memory

memory is a skill for Claude Code, Codex from yc-software/qm. It costs 70 tokens per session (1,040 once invoked), scanned A, original, MIT.

A tool for deliberately searching, saving, and organizing long-term notes about people, projects, and durable facts. It is separate from ordinary files and complements the memory recalled automatically during a conversation.

In plain words
What is it for?
Use it to look up remembered context, save a fact immediately, or clean up outdated or wrong notes.
Why use it?
Important context can be missed by automatic memory or become stale and incorrect. This provides a way to find, record, correct, and curate what should be remembered.

Skill for Claude CodeCodex

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

Good fit Use it to look up remembered context, save a fact immediately, or clean up outdated or wrong notes.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/yc-software/qm/memory
About the project

QM is a shared work environment for coding agents that gives each employee and conversation an isolated workspace while allowing collaboration in Slack and on the web. Startups use it to run agents for individuals, teams, and company operations, with selectable harnesses and models. The catalogue entries extend QM with skills, instructions, and settings.

yc-software/qm · 15,434 stars · on GitHub · x.com

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 yc-software/qm --skill memory
Clone the repo
git clone --depth 1 https://github.com/yc-software/qm

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 memory

README.md
[![agentmods](https://agentmods.dev/badge/skills/yc-software/qm/memory/github.svg)](https://agentmods.dev/skills/yc-software/qm/memory)
Your own site
<a href="https://agentmods.dev/skills/yc-software/qm/memory"><img src="https://agentmods.dev/badge/skills/yc-software/qm/memory/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 memory

Your own site · 80×15
<a href="https://agentmods.dev/skills/yc-software/qm/memory"><img src="https://agentmods.dev/badge/skills/yc-software/qm/memory.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 70 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,040 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Data Exfiltration · line 46
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
How audits are shown
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 $0.00070 $0.01040
Opus 5.5 $0.00028 $0.00416
Sonnet 5.5 $0.00014 $0.00208
Haiku 4.5 $0.00007 $0.00104

Measured 3d ago against content hash d2bc5197dbbf, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

memory scanned grade A 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -fsS -X POST "$AGENT_API_URL/v1/memory/facts" \
skills-seed/memory/SKILL.md · 72 lines

How it starts

The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.

memory — search, write, and curate what you remember

Everything here goes through the typed memory tool. Memory is NOT a file: writing memory/MEMORY.md with files action write or shell commands lands on your computer's disk and is silently lost — the tool is the one real path.

Every turn already auto-recalls a bounded selection from your notebooks into "## What you remember" and auto-extracts facts after you reply. This skill is for what the automatic path misses:

  • Search (action: "search") — what you remember is bigger than what auto-recall injects. Search spans every notebook this conversation may read (personal, channel, org); when more than one is in reach, each hit is tagged with the notebook it came from. Matching is substring-based (all terms must match), so prefer distinctive terms (a name, a project) over sentences. An empty result means those terms found no match, not that nothing is recorded. Try fewer terms or alternate wording before concluding a fact is absent.
  • Read another notebook (action: "read", scope: "channel:…") — use the exact scope ID from a search result to load that authorized notebook. search accepts scope too, to narrow a query. Omit it to search all authorized notebooks or read the current notebook. Access comes from this turn's sharing policy; naming a scope never grants access. Other notebooks are read-only.
  • Write now (action: "add", facts: [{text}, …]) — when the user corrects you or tells you something they'll expect you to know later, persist it immediately instead of hoping post-turn extraction catches it. Write self-contained facts (who/what, with enough context to be useful cold). Duplicates are dropped; added in the reply is the count actually new.
  • Curate (action: "edit" with facts: [{id, text}, …], action: "delete" with ids) — search or read to get each fact's #id, then fix facts that changed and delete stale, duplicate, or wrong ones. A call naming any id that isn't in this conversation's notebook changes nothing and lists the bad ids. Curation is for quality — merging duplicates, deleting disproven facts — not for deleting things the user asked you to remember.

The notebook you write is this conversation's own (your personal one in a DM, the channel's in a channel). Other authorized notebooks can be searched/read, not rewritten here.

The org-admin write path uses the self-API instead, called with $AGENT_API_URL and $AGENT_API_TOKEN (both already in your environment on every turn — if they are unset, this instance has no self-API; say so rather than pretending).

Read the full file on GitHub · 72 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. 3d ago Changed · -13 lines d2bc5197dbbf
  2. 22d ago Changed 7b34de24f670
  3. 1mo ago First seen · 85 lines · 70 tokens per session scan A c288d4e518d7

Subscribe to this mod's changes

memory is a skill published in the GitHub repository yc-software/qm (15,434 stars, last pushed today), licensed MIT. It adds 70 tokens to every session and 1,040 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

wiki-maintainer

Maintain the OpenClaw memory wiki vault with repeatable pages, managed blocks, and source-backed updates.

openclaw/openclaw · 25 tokens

obsidian-vault-maintainer

Maintain an Obsidian-friendly memory wiki vault with wikilinks, frontmatter, and official Obsidian CLI awareness.

openclaw/openclaw · 32 tokens

harness-creator

Build, audit, and improve harnesses that make AI coding agents reliable: AGENTS.md/CLAUDE.md instruction files, feature/state tracking, verification gates, scope boundaries, session handoff, memory persistence, context budgets, tool-permission safety, and multi-agent coordination. Use this whenever a coding agent is…

walkinglabs/learn-harness-engineering · 142 tokens

capabilities

Your capability catalog — read this at boot. Lists the temporal date-range skills and the external integrations (reached via the loopback broker) available to you as a spawned worker, and exactly how to call each. Read-only. Consult it whenever you're unsure what tools/integrations you have or how to invoke them.

chaitanyagiri/munder-difflin · 69 tokens

temporal

Resolve ANY named time window — today, yesterday, thisWeek, lastWeek, last7Days, last30Days, last90Days, thisMonth, lastMonth, thisQuarter, lastQuarter, thisYear, lastYear, last12Months — or an arbitrary range (lastNdays / lastNweeks / lastNmonths) to a concrete ISO date range relative to your run time. Read-only: no…

chaitanyagiri/munder-difflin · 114 tokens

last30Days

Resolve "last30Days" to a concrete ISO date range relative to your run time — a rolling 30-day window ending today. Returns inclusive civil dates plus exact UTC instants so you have temporal context without computing dates by hand. Read-only: no writes, no network. Use before a "last 30 days" / trailing-month task…

chaitanyagiri/munder-difflin · 83 tokens