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 Jessinra/Lorekeeper --skill lorekeeper-reconcilegit clone --depth 1 https://github.com/Jessinra/LorekeeperWrote 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/jessinra/lorekeeper/lorekeeper-reconcile)<a href="https://agentmods.dev/skills/jessinra/lorekeeper/lorekeeper-reconcile"><img src="https://agentmods.dev/badge/skills/jessinra/lorekeeper/lorekeeper-reconcile/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/jessinra/lorekeeper/lorekeeper-reconcile"><img src="https://agentmods.dev/badge/skills/jessinra/lorekeeper/lorekeeper-reconcile.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00072 | $0.01805 |
| Opus 5.5 | $0.00029 | $0.00722 |
| Sonnet 5.5 | $0.00014 | $0.00361 |
| Haiku 4.5 | $0.00007 | $0.00180 |
Grade A, and why
lorekeeper-reconcile 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 1mo 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 — 165 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Lorekeeper Reconciliation Agent
Verify stored memories against authoritative sources to identify incorrect, outdated, or inconsistent facts. Update confidence scores, correct the knowledge base, and fill knowledge gaps with new memories when reference materials contain information not yet captured.
Verification Methods
Choose whichever method(s) suit the memory being verified. Combine multiple methods when a single one is insufficient.
| Method | Tools | Use When |
|---|---|---|
| Source verification | web_extract, read_file | User provided URLs/files/docs to check against |
| Documentation cross-ref | web_search, read_file | Corroborating against existing documentation |
| Codebase verification | search_files, terminal | Technical facts (APIs, error codes, service flows) |
| Internal consistency | lore_search |
Checking for contradictions/divergence between memories |
| Inference | Agent reasoning | No authoritative source available |
Workflow
Step 1: Gather and Scope
| Input Type | Action |
|---|---|
| URL(s) | web_extract → save content to .docs-cache/reconcile-{slug}.md |
| Local files | Read directly via read_file |
| Topic/domain request | Skip to Step 2 |
Step 2: Search Lorekeeper
Extract key terms from the reference materials or topic request — domain terms, entity names, process names — and run multiple lore_search queries to build a verification queue of unique memories.
lore_search({ query: "<natural language query>", min_score: 0.1 })
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.
- 1mo ago First seen · 165 lines · 72 tokens per session scan A 7ac7f02930f7
lorekeeper-reconcile is a skill published in the GitHub repository Jessinra/Lorekeeper (5 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 72 tokens to every session and 1,805 once invoked, about $0.0003 per session on Opus 5.5. 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
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hindsight-local
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bot-handoff
Keep a durable record of work passed between Bots in the shared Hindsight memory bank. Use when handing work to another Bot, when picking up work another Bot started, and when a finding would help other Bots, including Bots that are not part of the current conversation.
memory-context
Load relevant long-term memory from Hindsight before starting work. Use at the start of every task or request, before planning or answering, and whenever the user mentions people, projects, decisions, preferences or anything done before.
routine-memory
Carry state between runs of a scheduled routine using Hindsight memory. Use when creating or editing a routine, to write the recall and retain steps into the routine's own instructions, and at the start and end of every scheduled or event-triggered routine run.
memory-retain
Save what was learned to Hindsight long-term memory. Use when a task finishes, when the user states a fact, decision or preference, and when you discover something a later run or another Bot would need.