recall

A command that searches Walrus Memory for information related to a question or task. It then reports the useful results or says when none are relevant.

In plain words
What is it for?
Use it before work that depends on prior notes, requirements, preferences, or decisions.
Why use it?
It saves you from manually reconstructing earlier decisions and project context.

Command

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/commandosslabs/walrus-memory-mcp-plugin/recall
Clone the repo
git clone --depth 1 https://github.com/CommandOSSLabs/walrus-memory-mcp-plugin
Per session 9 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 78 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 $0.00009 $0.00078
Opus 5 $0.00005 $0.00039
Sonnet 5 $0.00002 $0.00016
Haiku 4.5 $0.00001 $0.00008

Measured yesterday against content hash c9a81271841f, 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 yesterday.

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.

commands/recall.md · 16 lines

What it actually says

Search Walrus Memory with memwal_recall for context relevant to the user's query below.

Use a focused semantic query. After recalling, summarize only the useful findings and say when no relevant memory was found.

Recall query:

$ARGUMENTS
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. yesterday First seen · 16 lines · 9 tokens per session scan A c9a81271841f

Subscribe to this mod's changes

recall is a command published in the GitHub repository CommandOSSLabs/walrus-memory-mcp-plugin (0 stars, last pushed 13d ago), licensed Apache-2.0. It adds 9 tokens to every session and 78 once invoked, about $0.0000 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 2026-08-31.