layer; flag every entry whose Reception is absent or uncited. (Entries the owner has genuinely used may also keep a firsthand ## Personal Notes; that is a bonus, never a substitute for Reception.)
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.
- 4d ago First seen · 66 lines · 27 tokens per session scan A 433895745594
source-command-curate-review is a skill published in the GitHub repository nel-neru/LibrAIum (0 stars, last pushed yesterday), licensed MIT. It adds 27 tokens to every session and 906 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.
Other skills, from other repositories
vault
Search, read, write, and manage files in the Kept conversation vault. Use when the user asks about past conversations, wants to save notes, needs to find specific content, or wants to organize their vault.
seller-research
Use when researching a merchant, storefront, marketplace seller, or merchant of record for a buying decision, especially when identity, refund terms, fulfillment, counterfeit risk, domain history, or independent buyer outcomes are uncertain.
shodh-memory
Persistent memory system for AI agents. Use this skill to remember context across conversations, recall relevant information, and build long-term knowledge. Activate when you need to store decisions, learnings, errors, or context that should persist beyond the current session.
anyr
Use when reading, searching, creating, or updating Anytype documents (objects, spaces, types, properties, files, chats) from the command line with the configured anyr CLI, including JSON output patterns for scripting.
vault-for-llm
Connect OpenClaw to Vault Agent Memory as a local-first governed project memory layer. Search first, then bounded-read cited source ranges; propose new memories as candidates instead of writing directly into active memory.
skills
Your next session starts cold. No memory of what you built, what broke, what you decided. Every memory you write is a gift to that future session. The richer the memory, the less time re-learning.