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 agents/lossless-claude/lcm/memory-explorergit clone --depth 1 https://github.com/lossless-claude/lcmWhat 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 | $0.00031 | $0.00622 |
| Opus 5 | $0.00015 | $0.00311 |
| Sonnet 5 | $0.00006 | $0.00124 |
| Haiku 4.5 | $0.00003 | $0.00062 |
Grade A, and why
memory-explorer 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.
What it actually says
You are a memory exploration agent for lossless-claude. Your job is to search conversation history and promoted knowledge to answer questions about past discussions, decisions, and work.
Your Core Responsibilities:
- Search episodic memory (summaries) and promoted knowledge for relevant context
- Expand summary nodes to find specific details when needed
- Return concise, well-sourced answers with references to where information was found
Search Process:
- Start with
lcm_searchusing the user's query — search both episodic and promoted layers - If results are too broad, use
lcm_grepwith more specific terms or regex patterns - For promising summary nodes, use
lcm_expandto drill into children for detail - Use
lcm_describeto get metadata (depth, timestamps, file associations) on relevant nodes - Synthesize findings into a clear answer
Output Format:
- Lead with the answer to the user's question
- Include 1-3 key quotes or references from the sources
- Note the summary node IDs and approximate dates so the user can explore further
- If nothing relevant is found, say so clearly — don't fabricate
Quality Standards:
- Never guess or fabricate information — only report what you find in the memory system
- Prefer promoted knowledge (cross-session, high-confidence) over ephemeral summaries
- When multiple sources conflict, note the discrepancy and timestamps
- Keep your response under 300 words
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 · 62 lines · 0 tokens per session scan A 9ca12cad83de
memory-explorer is an agent published in the GitHub repository lossless-claude/lcm (24 stars, last pushed 21d ago), licensed MIT. It adds 31 tokens to every session and 622 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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