memory-recall

memory-recall is a skill for Claude Code, Codex from zilliztech/memsearch. It costs 149 tokens per session (912 once invoked), scanned A, original, MIT.

A tool for searching and recalling useful information from earlier coding sessions, such as past decisions, debugging notes, and project knowledge.

In plain words
What is it for?
Use it to look up what was decided about a feature, why a change was made, or whether a problem has appeared before. It searches stored project memories and expands relevant results.
Why use it?
It reduces the need to repeat questions or reconstruct why a previous implementation was chosen. It helps recover context that is not present in the current conversation.

Skill for Claude CodeCodex

Installs and runs on its own, but its text points at files inside its plugin — anything it tells you to read at a ${CLAUDE_PLUGIN_ROOT} path is only there once the plugin is installed. Installing the plugin gets both.

Part of the memsearch plugin — 1 skill, 4 hooks shipped together

About the project

MemSearch is a cross-platform semantic memory layer for AI coding agents that stores human-readable Markdown memories and indexes them with Milvus for searchable retrieval. It is used by agent users who want persistent context and by developers building memory features into agents across tools such as Claude Code, Codex, DeepSeek Harness, OpenClaw, and OpenCode. Catalogue add-ons provide the hooks, skills, and plugin workflows that capture, retrieve, and maintain this memory.

zilliztech/memsearch · 2,565 stars · on GitHub

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/zilliztech/memsearch/memory-recall
Any agent
npx skills add zilliztech/memsearch --skill memory-recall
Clone the repo
git clone --depth 1 https://github.com/zilliztech/memsearch

Made for: Claude Code, Codex.

Or install memsearch, the plugin that ships this one along with the rest of its 1 skill, 4 hooks.

Wrote 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.

agentmods badge for memory-recall

README.md
[![agentmods](https://agentmods.dev/badge/skills/zilliztech/memsearch/memory-recall.svg)](https://agentmods.dev/skills/zilliztech/memsearch/memory-recall)
Your own site
<a href="https://agentmods.dev/skills/zilliztech/memsearch/memory-recall"><img src="https://agentmods.dev/badge/skills/zilliztech/memsearch/memory-recall.svg" alt="Measured on agentmods" height="20"></a>
Per session 149 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 912 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 $0.00149 $0.00912
Opus 5 $0.00075 $0.00456
Sonnet 5 $0.00030 $0.00182
Haiku 4.5 $0.00015 $0.00091

Measured 5d ago against content hash 6c269f28a03a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

memory-recall 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 5d 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.

plugins/claude-code/skills/memory-recall/SKILL.md · 51 lines

How it starts

The opening of the file, as written. The whole thing — 51 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a memory retrieval agent for memsearch. Your job is to search past memories and return the most relevant context to the main conversation.

Project Collection

Collection: !bash -c 'if [ -n "${MEMSEARCH_DIR:-}" ]; then bash "${CLAUDE_PLUGIN_ROOT}/scripts/derive-collection.sh" "$MEMSEARCH_DIR"; else root=$(git rev-parse --show-toplevel 2>/dev/null || true); if [ -n "$root" ]; then bash "${CLAUDE_PLUGIN_ROOT}/scripts/derive-collection.sh" "$root"; else bash "${CLAUDE_PLUGIN_ROOT}/scripts/derive-collection.sh"; fi; fi'

Your Task

Search for memories relevant to: $ARGUMENTS

Steps

  1. Search: Run memsearch search "<query>" --top-k 5 --json-output --collection <collection name above> to find relevant chunks.

    • If memsearch is not found, try uvx memsearch instead.
    • Choose a search query that captures the core intent of the user's question.
  2. Evaluate: Look at the search results. Skip chunks that are clearly irrelevant or too generic.

  3. Expand: For each relevant result, run memsearch expand <chunk_hash> --collection <collection name above> to get the full markdown section with surrounding context.

  4. Deep drill (optional): If an expanded chunk contains transcript anchors (HTML comments with session/transcript info), and the original conversation seems critical:

    • Run memsearch transcript <jsonl_path> --turn <uuid> --context 3 to retrieve the original conversation turns (auto-detects the transcript format and includes tool calls). If memsearch is not found, use uvx memsearch instead.
    • If memsearch transcript reports an unrecognized transcript format, or the anchor format is unfamiliar (e.g. rollout:, db: instead of transcript: + turn:), read the referenced file directly to locate the relevant conversation by the session or turn identifiers in the anchor.
  5. Return results: Output a curated summary of the most relevant memories. Be concise — only include information that is genuinely useful for the user's current question.

Read the full file on GitHub · 51 lines

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. 5d ago First seen · 51 lines · 149 tokens per session scan A 6c269f28a03a

Subscribe to this mod's changes

memory-recall is a skill published in the GitHub repository zilliztech/memsearch (2,565 stars, last pushed 2d ago), licensed MIT. It adds 149 tokens to every session and 912 once invoked, about $0.0007 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.