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 teimurjan/lethe --skill recall-globalgit clone --depth 1 https://github.com/teimurjan/letheWrote 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/teimurjan/lethe/recall-global)<a href="https://agentmods.dev/skills/teimurjan/lethe/recall-global"><img src="https://agentmods.dev/badge/skills/teimurjan/lethe/recall-global/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/teimurjan/lethe/recall-global"><img src="https://agentmods.dev/badge/skills/teimurjan/lethe/recall-global.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 | $0.00064 | $0.00654 |
| Opus 5 | $0.00032 | $0.00327 |
| Sonnet 5 | $0.00013 | $0.00131 |
| Haiku 4.5 | $0.00006 | $0.00065 |
Grade A, and why
recall-global 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 9d 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 — 39 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a memory retrieval agent for lethe, a memory store that indexes your Claude Code / Codex transcripts directly, with hybrid BM25 + dense retrieval and clustered retrieval-induced forgetting.
Scope
This skill searches every lethe project the user has indexed via DuckDB ATTACH. Every lethe index auto-registers a project in ~/.lethe/projects.json, so this sees everything the user has ever indexed. If the user only wants the current project, use the recall skill instead.
Task
Find memories relevant to: $ARGUMENTS
Steps
-
Search. Run the CLI with
--all:lethe search "<query>" --all --top-k 5 --json-output- If
letheis not on PATH, ask the user to install it:brew tap teimurjan/lethe && brew install lethe(macOS / Linuxbrew) orcargo install lethe-cli.
Output is JSON with per-project attribution:
[{"id": "...", "content": "...", "score": 4.2, "project_slug": "...", "project_root": "..."}, ...].--allalways opens every per-project index read-only, so cross-project recall is concurrency-safe and never updates RIF state. No--read-onlyopt-out is needed here. Note:--alldoes not reindex transcripts, so each project reflects its last single-projectrecall/lethe index; runrecall(orlethe index) in a project first if you need its very latest turns. -
Filter. Skip results that obviously don't match the user's question. A weak cross-encoder score (< 0) usually means a miss.
-
Expand. For the top 2–3 hits, run
lethe --root <project_root> expand <id1> <id2> ...(multi-arg, single call). Group hits byproject_rootso each call hits the right project's index — across N projects, issue N parallel calls. Output is plain text with=== <id> ===headers between chunks. -
Summarize. Return a concise, source-referenced answer:
- Quote or paraphrase the relevant fragments.
- Always cite the source project (slug or path) since hits span multiple repos — disambiguation matters more here than in single-project recall.
- Cite day / session within the project when it helps.
- If nothing clearly applies, say "No relevant memories found across any registered project." — do not fabricate.
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.
- 9d ago First seen · 39 lines · 64 tokens per session scan A 04ebee213f5b
recall-global is a skill published in the GitHub repository teimurjan/lethe (11 stars, last pushed 1mo ago), licensed MIT. It adds 64 tokens to every session and 654 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 2026-08-30.
Other skills, from other repositories
knowledge_store_skill
Skill for working with local .knowledge.yaml files via KnowledgeStore. Use this when you need to recall, search, or manage directory-local memories and knowledge links stored in plain YAML alongside the user's project files. KnowledgeStore is directory-scoped. Each directory that contains a .knowledge.yaml file…
cocoscout
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cocohealth
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pull-search
CocoPull session archive search — full-text search across past sessions. Handles $pull search " " with --since and --feature filters, and $pull index rebuild.
pod-kb
Display the project knowledge base (lifecycle/kb.md) — project-specific patterns, decisions, and gotchas accumulated by CocoCupper across sessions.
pod-resume
Reconstruct context for a returning developer. Reads .cocoplus/ state and generates a narrative summary of project status, last achievements, pending tasks, recent decisions, available patterns, CocoCupper insights, and recommended next action.