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Agent skill

Recall

by davepoon in davepoon/buildwithclaude

Search Origin's local memory by query. An agent skill from davepoon/buildwithclaude.

MITAuto-check passed

Install Recall

skills CLI
$ npx skills add davepoon/buildwithclaude --skill recall -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install davepoon/buildwithclaude recall --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/davepoon/buildwithclaude.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/origin/skills/recall .claude/skills/recall && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
recall
GitHub stars
3.6k
Token cost
~981 tokens
SKILL.md length
480 words
Files
1
Skills in repo
245
Repo updated
First seen
Licence
MIT

At a glance

Search Origin's local memory by query. An agent skill from davepoon/buildwithclaude.

  • Works in 4 steps: expand the query (agent-side) → call the MCP tool → rerank (agent-side) → …
  • The user asks do you remember
  • SKILL.md covers Two phases, When to use, When NOT to use and Hint: write specific queries
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Recall is an agent skill from davepoon/buildwithclaude. Search Origin's local memory by query. Targeted lookup, not orientation. Invoked as /recall <query. Use when the user asks "do you remember", "what do you know about", "look up".

Its SKILL.md is about 980 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: A single hub to find Claude Skills, Agents, Commands, Hooks, Plugins, and Marketplace collections to extend Claude Code, Claude Desktop, Agent SDK and OpenClaw. The licence is MIT.

When your agent uses it

  • The user asks do you remember
  • What do you know about

Example prompts

  • “do you remember”
  • “what do you know about”
  • “look up”
  • “/recall”

Requirements

  • Pre-approved tools (allowed-tools): mcp__plugin_origin_origin__recall

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. expand the query (agent-side)
  2. call the MCP tool
  3. rerank (agent-side)
  4. render revision context (per result)

What it can do on your machine

Read from SKILL.md and the folder at commit 10bfc43. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • mcp__plugin_origin_origin__recall

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Recall loads about 981 tokens when it runs. Until then it costs about 47 tokens; SKILL.md has 480 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~47
When it runs · the whole SKILL.md, loaded when a task matches
~981

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from davepoon/buildwithclaude at commit 10bfc43, republished under its MIT licence (© davepoon). 480 words, ~981 tokens.

Download SKILL.mdSave it as .claude/skills/recall/SKILL.md (or your agent's skills folder).
name
recall
description
Search Origin's local memory by query. Targeted lookup, not orientation. Invoked as `/recall <query>`. Use when the user asks "do you remember", "what do you know about", "look up".
allowed-tools
mcp__plugin_origin_origin__recall
argument-hint
<query>

/recall

Search Origin's memory by natural-language query. Returns matching memories ranked by hybrid vector + FTS search, then re-ordered by the agent if it helps.

Two phases

When a local model or API key is configured, the daemon can rerank and expand server-side. In local memory mode it cannot. The skill always does agent-side expansion and rerank itself — cheap, makes results good in both modes.

Phase 1 — expand the query (agent-side)

Before calling recall, rewrite the user's query into a more search-friendly form:

  • Replace pronouns with the referent ("it" → the actual thing).
  • Expand abbreviations the embedder is unlikely to know.
  • Add the obvious synonym when the original term is too narrow (e.g. "auth" → "auth OR authentication").

Don't over-expand. If the query is already specific, leave it alone. One recall call per /recall invocation — duplicate calls double embedding load and the merge step is rarely worth it. The daemon's own search_memory_expanded exists for the multi-query case; if it matters, use that endpoint instead of issuing parallel calls here.

Phase 2 — call the MCP tool
recall(query="<expanded query>", space=<inferred>, memory_type=<inferred>)

Inferences (do not ask the user):

  • space: current working directory (e.g. ~/Repos/origin/... → "origin"), the topic being discussed, or whatever space was mentioned in recent turns. Always pass when scope is known; if uncertain, run list_spaces later (post-PR-C) or omit.
  • memory_type: only when the query itself names a type ("decision on X", "lesson about Y", "preference for Z"). Otherwise omit and let hybrid search rank.
  • limit: default 10. Use 3-5 for quick lookups, 10-20 for exploration.
Phase 3 — rerank (agent-side)

The daemon returns hits ranked by hybrid search. That ranking is good but not perfect — it doesn't know the user's exact intent.

Re-read the returned memories against the original query. Promote the ones that directly answer the question; demote ones that just share keywords.

Show the user the top 3-5 reranked hits. Surface the rest only if asked.

Show full SKILL.md (171 more words)Show less
Phase 4 — render revision context (per result)

Each memory may carry revision fields: version, pending_revision, merged_from, last_delta_summary. Most memories are fresh (v1, none set) — render nothing extra for those. Only add a tag line when something meaningful is present.

Condition: emit the tag line when any of these holds:

  • version > 1
  • merged_from is non-empty
  • pending_revision == true

Format — one compact line above the memory body:

<id>  v<N> (merged <K> memories)         ← merged_from has K entries
<id>  v<N>, pending revision against <id> ← pending_revision true
<id>  v<N> — <last_delta_summary>         ← version > 1, delta populated
<id>  v<N>                                ← version > 1, no delta

Rules:

  • Merged takes precedence over pending_revision in the label.
  • Omit — <delta> when last_delta_summary is empty or null.
  • Skip the tag line entirely when version == 1 (or null) and no other flag is set. Preserves current output for fresh memories.

When to use

  • "What did I say about X?"
  • "Do you remember the decision on Y?"
  • Need a specific fact before continuing.

When NOT to use

  • Broad session orientation → use /brief instead.
  • Storing a new memory → use /capture.

Hint: write specific queries

"Alice database preference" finds more than "database stuff". The semantic matcher rewards specificity. If too many results return, add filters rather than making the query longer.

© davepoon, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in plugins/origin/skills/recall of davepoon/buildwithclaude.

Open the folder on GitHubat commit 10bfc43

Compare with similar skills

Recall next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Recall compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Recall this skilldavepoon/buildwithclaude3.6k—~981Automated safety check: PassMIT
Recallcursor/plugins10k7 repos~1.3kAutomated safety check: PassNone
Agentmemory Recallrohitg00/agentmemory29k—~557Automated safety check: PassApache-2.0
Cross Origin Securitythedaviddias/Front-End-Checklist74k—~595Automated safety check: PassMIT
Cross Origin Isolationthedaviddias/Front-End-Checklist74k—~565Automated safety check: PassMIT
Origin APIcursor/plugins10k—~694Automated safety check: PassMIT

Similar skills

  • Recall

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    A skill your agent uses when reviewing security-sensitive web apps, SharedArrayBuffer usage, worker-heavy apps, editors, or measurement features that require cross-origin isolation.

    74k GitHub stars~565 tokensUpdated 2 days ago
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  • Origin API

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    Routes questions about the Cursor Origin API to the right section of the Origin docs and names the few rules to check first.

    10k GitHub stars~694 tokensUpdated today
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  • Cognee Memory Recall

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Questions about Recall

What does Recall do?

Search Origin's local memory by query. An agent skill from davepoon/buildwithclaude. Recall is an agent skill from davepoon/buildwithclaude. Search Origin's local memory by query.

When should I use Recall?

Recall fits situations like: the user asks do you remember; what do you know about.

How do I install Recall in Claude Code?

Run `npx skills add davepoon/buildwithclaude --skill recall -a claude-code`. Or copy the skill folder (plugins/origin/skills/recall in davepoon/buildwithclaude) into .claude/skills/recall in your project. Claude Code loads it when a task matches its description.

How do I install Recall in Codex?

Run `npx skills add davepoon/buildwithclaude --skill recall -a codex`. Or copy the skill folder (plugins/origin/skills/recall in davepoon/buildwithclaude) into .agents/skills/recall in your project. Codex loads it when a task matches its description.

Can I use Recall in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add davepoon/buildwithclaude --skill recall -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/recall, .gemini/skills/recall, .github/skills/recall and .opencode/skills/recall in your project.

What does Recall need to run?

SKILL.md names no scripts, command-line tools or credentials: Recall is instructions for the agent only. Its frontmatter pre-approves these tools: mcp__plugin_origin_origin__recall.

Does Recall access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Recall safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Recall use?

Recall is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Recall use?

About 981 tokens (SKILL.md is roughly 3.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Recall?

Skills that share tags, products or a category with Recall: Recall (cursor/plugins, 10k stars), Agentmemory Recall (rohitg00/agentmemory, 29k stars), Cross Origin Security (thedaviddias/Front-End-Checklist, 74k stars) and Cross Origin Isolation (thedaviddias/Front-End-Checklist, 74k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Recall?

davepoon (a GitHub user) maintains it in davepoon/buildwithclaude, which has 3,604 GitHub stars. The repository holds 245 skills in this directory. The repository was last updated on October 6, 2026.

Source: davepoon/buildwithclaude on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.