recall

recall is a command for Claude Code from vshulcz/deja-vu. It costs 17 tokens per session (184 once invoked), scanned A, a copy of deja, MIT.

A command for searching your own past AI coding sessions on the machine. It can look for earlier discussions, errors, decisions, or fixes across coding tools.

In plain words
What is it for?
Use it to find a past error message, function name, file path, project decision, or fix, then retrieve more context when the first result is too brief.
Why use it?
It saves you from repeating an investigation when the same project problem or question was already handled in an earlier session.

Command for Claude Code

Written for Claude Code: $ARGUMENTS substitution.

Good fit Use it to find a past error message, function name, file path, project decision, or fix, then retrieve more context when the first result is too brief.

Compare 6 commands from other repositories ↓
Install with agentmods
npx agentmods add commands/vshulcz/deja-vu/recall
About the project

deja-vu is a local memory system that indexes coding-agent session histories and makes relevant past work available to other agents. It helps users share fixes and context across Claude Code, Codex, Cursor, Copilot CLI, and other coding agents without using a language model or embeddings. The catalogue contains hooks, commands, MCP components, skills, plugins, and instructions for connecting agents to that memory.

vshulcz/deja-vu · 1,288 stars · on GitHub · vshulcz.github.io

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.

Clone the repo
git clone --depth 1 https://github.com/vshulcz/deja-vu

Made for: Claude Code.

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/vshulcz/deja-vu/recall/github.svg)](https://agentmods.dev/commands/vshulcz/deja-vu/recall)
Your own site
<a href="https://agentmods.dev/commands/vshulcz/deja-vu/recall"><img src="https://agentmods.dev/badge/commands/vshulcz/deja-vu/recall/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.

agentmods 80×15 button for recall

Your own site · 80×15
<a href="https://agentmods.dev/commands/vshulcz/deja-vu/recall"><img src="https://agentmods.dev/badge/commands/vshulcz/deja-vu/recall.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 17 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 184 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 97% copy Near-identical to another mod 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 $0.00017 $0.00184
Opus 5.5 $0.00007 $0.00074
Sonnet 5.5 $0.00003 $0.00037
Haiku 4.5 $0.00002 $0.00018

Measured 7d ago against content hash c78fbe44c2ed, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, 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 7d 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.

Origin

This is a copy

97% identical to deja — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

extensions/grok/commands/recall.md · 23 lines

What it actually says

Search the user's own past sessions across every AI coding tool on this machine, then answer from what you find.

Call the deja tool in recall mode with the user's words as the query — the most specific tokens win (an exact error string, a function name, a file path, a flag). If a result looks right but is too short to act on, follow up with context mode using a term from it.

If the deja MCP tool is unavailable, fall back to the CLI:

deja --framed search -- "$ARGUMENTS"

Answer with what actually happened in those sessions — when it was, which project and tool, what was decided or fixed. Say plainly if nothing matched rather than filling the gap from general knowledge.

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. 7d ago Changed c78fbe44c2ed
  2. 1mo ago Changed a9cc5950d90b
  3. 1mo ago Changed 5ddaca370f12
  4. 1mo ago First seen · 23 lines · 17 tokens per session scan A a373941b43ef

Subscribe to this mod's changes

recall is a command published in the GitHub repository vshulcz/deja-vu (1,288 stars, last pushed today), licensed MIT. It adds 17 tokens to every session and 184 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 97% identical to deja, differing in 2 lines, and is treated as a copy.