workspace-agent-memory-save

workspace-agent-memory-save is a skill for Claude Code, Codex from eaglesakura/agent-skills. It costs 142 tokens per session (865 once invoked), scanned A, original, MIT.

A workspace memory tool that saves research results and conversation summaries as Markdown files in .ai-agent/memory/.

In plain words
What is it for?
It is for recording findings, decisions, evidence, and handover notes in a structured file, updating an existing memory when one already covers the topic.
Why use it?
It keeps important conclusions from being lost in chat history and makes them reusable in later chats or by other agents.

Skill for Claude CodeCodex

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

Good fit It is for recording findings, decisions, evidence, and handover notes in a structured file, updating an existing memory when one already covers the topic.

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Install with agentmods
npx agentmods add skills/eaglesakura/agent-skills/workspace-agent-memory-save
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 eaglesakura/agent-skills --skill workspace-agent-memory-save
Clone the repo
git clone --depth 1 https://github.com/eaglesakura/agent-skills

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 workspace-agent-memory-save

README.md
[![agentmods](https://agentmods.dev/badge/skills/eaglesakura/agent-skills/workspace-agent-memory-save.svg)](https://agentmods.dev/skills/eaglesakura/agent-skills/workspace-agent-memory-save)
Your own site
<a href="https://agentmods.dev/skills/eaglesakura/agent-skills/workspace-agent-memory-save"><img src="https://agentmods.dev/badge/skills/eaglesakura/agent-skills/workspace-agent-memory-save.svg" alt="Measured on agentmods" height="20"></a>
Per session 142 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 865 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 $0.00142 $0.00865
Opus 5 $0.00071 $0.00432
Sonnet 5 $0.00028 $0.00173
Haiku 4.5 $0.00014 $0.00086

Measured 8d ago against content hash ee3c78bb60e3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

workspace-agent-memory-save 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 8d 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.

packages/agentic-workspace/.apm/skills/workspace-agent-memory-save/SKILL.md · 55 lines

What it actually says

Workspace / Agent Memory Save

長い調査や複数ターンの結論は、チャット履歴だけに置くと失われやすい。 後続チャット・別 Agent・人間が ## 見出し単位で拾える形で .ai-agent/memory/ に残す。 ベースは @this/.ai-agent/memory/workspace-agent-temporary)。

いつ使うか / いつ保存するか

  • ユーザーが調査を依頼し、結果をまとめた直後
  • 「保存」「memory」「引き継ぎ」「メモ化」などを求められたとき
  • 同じテーマを別チャットで続ける可能性が高いとき

一時スクリプトや生ログだけなら workspace-agent-temporary の提案どおり .ai-agent/tmp/ で足りる。 再利用したい結論・判断材料・引用があるときが Memory の対象である。

出力先

  • パス: @this/.ai-agent/memory/{文脈を示す短い名前}.md
  • .ai-agent/ の存在・ひな形は workspace-layout、用途別の配置判断は workspace-agent-temporary(常に @this/.ai-agent、単数形)
  • 同テーマの Memory が既にある場合は 新規作成せず更新する
  • 用済みになったら .ai-agent/memory/done/ へ移してよい

ファイル名

  • 内容が推測できる短い kebab-case(例: app-dependency-update-precheck-2026-05-09.md
  • 空白や曖昧な memo.md / notes.md は避ける

ドキュメントの書き方

  • テンプレート に従う
  • 先頭の # は会話内容の一言まとめ
  • 本体は ##(レベル2)でトピック分割する
    • 後続ロードは ## 単位で概要把握される想定のため、1 見出しに論点が混ざらないようにする
  • 箇条書き・表を中心に、結論が先に読めるように書く
  • 根拠となるコードやコマンドは引用・実行内容として残す(パスや条件が再現できる粒度)

手順

  1. workspace-layout / workspace-agent-temporary に従い @this/.ai-agent/memory/ の実パスを決める
  2. 既存 Memory の有無を確認し、あれば更新・なければ新規作成する
  3. テンプレートに沿って見出しを切り、調査結果または引き継ぎサマリを書く
  4. 保存先パスをユーザー(または親 Agent)に報告する
Files

What ships with it

4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 8d ago First seen · 55 lines · 142 tokens per session scan A ee3c78bb60e3

Subscribe to this mod's changes

workspace-agent-memory-save is a skill published in the GitHub repository eaglesakura/agent-skills (2 stars, last pushed 2d ago), licensed MIT. It adds 142 tokens to every session and 865 once invoked, about $0.0007 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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