recall

recall is a skill for Claude Code, Codex from wenlan-app/wenlan. It costs 50 tokens per session (1,279 once invoked), scanned B, original, Apache-2.0.

A slash command for searching Wenlan's local memory by a specific question or phrase. It can search a chosen space when one is provided.

In plain words
What is it for?
Use it to retrieve one remembered detail from local agent memory by natural-language query.
Why use it?
It helps find a past fact, decision, lesson, or preference without reviewing the whole session.

Skill for Claude CodeCodex

Written for Claude Code and Codex: allowed-tools in frontmatter, but also agents/openai.yaml present. Also seen: mentions Codex.

Good fit Use it to retrieve one remembered detail from local agent memory by natural-language query.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/wenlan-app/wenlan/recall
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.

Any agent
npx skills add wenlan-app/wenlan --skill recall
Clone the repo
git clone --depth 1 https://github.com/wenlan-app/wenlan

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for recall

README.md
[![agentmods](https://agentmods.dev/badge/skills/wenlan-app/wenlan/recall/github.svg)](https://agentmods.dev/skills/wenlan-app/wenlan/recall)
Your own site
<a href="https://agentmods.dev/skills/wenlan-app/wenlan/recall"><img src="https://agentmods.dev/badge/skills/wenlan-app/wenlan/recall/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for recall

Your own site · 80×15
<a href="https://agentmods.dev/skills/wenlan-app/wenlan/recall"><img src="https://agentmods.dev/badge/skills/wenlan-app/wenlan/recall.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 50 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,279 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00050 $0.01279
Opus 5.5 $0.00020 $0.00512
Sonnet 5.5 $0.00010 $0.00256
Haiku 4.5 $0.00005 $0.00128

Measured 3d ago against content hash 2788713c0c07, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade B, and why

recall scanned grade B with 1 finding 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 3d ago.

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.

Reads agent configuration directoriesmediumAgent snooping

.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.

resolver="$(find "$HOME/.codex/plugins/cache" -path '*/wenlan/*/bin/resolve-space.sh' 2>/dev/null | head -1)"
Origin

Copies of this mod

1 near-identical copy found in the catalogue:

  • recall — 86% identical, 154 lines differ
plugin-codex/skills/recall/SKILL.md · 137 lines

How it starts

The opening of the file, as written. The whole thing — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/recall

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

Resolve the active space

The /recall skill accepts one optional inline token of the form space:<name> anywhere in the argument string. The bundled resolver strips it and returns the rest as the query. It prints the resolved Space line itself:

raw_args="<the full argument string passed to /recall>"
# The resolver ships inside the installed plugin; the relative path only
# exists in a wenlan checkout.
resolver="$(find "$HOME/.codex/plugins/cache" -path '*/wenlan/*/bin/resolve-space.sh' 2>/dev/null | head -1)"
resolved="$("${resolver:-plugin-codex/bin/resolve-space.sh}" --cwd "$PWD" --args "$raw_args")"
space="$(printf '%s\n' "$resolved" | cut -f1)"
source_layer="$(printf '%s\n' "$resolved" | cut -f2)"
query="$(printf '%s\n' "$resolved" | cut -f3-)"

If query is empty, ask the user what they want to search for. Pass space="$space" to the recall MCP tool only when space is non-empty; otherwise omit the space filter.

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.

Read the full file on GitHub · 137 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 3d ago Changed · +39 lines · +18 tokens per session 2788713c0c07
  2. 4d ago First seen · 98 lines · 32 tokens per session scan B 2873d9bf8d0d

Subscribe to this mod's changes

recall is a skill published in the GitHub repository wenlan-app/wenlan (82 stars, last pushed yesterday), licensed Apache-2.0. It adds 50 tokens to every session and 1,279 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-11.