What is cross-agent-recall?

A read-only search tool for finding relevant details in earlier coding-agent sessions from Claude Code and Codex. It can recover past fixes, decisions, commands, and handoff context.

Use it to find how a previous bug was fixed, recover an earlier command or design decision, or continue work started in another coding agent.

It helps avoid repeating investigations when the answer or approach may already exist in an earlier session.

cross-agent-recall — Skill for Claude Code and Codex by Lum1104: A read-only search tool for finding relevant details in…

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/lum1104/uni-code/cross-agent-recall

Any agent

npx skills add Lum1104/uni-code --skill cross-agent-recall

Clone the repo

git clone --depth 1 https://github.com/Lum1104/uni-code

Made for: Claude Code, Codex.

Or install uni-code, the plugin that ships this one along with the rest of its 1 skill, 1 MCP server.

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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/lum1104/uni-code/cross-agent-recall.svg)](https://agentmods.dev/skills/lum1104/uni-code/cross-agent-recall)

Your own site

<a href="https://agentmods.dev/skills/lum1104/uni-code/cross-agent-recall"><img src="https://agentmods.dev/badge/skills/lum1104/uni-code/cross-agent-recall.svg" alt="Measured on agentmods" height="20"></a>

Per session 73 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 539 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	$0.00073	$0.00539
Opus 5	$0.00036	$0.00269
Sonnet 5	$0.00015	$0.00108
Haiku 4.5	$0.00007	$0.00054

Measured 4d ago against content hash 0558abd88e58, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

cross-agent-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 4d 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.

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/cross-agent-recall/SKILL.md · 29 lines

How it starts

The opening of the file, as written. The whole thing — 29 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Cross-agent recall

This machine has uni-code installed: a local, read-only index of every Claude Code and Codex session, exposed through the uni-code MCP server.

When to reach for it

The user references past work you don't have in context: "that bug we fixed", "the command from last time", "why did we choose X".
The user mentions another agent: "I started this in Codex", "Claude tried something yesterday".
You are about to re-derive something (a config, a fix, an investigation) the user has plausibly done before — one cheap search first can save the whole rework.

How to use it

resume_session when the user wants to CONTINUE earlier work in earnest ("resume the Codex session", "continue exactly where I left off") — it reconstructs the session's effective context: the source agent's own compaction summary plus everything after it. Pass project: "."; if the result turns out to be this very conversation, pass the other agent's name or an explicit id.
get_handoff for a quick one-page orientation instead (goal, where it ended, files touched, commands, errors) when the user just wants you up to speed, not a full continuation.
search_history with distinctive terms — code identifiers and error strings beat prose; Chinese/Japanese/Korean queries work. Add project: "." to scope to the current project.
read_session on the best hit's id. Default returns the END of the session (outcomes, conclusions); pass from_start: true to see the original goal.
list_sessions when there is no search term — e.g. "what was I doing yesterday?".

Notes

Results may come from a different agent than the current one; treat them as the user's own history, and say which agent/session an answer came from.
Everything is local and read-only; the index refreshes automatically on each query. If the very first query on a machine is slow, that is the one-time initial indexing.
If a search returns nothing, retry once with fewer or different terms before concluding the history doesn't exist.

Read the full file on GitHub · 29 lines

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.

4d ago First seen · 29 lines · 73 tokens per session scan A 0558abd88e58

Subscribe to this mod's changes

cross-agent-recall is a skill published in the GitHub repository Lum1104/uni-code (7 stars, last pushed 1mo ago), licensed MIT. It adds 73 tokens to every session and 539 once invoked, about $0.0004 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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