A memory-search skill for finding previously saved information in Super Memory, a semantic memory store.

Use it to search memories by topic, agent, type, or result count, and review matching content with relevance and age.

It helps recover relevant context from earlier sessions without remembering exactly where or how it was saved.

recall — Skill by Utundry

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/utundry/sloplesscode/recall

Any agent

npx skills add Utundry/sloplesscode --skill recall

Clone the repo

git clone --depth 1 https://github.com/Utundry/sloplesscode

Made for: Claude Code, Codex.

Per session 52 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 380 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.

Model	Per session	Once invoked
Fable 5	$0.00052	$0.00380
Opus 5	$0.00026	$0.00190
Sonnet 5	$0.00010	$0.00076
Haiku 4.5	$0.00005	$0.00038

Measured yesterday against content hash fa194190b6c7, 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.

skills/recall/SKILL.md · 46 lines

What it actually says

Recall — Search Super Memory

Search the semantic memory store for relevant saved information.

Arguments

$ARGUMENTS

Instructions

Parse the arguments:
- query: Search text (required)
- agent: Filter by agent ID (flag --agent <id>, default: no filter)
- type: Filter by memory type (flag --type <type>, default: no filter)
- n: Max results to return (flag --n <n>, default: 5)
Call mcp__super-memory__memory_search with:
- query: the search text
- agent_id: if provided
- memory_type: if provided
- limit: n value
Present results ranked by relevance score. For each result show:
- Score and similarity
- Memory type and category
- Full content
- Age (from timestamp)
If no results found, say so. If server is unreachable, suggest starting the services.

Examples

/recall user preferences
/recall --agent project1 database configuration
/recall --type task --n 10 pending work
/recall what does the user prefer for code style

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.

yesterday First seen · 46 lines · 52 tokens per session scan A fa194190b6c7

Subscribe to this mod's changes

recall is a skill published in the GitHub repository Utundry/sloplesscode (1 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 52 tokens to every session and 380 once invoked, about $0.0003 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.

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