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 aakarim/OpenLore --skill openlore-housekeepinggit clone --depth 1 https://github.com/aakarim/OpenLoreWrote 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/aakarim/openlore/openlore-housekeeping)<a href="https://agentmods.dev/skills/aakarim/openlore/openlore-housekeeping"><img src="https://agentmods.dev/badge/skills/aakarim/openlore/openlore-housekeeping.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 5.1 | $0.00048 | $0.00706 |
| Opus 5 | $0.00024 | $0.00353 |
| Sonnet 5 | $0.00010 | $0.00141 |
| Haiku 4.5 | $0.00005 | $0.00071 |
Grade A, and why
openlore-housekeeping 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 7d 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 — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenLore Housekeeping
Keep a shared knowledge base healthy. Run each check below, collect findings,
and publish one report. Requires the openlore skill (server access via
$OPENLORE_SSH).
1. Find stale documents
Documents carry frontmatter. Use lore meta to list paths with dates, then
flag old ones:
ssh $OPENLORE_SSH "lore meta /docs | jq -r 'select(.updated != null) | [.updated, .path] | @tsv' | sort"
Flag anything older than the agreed threshold (default: 90 days). Also flag documents with no frontmatter date at all:
ssh $OPENLORE_SSH "lore meta /docs | jq -r 'select(.updated == null) | .path'"
2. Find broken internal links
Extract relative Markdown links and check each target exists:
ssh $OPENLORE_SSH "grep -rho ']([^)h][^)]*)' /docs | tr -d ']()' | sort -u"
For each path, test it: ssh $OPENLORE_SSH "test -e /docs/<target> || echo missing: <target>".
3. Check the publish inboxes
Items published into an inbox wait for a human to move them into the docset. List what is waiting and how old it is:
ssh $OPENLORE_SSH "find / -type f | grep '/inbox/' | xargs -I{} stat {}"
Flag inbox items older than 7 days: they are stuck and need a human decision.
4. Check trajectory freshness
If the server has a /trajectories docset, confirm recent agent runs are
being synced:
ssh $OPENLORE_SSH "ls -t /trajectories | head -5"
Compare with local ~/.headlong/trajectories/. Sync any completed run that is
missing (see the openlore skill for the sync procedure).
5. Check skill coverage
If the server hosts a skills collection, verify every skill directory has a
SKILL.md:
ssh $OPENLORE_SSH "ls -1 /skills | while read -r d; do test -e /skills/\$d/SKILL.md || echo missing: \$d; done"
6. Publish the report
Write one Markdown report with a section per check and only actionable findings. Publish it; the inbox keeps reports out of the docset until a human accepts them:
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.
- 7d ago First seen · 86 lines · 48 tokens per session scan A 2653fe7f9fd2
openlore-housekeeping is a skill published in the GitHub repository aakarim/OpenLore (88 stars, last pushed 2d ago), licensed MIT. It adds 48 tokens to every session and 706 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 2026-08-30.
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