lorekeeper-protocol

A session-start and memory-management procedure for Lorekeeper, a persistent store of information used by an agent.

In plain words
What is it for?
Use it at the start of each session and when the work changes topic or needs memory cleanup and health checks.
Why use it?
It helps the agent recover relevant past decisions, follow connected memories, remove dead ends, and reduce duplicated or conflicting knowledge.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/jessinra/lorekeeper/lorekeeper-protocol
Any agent
npx skills add Jessinra/Lorekeeper --skill lorekeeper-protocol
Clone the repo
git clone --depth 1 https://github.com/Jessinra/Lorekeeper

Made for: Claude Code, Codex.

Per session 57 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,104 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00057 $0.01104
Opus 5 $0.00028 $0.00552
Sonnet 5 $0.00011 $0.00221
Haiku 4.5 $0.00006 $0.00110

Measured 2d ago against content hash 90b31fedf316, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

lorekeeper-protocol 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.

src/lorekeeper/assets/skills/lorekeeper-protocol/SKILL.md · 93 lines

How it starts

The opening of the file, as written. The whole thing — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Lorekeeper Protocol

Follow this protocol every session to keep your memory store accurate, healthy, and growing.

Inspired by MRAgent (Ji et al., NUS, ICML 2026): memory is reconstructed, not retrieved. Actively explore the memory graph — search, reason, follow links, prune dead ends, repeat.

Phase 1 — Session Start

Trigger: Beginning of every session, before any substantive work.

  1. Identify the session topic (1–3 keywords).
  2. Search: lore_search({ query: "<topic>", min_score: 0.15, include_links: true })
  3. Read all returned memories — decisions, constraints, patterns.
  4. Provide feedback: lore_update({ memory_feedback: [{ id: "<id>", useful: true/false }] })
  5. If fewer than 3 results, run a broader fallback search.

Do not skip. Working without context causes duplicate inserts and contradictory decisions.

Phase 1.5 — Active Memory Reconstruction

Trigger: After Phase 1, before acting on retrieved memories.

Run the reconstruction loop until the surface is exhausted:

1. READ top results. 2. REASON about what's still unknown. 3. TRAVERSE links from high-value memories. 4. SEARCH for inferred cues. 5. PRUNE dead ends. 6. REPEAT. BREAK when 2 consecutive iterations return no novel results.

Rule: If you've read a memory and still have open questions, run another search — don't settle for the first batch.

Phase 2 — Mid-Session (Topic Shift)

Trigger: Conversation shifts to a new domain, subsystem, or question.

  1. Run a fresh lore_search for the new topic.
  2. Follow links from already-known relevant memories.
  3. Provide feedback. If connected to explored topic, run reconstruction at reduced depth (1–2 iterations).

Rule: If you're reasoning about something you haven't searched for, search first.

Phase 3 — Session End

Trigger: End of every session.

  1. Insert new memories for decisions, root causes, architecture insights, user corrections, patterns.
  2. Store with cues in mind: insert explicit references links to related memories.
  3. Reflect: lore_reflect({ session_id, summary, topic, task_type, what_was_done, decisions, lessons_learnt, good_patterns, factual_discoveries, memory_ids })

Read the full file on GitHub · 93 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

  1. 2d ago First seen · 93 lines · 57 tokens per session scan A 90b31fedf316

Subscribe to this mod's changes

lorekeeper-protocol is a skill published in the GitHub repository Jessinra/Lorekeeper (4 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 57 tokens to every session and 1,104 once invoked, about $0.0003 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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