Agent skill

Session Memory

by oaustegard in oaustegard/claude-skills

Maintains a structured running-notes document during long work sessions.

MITAuto-check passedAgent Workflows

Install Session Memory

skills CLI
$ npx skills add oaustegard/claude-skills --skill session-memory -a claude-code

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

GitHub CLI
$ gh skill install oaustegard/claude-skills session-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/oaustegard/claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/session-memory .claude/skills/session-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
session-memory
GitHub stars
150
Token cost
~1.6k tokens
SKILL.md length
603 words
Files
2
Skills in repo
93
Repo updated
First seen
Licence
MIT

At a glance

Maintains a structured running-notes document during long work sessions.

  • Works in 5 steps: Read the existing note (if any) via… → Update in place. Edit the relevant… → Prioritize user corrections. When the… → …
  • The user says session notes
  • SKILL.md covers When to Use, Template (Fixed Sections), Storage and Update Discipline, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Session Memory is an agent skill from oaustegard/claude-skills. Maintains a structured running-notes document during long work sessions. Use when the user says "session notes", "update notes", "start session notes", "show session notes", or when you recognize the current session has accumulated enough state (decisions, corrections, files touched, errors) that it risks being lost under context pressure. Stores notes as a procedure memory tagged [session-memory, active] so they survive container death within the same session thread.

Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `CHANGELOG.md`).

It sits in Agent Workflows, covering Agent memory and Session handoff. The repository describes itself as: My collection of Claude skills. The licence is MIT.

When your agent uses it

  • The user says session notes
  • Start session notes
  • Show session notes
  • You recognize the current session has accumulated enough state (decisions

Example prompts

  • “session notes”
  • “update notes”
  • “start session notes”
  • “/session-memory”

Requirements

  • Python 3

Workflow steps

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

  1. Read the existing note (if any) via `recall(tags_all=["session-memory",
  2. Update in place. Edit the relevant sections; append to ## Worklog.
  3. Prioritize user corrections. When the user pushes back or corrects an
  4. Deduplicate against stash and explicit memories. If an item is already
  5. Supersede, don't append. Write the full updated document back via

What it can do on your machine

Read from SKILL.md and the folder at commit 559a6cd. 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

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown and python).

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

  • Network

    No URLs in SKILL.md.

    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

Session Memory loads about 1.6k tokens when it runs. Until then it costs about 122 tokens; SKILL.md has 603 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~122
When it runs · the whole SKILL.md, loaded when a task matches
~1.6k

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 oaustegard/claude-skills at commit 559a6cd, republished under its MIT licence (© oaustegard). 603 words, ~1,562 tokens.

Download SKILL.mdSave it as .claude/skills/session-memory/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
session-memory
description
Maintains a structured running-notes document during long work sessions. Use when the user says "session notes", "update notes", "start session notes", "show session notes", or when you recognize the current session has accumulated enough state (decisions, corrections, files touched, errors) that it risks being lost under context pressure. Stores notes as a procedure memory tagged [session-memory, active] so they survive container death within the same session thread.
metadata.version
0.1.0

Session Memory - Running Notes

Maintain a single structured markdown document that tracks what is happening right now in the current work session. This is within-session continuity, distinct from remember() (cross-session semantic memory) and stash (coarse checkpoint).

When to Use

Invoke on any of these triggers:

  • User says "session notes", "update notes", "start session notes", "show session notes", "note the session", "write it down"
  • User indicates they want continuity across context compression: "before you forget", "write that down", "for when context gets compressed"
  • You have independently completed a meaningful block of work (file edits, a bugfix, a design choice, a reversal after correction) and no note has been updated for a while

Do NOT invoke for:

  • One-off answers with no follow-up
  • Cross-session persistence — that's remember()
  • Coarse checkpoints intended for another session to resume — that's stash

Template (Fixed Sections)

Every session note uses exactly these sections, in this order, with these headers. Preserve the structure on every update. Never rename or reorder sections. Update the content within sections; leave empty sections present with a single _(nothing yet)_ placeholder.

markdown
# Session: {short title, 3-8 words, derived from the initial task}

## Current State
_What is actively being worked on right now. Explicit next step._

## Task Specification
_What the user originally asked for. Constraints, acceptance criteria,
design decisions that framed the work._

## Files and Functions
_Important paths touched or referenced, one per line, with a one-line
note on what they contain and why they matter._

## Errors & Corrections
_Errors encountered and how they were fixed. User corrections to my
approach — these have priority over routine progress entries._

## Key Decisions
_Choices made during the session with their rationale. One bullet per
decision. Lead with the choice, then the why._

## Worklog
_Terse, append-only, chronological. One line per attempt or step.
Prefix with ✓ (done), ✗ (failed), → (in progress), or ↺ (reverted)._

Storage

Persist as a procedure memory via the remembering skill, so notes survive container death within the session thread.

python
from remembering.scripts import remember, recall, supersede

# First write in a session: create the memory
note_id = remember(
    note_markdown,
    "procedure",
    tags=["session-memory", "active"],
    priority=1,
)

# Subsequent updates: find the active note and supersede it
existing = recall(tags_all=["session-memory", "active"], n=1)
if existing:
    note_id = supersede(existing[0].id, updated_markdown, "procedure",
                        tags=["session-memory", "active"], priority=1)

Session boundary: when the user says "session done", "wrap up", "end session", or the conversation is clearly winding down, retag the active note from active to archived by superseding it with the same body and tags=["session-memory", "archived"].

One note is active at a time. If recall(tags_all=["session-memory", "active"]) returns more than one, the oldest is stale — archive it before updating the current one.

Update Discipline

On each invocation:

  1. Read the existing note (if any) via recall(tags_all=["session-memory", "active"], n=1). Work from its current body — do not regenerate from scratch.
  2. Update in place. Edit the relevant sections; append to ## Worklog. Do not drop prior content unless it is now wrong (then move the correction to ## Errors & Corrections).
  3. Prioritize user corrections. When the user pushes back or corrects an approach, that goes into ## Errors & Corrections before other updates.
  4. Deduplicate against stash and explicit memories. If an item is already captured in a stash or a remember() call, reference it by ID rather than restating. Notes are supplementary, not duplicative.
  5. Supersede, don't append. Write the full updated document back via supersede(). This keeps exactly one active note per session.
Show full SKILL.md (219 more words)Show less

Budget

Target ~12K tokens for the note document. Prefer concise phrasing, but do not truncate substantive content to hit the target — trigger ## Key Decisions consolidation (collapse related bullets) before cutting. If the document exceeds ~20K tokens, compress ## Worklog first (merge consecutive ✓ entries into a single summary line, keep corrections and decisions intact).

Rationale: we run on 200K–1M context models, so the original 2K budget from the issue spec was over-constrained. 12K matches Claude Code's upstream design and leaves ample room for the surrounding conversation.

Surface to User

When the user asks to "show session notes", print the current note body verbatim in a fenced code block. Do not paraphrase.

When updating silently (you triggered it yourself), confirm with a single line: Updated session notes (note id: <short-id>). Do not dump the full body unsolicited.

Invariants

  • Section headers and order are fixed. Updates change content, not structure.
  • User corrections take priority over routine progress in ordering and detail.
  • Notes do not duplicate what is already in stash or explicit memories.
  • Manual invocation always works. Automatic triggers are a convenience, not a requirement.
  • Exactly one session-memory + active memory exists per session. Stale actives are archived, not left dangling.
  • remembering — cross-session memory store (where these notes persist)
  • stash-resume-protocol (ops) — coarse session checkpoints
  • context-hygiene (ops) — when and what to offload from context

© oaustegard, 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 session-memory of oaustegard/claude-skills.

  • SKILL.md
  • CHANGELOG.md

Open the folder on GitHubat commit 559a6cd

Compare with similar skills

Session Memory next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Session Memory compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Session Memory this skilloaustegard/claude-skills150—~1.6kAutomated safety check: PassMIT
Beads Task Memorygastownhall/beads28k—~1.2kAutomated safety check: PassMIT
Session History Searchslopus/happy24k—~3.1kAutomated safety check: PassMIT
Memori Long-Term MemoryMemoriLabs/Memori17k—~2kAutomated safety check: NotesCustom licence
Coding Agent Session Findercode-yeongyu/oh-my-openagent70k—~2.8kAutomated safety check: PassCustom licence
Deja History Searchvshulcz/deja-vu1.1k1 repos~1.3kAutomated safety check: PassMIT

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Categories

Questions about Session Memory

What does Session Memory do?

Maintains a structured running-notes document during long work sessions. Session Memory is an agent skill from oaustegard/claude-skills. Maintains a structured running-notes document during long work sessions.

When should I use Session Memory?

Session Memory fits situations like: the user says session notes; start session notes; show session notes; you recognize the current session has accumulated enough state (decisions.

How do I install Session Memory in Claude Code?

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

How do I install Session Memory in Codex?

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

Can I use Session 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 oaustegard/claude-skills --skill session-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/session-memory, .gemini/skills/session-memory, .github/skills/session-memory and .opencode/skills/session-memory in your project.

What does Session Memory need to run?

SKILL.md names no scripts, command-line tools or credentials: Session Memory is instructions for the agent only. Our summary lists: Python 3.

Does Session Memory access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Session 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 Session Memory use?

Session 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 Session Memory use?

About 1.6k tokens (SKILL.md is roughly 6.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Session Memory?

Skills that share tags, products or a category with Session Memory: Beads Task Memory (gastownhall/beads, 28k stars), Session History Search (slopus/happy, 24k stars), Memori Long-Term Memory (MemoriLabs/Memori, 17k stars) and Coding Agent Session Finder (code-yeongyu/oh-my-openagent, 70k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Session Memory?

oaustegard (a GitHub user) maintains it in oaustegard/claude-skills, which has 150 GitHub stars. The repository holds 93 skills in this directory. The repository was last updated on October 2, 2026.

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