recall

recall is a skill for Claude Code from mubit-ai/claude-plugins. It costs 37 tokens per session (568 once invoked), scanned A, original, Apache-2.0.

A search tool for finding stored lessons, rules, facts, or past work that relate to a specific question.

In plain words
What is it for?
It is for looking up details about earlier decisions, constraints, debugging approaches, or project history.
Why use it?
It brings back relevant previous knowledge when the context already provided to the agent is not enough.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter. Also seen: mentions subagents.

Part of the mubit-memory plugin — 13 skills, 1 agent, 13 hooks, 1 MCP server shipped together

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/mubit-ai/claude-plugins/recall
Any agent
npx skills add mubit-ai/claude-plugins --skill recall
Clone the repo
git clone --depth 1 https://github.com/mubit-ai/claude-plugins

Made for: Claude Code.

Or install mubit-memory, the plugin that ships this one along with the rest of its 13 skills, 1 agent, 13 hooks, 1 MCP server.

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 recall

README.md
[![agentmods](https://agentmods.dev/badge/skills/mubit-ai/claude-plugins/recall.svg)](https://agentmods.dev/skills/mubit-ai/claude-plugins/recall)
Your own site
<a href="https://agentmods.dev/skills/mubit-ai/claude-plugins/recall"><img src="https://agentmods.dev/badge/skills/mubit-ai/claude-plugins/recall.svg" alt="Measured on agentmods" height="20"></a>
Per session 37 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 568 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 5.1 $0.00037 $0.00568
Opus 5 $0.00018 $0.00284
Sonnet 5 $0.00007 $0.00114
Haiku 4.5 $0.00004 $0.00057

Measured 6d ago against content hash 4348017051a8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

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 6d 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.

integrations/claude-code/skills/recall/SKILL.md · 50 lines

How it starts

The opening of the file, as written. The whole thing — 50 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Relevant memory was already injected at the top of this turn by the Mubit recall hook. Read it before searching. Most of the time you do not need this skill.

When you do:

  1. Issue one broad mubit_recall call. Not three narrow ones.
  2. Read the evidence. If it answers the question, stop.
  3. Only if the first call returned nothing usable, issue one reformulated call.

Never fan out into parallel searches across sub-topics. Mubit retrieval is hybrid (semantic + lexical + recency + graph); one well-formed query beats four keyword slices at a quarter of the latency. Two calls is the ceiling.

Cite what you use by its reference_id, and call mubit_outcome with those entry_ids when recalled memory turns out to be right or wrong. That feedback is what makes the next recall better.

Writing the query

Query with the question, not with keywords. "Why does the drain hook retry twice on a 5xx" retrieves better than "drain retry 5xx", because the semantic half of the hybrid index has something to match on and the lexical half still catches the identifiers. Include the identifiers you already know — file names, symbol names, error strings — inside the sentence rather than instead of it.

A reformulation is a different concept, not a synonym. If "auth failed on ingest" returned nothing, "401 from the control plane" is a reformulation; "authentication failure ingest" is the same query with the words shuffled and will return the same nothing.

When two calls return nothing

Say so and move on. Empty is a real answer: it means nothing about this was ever captured, and a third query will not invent it. If the answer you then work out by hand is worth keeping, save it with /mubit-memory:remember so the next session's recall is not empty too.

Deep searches belong to the subagent

If the question genuinely needs several angles — "what do we know about X" across an unfamiliar area — invoke @mubit-memory:mubit-recall instead. It runs the same searches in an isolated context and returns a synthesis, so the raw evidence never lands here.

Read the full file on GitHub · 50 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. 6d ago First seen · 50 lines · 37 tokens per session scan A 4348017051a8

Subscribe to this mod's changes

recall is a skill published in the GitHub repository mubit-ai/claude-plugins (13 stars, last pushed yesterday), licensed Apache-2.0. It adds 37 tokens to every session and 568 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.

Related

Other skills, from other repositories

media-ingest

Ingest video, audio, PDF, book, screenshot, and GitHub repo content into the brain. Multi-format handling with entity extraction and backlink propagation. Covers video-ingest, youtube-ingest, and book-ingest subtypes.

garrytan/gbrain · 52 tokens

mem0-oss-to-platform

Plan and then execute a migration of a project from the mem0 open-source / self-hosted SDK (the local Memory class) to the mem0 Platform / hosted / managed SDK (the MemoryClient class). Use this whenever a developer wants to move, switch, or migrate their mem0 usage off OSS/self-hosted to the hosted API — e.g.…

mem0ai/mem0 · 273 tokens

Cortex

Operate Cortex, the LifeOS memory system — the typed Knowledge Archive (People, Companies, Ideas, Research with typed related: links) plus recall of prior work sessions, ISAs, and conversations. Search, add, harvest, develop, ingest, distill, graph-navigate, recall. USE WHEN cortex, knowledge, knowledge base, search…

danielmiessler/LifeOS · 196 tokens

agent-memory

../../../engineering/agent-memory/skills/agent-memory/SKILL.md.

alirezarezvani/claude-skills · 0 tokens

memory

Use when the user asks to remember, recall, forget, update, search, or inspect durable OpenSquilla memory, including profile facts in USER.md and long-term notes in MEMORY.md or memory//.md.

opensquilla/opensquilla · 44 tokens

ha-data-stores

Map of Hope Agent's local data stores and safe read-only query workflow. Use when the user asks where Hope Agent stores data, wants to inspect sessions/messages/memory/logs/background jobs/knowledge indexes/settings, asks the model to query local app data, or debugging requires checking persisted state. Trigger…

shiwenwen/hope-agent · 115 tokens