---
name: Remnic Recall
slug: remnic-recall-2
category: AI Engineering
description: Remnic Recall searches Remnic memories with a natural-language query when a task needs prior context. Use it to retrieve relevant past discussions before continuing work.
github: "https://github.com/joshuaswarren/remnic/tree/main/packages/plugin-codex/skills/remnic-recall"
language: TypeScript
stars: 193
forks: 23
install: "npx degit https://github.com/joshuaswarren/remnic/tree/main/packages/plugin-codex/skills/remnic-recall ~/.claude/skills/remnic-recall"
installs_to: ~/.claude/skills/remnic-recall
source_path: packages/plugin-codex/skills/remnic-recall/SKILL.md
collection_size: 12
category_size: 3278
collection_url: "https://dirskills.com/collections/joshuaswarren/remnic"
added: 2026-09-06T05:19:10.924Z
last_synced: 2026-09-06T05:19:10.924Z
canonical_url: "https://dirskills.com/skills/remnic-recall-2"
---

# Remnic Recall

Remnic Recall searches Remnic memories with a natural-language query when a task needs prior context. Use it to retrieve relevant past discussions before continuing work.

**Install:**

```bash
npx degit https://github.com/joshuaswarren/remnic/tree/main/packages/plugin-codex/skills/remnic-recall ~/.claude/skills/remnic-recall
```

## README

## When to use

Use when the user or the current task needs prior context from Remnic. This is the default first step for any non-trivial turn that could benefit from memory.

Triggers:

- "What do you remember about …"
- "Have we talked about …"
- "Recall anything on …"
- A new task begins and the agent wants background.

## Inputs

- `query` (required) — natural-language question or topic string.
- Optional budget hint from the caller (e.g., "brief", "deep").

## Procedure

1. Build a concise natural-language query from the user's request. Prefer the user's own wording over paraphrase.
2. Call `remnic_recall` with that query. Ask for 3–8 results unless the caller hinted otherwise.
3. Skim the returned memories. Discard anything clearly off-topic.
4. Present 1–5 relevant bullet points to the user, each attributed to its source memory when useful.
5. If nothing relevant came back, say so plainly and suggest `remnic-remember` if there is something worth storing now.

## Efficiency plan

- One broad recall beats several narrow ones.
- Reuse results within the same turn — do not re-query for the same topic.
- Skip recall entirely for trivially local requests (formatting, arithmetic, mechanical refactors).

## Pitfalls and fixes

- **Pitfall:** Quoting irrelevant recalls just because they came back. **Fix:** Filter by topical relevance before surfacing.
- **Pitfall:** Over-narrowing the query and missing useful context. **Fix:** Start broad; refine only if the first pass was noisy.
- **Pitfall:** Presenting raw memory blobs. **Fix:** Summarize in the user's own terms.

## Verification checklist

- [ ] `remnic_recall` was called with a natural-language query.
- [ ] Results were filtered for relevance before surfacing.
- [ ] User-facing summary is concise (≤ 5 bullets unless requested).
- [ ] Legacy `engram_recall` alias was not preferred over `remnic_recall`.

> Tool names: canonical name is `remnic_recall`. The legacy `engram_recall` alias remains accepted during v1.x.