How do I install the Recall skill?

Run npx skillmds@latest add lucassantana-dev/recall-2 in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Recall safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Recall?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Recall free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Recall?

LucasSantana-Dev (@lucassantana-dev) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Recall by lucassantana-dev — Agent Skill

Name: Recall
Author: LucasSantana-Dev

Recall

Semantic-search personal knowledge (memory, plans, handoffs, skills, Codex rules) via the local RAG index at ~/.claude/rag-index/. Use when a query is fuzzy or cross-file ("how did we fix X", "what did we decide about Y", "which skill handles Z"). Complements grep (exact) and Serena (code symbols). If the user asks a recall question that doesn't map to a specific known file, reach here first.

LucasSantana-Dev Updated Sep 21, 2026 1 repo stars

File contents

recall

Semantic search over your personal knowledge corpus — chunked + embedded with all-MiniLM-L6-v2, stored in SQLite at ~/.claude/rag-index/index.sqlite. Local-only.

When to use

Fuzzy / cross-file recall: "how did we fix pi-hole v6 volume shadow?"
Skill discovery by intent: "which skill covers X"
Past-decision lookup: "why did we choose Caddy over nginx-proxy"
Handoff resumption: "what was I doing Thursday"

When NOT to use

Code symbols / refs in a live repo → use Serena instead.
Grep for a literal string → use Grep tool.
Reading a file you already know the name of → use Read tool.

Usage

~/.claude/rag-index/venv/bin/python ~/.claude/rag-index/query.py "<natural-language question>"

Flags:

--top N (default 5)
--scope memory,plans,handoffs,skills,codex (default all)
--format json (structured output for programmatic callers)

Index sources

~/.claude/projects/-Users-lucassantana/memory/*.md
~/.claude/plans/*.md
~/.claude/handoffs/*/*.md
~/.claude/skills/*/SKILL.md
~/.codex/AGENTS.md + ~/.codex/rules/*.rules

Rebuild

~/.claude/rag-index/venv/bin/python ~/.claude/rag-index/build.py              # full (~5s, 900 chunks)
~/.claude/rag-index/venv/bin/python ~/.claude/rag-index/build.py --incremental path/to/file.md  # single file

A PostToolUse hook auto-runs --incremental whenever Claude writes to a tracked directory, so day-to-day you never need to rebuild manually. Full rebuild only after schema changes or bulk file moves.

Output format

#1  rrf=0.0312 cos=0.41 bm=7.82  [memory]  /path/to/file.md:40-53
   <400-char snippet>

rrf is the fused rank score; cos is MiniLM cosine similarity; bm is BM25 lexical score. With rerank enabled, the CLI also includes cross-encoder ordering from the top fused candidates.

Tuning notes

Markdown fallback chunks are ~300 words with small overlap; code chunks are symbol-aware.
Local model only (no network, ~90 MB).
Reference deployment is ~17k chunks × 384 dims; full rebuild ~55 s on Apple Silicon.
Reranker is supported via --rerank on|off|auto; use --fast to disable it for latency.

Integration

plan skill: append "related past plans" by running recall --scope plans on the task description.
pr-flow / ship: inject related ADR / spec references into PR body.
sync-memories: chains into build.py --incremental automatically.

---name: recall-2description: Semantic-search personal knowledge (memory, plans, handoffs, skills, Codex rules) via the local RAG index at ~/.claude/rag-index/. Use when a query is fuzzy or cross-file ("how did we fix X", "what did we decide about Y", "which skill handles Z"). Complements grep (exact) and Serena (code symbols). If the user asks a recall question that doesn't map to a specific known file, reach here first.---# recallSemantic search over your personal knowledge corpus — chunked + embedded with `all-MiniLM-L6-v2`, stored in SQLite at `~/.claude/rag-index/index.sqlite`. Local-only.## When to use- Fuzzy / cross-file recall: "how did we fix pi-hole v6 volume shadow?"- Skill discovery by intent: "which skill covers X"- Past-decision lookup: "why did we choose Caddy over nginx-proxy"- Handoff resumption: "what was I doing Thursday"## When NOT to use- Code symbols / refs in a live repo → use Serena instead.- Grep for a literal string → use Grep tool.- Reading a file you already know the name of → use Read tool.## Usage```bash~/.claude/rag-index/venv/bin/python ~/.claude/rag-index/query.py "<natural-language question>"```Flags:- `--top N` (default 5)- `--scope memory,plans,handoffs,skills,codex` (default all)- `--format json` (structured output for programmatic callers)## Index sources- `~/.claude/projects/-Users-lucassantana/memory/*.md`- `~/.claude/plans/*.md`- `~/.claude/handoffs/*/*.md`- `~/.claude/skills/*/SKILL.md`- `~/.codex/AGENTS.md` + `~/.codex/rules/*.rules`## Rebuild```bash~/.claude/rag-index/venv/bin/python ~/.claude/rag-index/build.py # full (~5s, 900 chunks)~/.claude/rag-index/venv/bin/python ~/.claude/rag-index/build.py --incremental path/to/file.md # single file```A `PostToolUse` hook auto-runs `--incremental` whenever Claude writes to a tracked directory, so day-to-day you never need to rebuild manually. Full rebuild only after schema changes or bulk file moves.## Output format```text#1 rrf=0.0312 cos=0.41 bm=7.82 [memory] /path/to/file.md:40-53 <400-char snippet>````rrf` is the fused rank score; `cos` is MiniLM cosine similarity; `bm` is BM25 lexical score.With rerank enabled, the CLI also includes cross-encoder ordering from the top fused candidates.## Tuning notes- Markdown fallback chunks are ~300 words with small overlap; code chunks are symbol-aware.- Local model only (no network, ~90 MB).- Reference deployment is ~17k chunks × 384 dims; full rebuild ~55 s on Apple Silicon.- Reranker is supported via `--rerank on|off|auto`; use `--fast` to disable it for latency.## Integration- `plan` skill: append "related past plans" by running `recall --scope plans` on the task description.- `pr-flow` / `ship`: inject related ADR / spec references into PR body.- `sync-memories`: chains into `build.py --incremental` automatically.

Frequently asked questions