recall

recall is a command for coding agents from EverMind-AI/EverMe. It costs 18 tokens per session (277 once invoked), scanned A, original, Apache-2.0.

A command for searching EverMe's stored memories with a query and using relevant results as context for the current task.

In plain words
What is it for?
Use it to recall past decisions, conversations, project details, or solved errors, with a broader retry when the first search is weak.
Why use it?
It avoids relying on guesses about earlier work and says when the memory search finds nothing useful.

Command

Part of the everme plugin — 2 commands, 4 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 commands/evermind-ai/everme/recall
Clone the repo
git clone --depth 1 https://github.com/EverMind-AI/EverMe

Or install everme, the plugin that ships this one along with the rest of its 2 commands, 4 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/commands/evermind-ai/everme/recall.svg)](https://agentmods.dev/commands/evermind-ai/everme/recall)
Your own site
<a href="https://agentmods.dev/commands/evermind-ai/everme/recall"><img src="https://agentmods.dev/badge/commands/evermind-ai/everme/recall.svg" alt="Measured on agentmods" height="20"></a>
Per session 18 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 277 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 $0.00018 $0.00277
Opus 5 $0.00009 $0.00138
Sonnet 5 $0.00004 $0.00055
Haiku 4.5 $0.00002 $0.00028

Measured 4d ago against content hash 8eb26ed5d127, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, 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 4d 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/commands/recall.md · 28 lines

What it actually says

EverMe · recall

Use the canonical EverMe MCP tools:

  • mem_search — hybrid search across episodic memories, profile entries, agent cases/skills, and the recent raw transcript.
  • mem_context — durable Profile snapshot only; it does not search past conversations and is not needed for this command.

Query

{{query}}

Instructions

  1. Call mem_search with a short version of the query. Start with topK: 10.
  2. If the returned memories are clearly relevant, summarize them briefly and use them to answer or guide the next action.
  3. If results are weak or empty, retry once with broader keywords. If still nothing useful, say so explicitly — do not fabricate context.
  4. Treat rows under "Recent unextracted transcript" as provisional, not as established facts or confirmed decisions.
  5. When citing a memory, mention its subject or session id when available so the user can trace it through evercli or the EverMe Web UI.
  6. NEVER paste an entire long memory body verbatim; quote only the salient parts.
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. 4d ago First seen · 28 lines · 18 tokens per session scan A 8eb26ed5d127

Subscribe to this mod's changes

recall is a command published in the GitHub repository EverMind-AI/EverMe (57 stars, last pushed 6d ago), licensed Apache-2.0. It adds 18 tokens to every session and 277 once invoked, about $0.0001 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.