computer-history

computer-history is a skill for Claude Code, Codex from MemTensor/memmy-agent. It costs 42 tokens per session (1,997 once invoked), scanned A, original, MIT.

A local activity-history reader that answers questions about what someone recently did on their computer. It uses readable summaries and, when available, detailed event records from the desktop.

In plain words
What is it for?
Use it to find recent contacts, work in progress, or where a task was left off on the computer.
Why use it?
It helps reconstruct recent work without relying on memory, while making clear when the history service is stopped or detailed records have expired.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to find recent contacts, work in progress, or where a task was left off on the computer.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/memtensor/memmy-agent/computer-history
About the project

Memmy is a local memory hub that gives multiple AI agents one shared, persistent context about their user. It helps people continue work across agents such as Claude Code, Codex, OpenClaw, and Hermes Agent. The catalogue entries are skills for using Memmy with supported agents.

MemTensor/memmy-agent · 2,212 stars · on GitHub · memmy.bot

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 MemTensor/memmy-agent --skill computer-history
Clone the repo
git clone --depth 1 https://github.com/MemTensor/memmy-agent

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 computer-history

README.md
[![agentmods](https://agentmods.dev/badge/skills/memtensor/memmy-agent/computer-history/github.svg)](https://agentmods.dev/skills/memtensor/memmy-agent/computer-history)
Your own site
<a href="https://agentmods.dev/skills/memtensor/memmy-agent/computer-history"><img src="https://agentmods.dev/badge/skills/memtensor/memmy-agent/computer-history/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 computer-history

Your own site · 80×15
<a href="https://agentmods.dev/skills/memtensor/memmy-agent/computer-history"><img src="https://agentmods.dev/badge/skills/memtensor/memmy-agent/computer-history.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 42 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,997 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. 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 $0.00042 $0.01997
Opus 5.5 $0.00017 $0.00799
Sonnet 5.5 $0.00008 $0.00399
Haiku 4.5 $0.00004 $0.00200

Measured 23d ago against content hash e1c96116ce89, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

computer-history 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 23d 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.

App/memmy-agent/src/skills/computer-history/SKILL.md · 167 lines

How it starts

The opening of the file, as written. The whole thing — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Computer History

Computer History keeps a local record of the user's desktop activity: readable per-window summaries, and the raw event streams those summaries were written from. They are two different things and answer different questions.

When to use

Use this skill when the user asks about their own recent activity — "who contacted me today", "what was I working on", "where did I leave off", "what did I do this morning" — or refers to Computer History directly.

First, find out where the data is and whether it is fresh

Call computer_history_status. It returns:

  • state — the recorder lifecycle, including running, paused, stopped and failed. If it is stopped and the user expects today's activity, say so rather than reporting an empty result as if nothing happened.
  • summary_directory — the readable summaries.
  • event_stream_root_path — the raw per-segment event streams.
  • privacy.raw_retention_hours — raw streams older than this are deleted. Summaries are not; beyond that window the summaries are all there is.
  • capture_health — current recorder signals and known limitations. A running recorder, a heartbeat or a healthy status does not prove that readable screen content was captured for the application and interval being investigated.

Compare the current date against what you find before treating anything as today's activity.

The two layers

<summary_directory>/
  <segment id>-10min-summary.md     one window, readable
  <6h window id>-6h-summary.md      a half-day, rolled up from the 10min ones

<event_stream_root_path>/
  <segment id>/
    events.jsonl                    every observed event, one JSON object per line
    metadata.json                   when the window started

Segment ids are UTC and aligned to the ten-minute grid, so 2026-09-08T08-20-00Z covers 08:20–08:30 UTC. Convert to the user's local time before reporting anything back to them.

How to answer

Broad questions — "what was I doing this afternoon", "what have I been working on". Read the 6h summaries first, then the 10min ones for a window that looks relevant. These may suffice for an overview. If the user asks for detail, verification or an explanation of missing activity, inspect the raw records before drawing a conclusion. For activity just performed, read the active segment and adjacent UTC segments even if no summary exists yet.

Read the full file on GitHub · 167 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.

  1. 23d ago Changed · +76 lines e1c96116ce89
  2. 1mo ago First seen · 91 lines · 42 tokens per session scan A 46f5030713cd

Subscribe to this mod's changes

computer-history is a skill published in the GitHub repository MemTensor/memmy-agent (2,212 stars, last pushed today), licensed MIT. It adds 42 tokens to every session and 1,997 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-21.

Related

computer-history compared with skills from other repositories

computer-history next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
computer-historyMemTensor/memmy-agentSkill2.2ktodayMITA42Claude Code, Codex
AgentMailagentic-in/elephant-agentSkill5852mo agononeA40Claude Code, Codex
Apple Notesagentic-in/elephant-agentSkill5852mo agononeA31Claude Code, Codex
Himalaya Emailagentic-in/elephant-agentSkill5852mo agononeA29Claude Code, Codex
YouTube Contentagentic-in/elephant-agentSkill5852mo agononeA28Claude Code, Codex
GitHub PR Workflowagentic-in/elephant-agentSkill5852mo agononeA29Claude Code, Codex
CLIagentic-in/elephant-agentSkill5852mo agononeC71Claude Code, Codex