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 LH8PPL/core-memory-kit --skill memory-searchgit clone --depth 1 https://github.com/LH8PPL/core-memory-kitWrote 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/lh8ppl/core-memory-kit/memory-search)<a href="https://agentmods.dev/skills/lh8ppl/core-memory-kit/memory-search"><img src="https://agentmods.dev/badge/skills/lh8ppl/core-memory-kit/memory-search/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/lh8ppl/core-memory-kit/memory-search"><img src="https://agentmods.dev/badge/skills/lh8ppl/core-memory-kit/memory-search.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 | $0.00208 | $0.02192 |
| Opus 5.5 | $0.00083 | $0.00877 |
| Sonnet 5.5 | $0.00042 | $0.00438 |
| Haiku 4.5 | $0.00021 | $0.00219 |
Grade A, and why
memory-search 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 — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Recalling from deep memory
You are a memory-retrieval agent. Search the kit's memory archive for: $ARGUMENTS
Query well: search the core noun phrases (e.g. "deploy target", "auth library decision"), not a full sentence. If the line above carries NO query (you run isolated and cannot see the conversation), start from the "When the query is vague" section below instead.
Memory is the ground truth for documented knowledge and prior decisions (the injected-snapshot authority rule). Your job is to find what is already recorded and return ONLY a curated summary — never the raw dumps.
The recall ladder (filter before you fetch; stop at the shallowest rung that answers)
Work index → neighborhood → bodies → (last resort) the session record. Full bodies are ~10x the tokens of an index line; fetch them only for the ids that survived filtering. Stop climbing the moment a rung answers the question — most questions end at step 1 or 2.
Step 1 — Search the index. Prefer the MCP tool when the cmk server is
connected; otherwise the CLI:
- MCP:
mk_searchwithquery(natural language is fine — when semantic recall is enabled the project default searches by meaning; paraphrase hits) ANDsource: "skill"(a telemetry tag — it lets the kit measure how often this skill fires; harmless, always pass it). - CLI:
cmk search "<query>" --source skill
Each hit is one line: id, tier/trust, source location, snippet. Run 1-3 query variants if the first misses (synonyms; the key noun alone). Drop hits that are clearly off-topic or too generic.
Score the survivors before you fetch. After dropping off-topic hits, rate each remaining hit 1-3 for how directly it answers the question (3 = likely answers it, 1 = tangential). Fetch full bodies (step 3) ONLY when at least 2 hits survive at score ≥ 2 — a lone weak hit rarely repays the tokens; answer from the index line + a re-query instead. This is the policy-retriever discipline: filter hard, fetch little.
Relative-answer re-query. If the question is relative — "the same X as Sarah", "like the auth project", "whatever we used last time" — a single search often can't resolve it. Re-query the REFERENT first (search "Sarah" / "auth project" to find X), THEN search X for the actual answer. Two cheap searches beat one that can't land.
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 · 173 lines · 208 tokens per session scan A e5da1254bfa2
memory-search is a skill published in the GitHub repository LH8PPL/core-memory-kit (7 stars, last pushed 26d ago), licensed MIT. It adds 208 tokens to every session and 2,192 once invoked, about $0.0008 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
mem9
Persistent cloud memory for OpenClaw agents. Use when users say: "install mem9" "setup memory" "add memory plugin" "openclaw memory" "mem9 onboarding" "memory not working" "import memories" "upload sessions".
mem9
Persistent cloud memory for OpenClaw agents. Use when users say: "install mem9" "setup memory" "add memory plugin" "openclaw memory" "mem9 onboarding" "memory not working" "import memories" "upload sessions".
ultramemory-snapshot
Compose and save a durable, wayback-grade session snapshot to UltraMemory. Use this whenever you are asked to write a session snapshot or rollup of the work just done — in particular when the UltraMemory capture hook nudges you to "Compose a session snapshot per the ultramemory-snapshot Skill rubric ... and save it…
save-topic
Use when the user wants to save or checkpoint topic progress, persist current discussion state, or save all topics before ending a session.
setup
Guides Claude through first-time UltraMemory configuration after plugin install — API key, MCP server registration, test recall, and 401/403 troubleshooting.
ignore-topic
Use when the user wants to ignore, skip, or exclude specific topics from being archived. Triggers on "ignore topic", "don't archive", "skip topic", "stop remembering", "list ignored topics", "remove ignore rule".