Agent skill

Memory

by ambient-code in ambient-code/platform

Manage the auto-memory system for this project. An agent skill from ambient-code/platform.

MITAuto-check passed

Install Memory

skills CLI
$ npx skills add ambient-code/platform --skill memory -a claude-code

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

GitHub CLI
$ gh skill install ambient-code/platform memory --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/ambient-code/platform.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/memory .claude/skills/memory && 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
memory
GitHub stars
131
Token cost
~1k tokens
SKILL.md length
409 words
Files
2
Skills in repo
18
Repo updated
First seen
Licence
MIT

At a glance

Manage the auto-memory system for this project. An agent skill from ambient-code/platform.

  • Works in 4 steps: Read MEMORY.md to get the index → Count total memories by type (user,… → List the most recently modified files → …
  • You need to find a past decision
  • SKILL.md covers Usage, User Input, Memory Location and Subcommands, plus 3 more sections
  • Calls git

What it does

Memory is an agent skill from ambient-code/platform. Manage the auto-memory system for this project. Search, audit, prune, and create memories with proper frontmatter. Use when you need to find a past decision, check if memories are stale, clean up duplicates, add a new memory, or understand what context is available. Triggers on: "check memory", "what do we remember about", "find the memory about", "clean up memories", "audit memories", "add to memory", "is there a memory for".

Its SKILL.md is about 1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `evals/evals.json`).

The repository describes itself as: Vision/Mission https://ambient-code.ai : Virtual team management and collaboration platform. User guides: https://ambient-code.github.io/platform/. The licence is MIT.

When your agent uses it

  • You need to find a past decision
  • Check if memories are stale
  • Clean up duplicates
  • Add a new memory

Example prompts

  • “check memory”
  • “what do we remember about”
  • “find the memory about”
  • “/memory”

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Read MEMORY.md to get the index
  2. Count total memories by type (user, feedback, project, reference)
  3. List the most recently modified files
  4. Report: total count, breakdown by type, last modified dates

What it can do on your machine

Read from SKILL.md and the folder at commit e15afd3. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • git

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

  • Network

    No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.

    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

Memory loads about 1k tokens when it runs. Until then it costs about 109 tokens; SKILL.md has 409 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~109
When it runs · the whole SKILL.md, loaded when a task matches
~1k

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 ambient-code/platform at commit e15afd3, republished under its MIT licence (© ambient-code). 409 words, ~1,015 tokens.

Download SKILL.mdSave it as .claude/skills/memory/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
memory
description
Manage the auto-memory system for this project. Search, audit, prune, and create memories with proper frontmatter. Use when you need to find a past decision, check if memories are stale, clean up duplicates, add a new memory, or understand what context is available. Triggers on: "check memory", "what do we remember about", "find the memory about", "clean up memories", "audit memories", "add to memory", "is there a memory for".

Memory Management

Manage the auto-memory system for the Ambient Code Platform project.

Usage

text
/memory                    # Show summary of all memories
/memory search <query>     # Search for a topic
/memory audit              # Check for stale/duplicate memories
/memory prune              # Remove stale memories (with confirmation)
/memory add <topic>        # Create a new memory

User Input

text
$ARGUMENTS

Parse the subcommand from $ARGUMENTS. Default to summary if empty.

Memory Location

All memory files live at:

text
$HOME/.claude/projects/<project-slug>/memory/

Use the active project's slug (the repo path with / replaced by -).

The index file is MEMORY.md in that directory.

Subcommands

/memory — Summary
  1. Read MEMORY.md to get the index
  2. Count total memories by type (user, feedback, project, reference)
  3. List the most recently modified files
  4. Report: total count, breakdown by type, last modified dates
/memory search <query>
  1. Read MEMORY.md for the index
  2. Grep through all memory files for the query term
  3. Read matching files and show relevant excerpts
  4. Report: matching files with frontmatter (name, type, description)
/memory audit

Check for quality issues:

  1. Stale memories — project/reference memories older than 3 months may be outdated
  2. Duplicate memories — similar names or descriptions across files
  3. Missing frontmatter — files without proper name, description, type fields
  4. Orphaned files — memory files not referenced in MEMORY.md
  5. Broken links — MEMORY.md entries pointing to nonexistent files
  6. Oversized index — MEMORY.md approaching the 200-line truncation limit

Report each issue with the file path and suggested action.

/memory prune
  1. Run the audit checks
  2. Present findings to the user
  3. For each stale/duplicate/orphaned memory, ask: keep, update, or delete?
  4. Execute confirmed deletions
  5. Update MEMORY.md index accordingly

Never delete without explicit confirmation.

Show full SKILL.md (174 more words)Show less
/memory add <topic>
  1. Ask the user what they want to remember (if not clear from context)
  2. Determine the memory type (user, feedback, project, reference)
  3. Create a new file with proper frontmatter:
markdown
---
name: <descriptive name>
description: <one-line description for relevance matching>
type: <user|feedback|project|reference>
---

<memory content>
  1. Add an entry to MEMORY.md
  2. Verify the entry was added correctly

Memory Types

TypeWhat to storeWhen to save
userRole, preferences, knowledgeLearning about the user
feedbackCorrections, validated approachesUser corrects or confirms approach
projectDecisions, initiatives, deadlinesLearning project context
referencePointers to external systemsDiscovering external resources

What NOT to Store

  • Code patterns derivable from reading current code
  • Git history (use git log)
  • Debugging solutions (the fix is in the code)
  • Anything in CLAUDE.md
  • Ephemeral task details
  • Secrets or credentials (API keys, tokens, passwords, private keys, OAuth secrets)
  • Sensitive personal data unless explicitly required

Quality Guidelines

  • Keep MEMORY.md under 200 lines (truncation risk)
  • Each entry: one line, under 150 characters
  • Update existing memories rather than creating duplicates
  • Include absolute dates (not "next Thursday")
  • For feedback/project types: include Why: and How to apply: lines

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

Files

SKILL.md and 1 other file in skills/memory of ambient-code/platform.

  • SKILL.md
  • evals/evals.json

Open the folder on GitHubat commit e15afd3

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Questions about Memory

What does Memory do?

Manage the auto-memory system for this project. An agent skill from ambient-code/platform. Memory is an agent skill from ambient-code/platform. Manage the auto-memory system for this project.

When should I use Memory?

Memory fits situations like: you need to find a past decision; check if memories are stale; clean up duplicates; add a new memory.

How do I install Memory in Claude Code?

Run `npx skills add ambient-code/platform --skill memory -a claude-code`. Or copy the skill folder (skills/memory in ambient-code/platform) into .claude/skills/memory in your project. Claude Code loads it when a task matches its description.

How do I install Memory in Codex?

Run `npx skills add ambient-code/platform --skill memory -a codex`. Or copy the skill folder (skills/memory in ambient-code/platform) into .agents/skills/memory in your project. Codex loads it when a task matches its description.

Can I use Memory 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 ambient-code/platform --skill memory -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/memory, .gemini/skills/memory, .github/skills/memory and .opencode/skills/memory in your project.

What does Memory need to run?

Going by SKILL.md and its folder, Memory needs the command-line tools its instructions call (git).

Does Memory access the network?

SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Memory 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 Memory use?

Memory 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 Memory use?

About 1k tokens (SKILL.md is roughly 4.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

Who maintains Memory?

ambient-code (a GitHub organization) maintains it in ambient-code/platform, which has 131 GitHub stars. The repository holds 18 skills in this directory. The repository was last updated on October 6, 2026.

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