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.
npx agentmods add skills/chachamaru127/codex-harness/cursor-memnpx skills add Chachamaru127/codex-harness --skill cursor-memgit clone --depth 1 https://github.com/Chachamaru127/codex-harnessWrote 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.
[](https://agentmods.dev/skills/chachamaru127/codex-harness/cursor-mem)<a href="https://agentmods.dev/skills/chachamaru127/codex-harness/cursor-mem"><img src="https://agentmods.dev/badge/skills/chachamaru127/codex-harness/cursor-mem.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00065 | $0.01885 |
| Opus 5 | $0.00032 | $0.00942 |
| Sonnet 5 | $0.00013 | $0.00377 |
| Haiku 4.5 | $0.00006 | $0.00188 |
Grade A, and why
cursor-mem 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 4d 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.
1. ヘルスチェック: `curl http://127.0.0.1:37777/health` How it starts
The opening of the file, as written. The whole thing — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cursor-Mem Integration Skill
CursorからClaude-memを活用するスキル。Claude CodeとCursorで同じメモリデータベースを共有し、セッション間の知識を引き継ぎます。
🎯 使用場面
検索（読み取り）
- 過去の意思決定を確認: 「なぜこのアーキテクチャを選んだのか？」
- パターンの参照: 「以前はどのように実装したか？」
- バグ修正履歴: 「同様の問題を過去に解決したか？」
- 技術選定の理由: 「なぜこのライブラリを使っているのか？」
記録（書き込み）
- PMとしての判断をメモ: レビュー中の気付きや設計判断
- パターンの記録: 再利用可能なソリューション
- 引き継ぎ事項: 次のセッションやチームメンバーへの情報
- 学習事項: トラブルシューティングで得た知見
📋 利用可能なMCPツール
Cursor上でclaude-memのMCPツールを直接利用できます：
検索系
mcp__claude-mem__search: キーワードでメモリを検索mcp__claude-mem__timeline: 時系列で記録を取得mcp__claude-mem__get_recent_context: 最近の文脈を取得mcp__claude-mem__get_observation: 特定の観測を取得
書き込み系
mcp__claude-mem__create_entities: 新しいエンティティを作成mcp__claude-mem__create_relations: エンティティ間の関連を作成mcp__claude-mem__add_observations: 観測を追加
🔧 セットアップ
1. MCPラッパースクリプトの配置
# harness リポジトリ内に claude-mem-mcp がインストールされている前提
# 絶対パスで参照
HARNESS_PATH="/path/to/claude-code-harness"
2. Cursor MCP設定
プロジェクトルートに .cursor/mcp.json を作成：
{
"mcpServers": {
"claude-mem": {
"type": "stdio",
"command": "/absolute/path/to/claude-code-harness/scripts/claude-mem-mcp"
}
}
}
⚠️ 重要: command には絶対パスを指定してください。
3. Cursor再起動
設定後、Cursorを再起動してMCPサーバーを認識させます。
💡 使い方の例
詳細な使用例は examples.md を参照してください。
基本的な検索
ユーザー: 「認証方式の選定理由を確認したい」
Cursor（Composer）:
→ 直接 mcp__claude-mem__search を呼び出し（auto mode により自動有効化）
→ クエリ: "認証 JWT Supabase 選定理由"
→ 過去の決定記録（decisions）を取得
v2.1.7+: MCP auto mode がデフォルト有効のため、MCPSearch による事前検索は不要です。
気付きの記録
ユーザー: 「この実装パターンを記録しておいて」
Cursor（Composer）:
→ 直接 mcp__claude-mem__add_observations を呼び出し
→ タイプ: pattern
→ タグ: source:cursor, review, best-practice
→ 内容: 実装パターンの説明
🏷️ タグ規約
Claude CodeとCursorで統一されたタグ体系を使用します：
| タグ | 用途 |
|---|---|
source:cursor |
Cursorから記録された情報 |
source:claude-code |
Claude Codeから記録された情報 |
type:decision |
意思決定の記録 |
type:pattern |
再利用可能なパターン |
type:bug |
バグ修正の記録 |
type:review |
レビューでの気付き |
type:handoff |
引き継ぎ事項 |
What ships with it
2 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.
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.
- 4d ago First seen · 175 lines · 65 tokens per session scan A 8e87b5d15682
cursor-mem is a skill published in the GitHub repository Chachamaru127/codex-harness (2 stars, last pushed 6mo ago), licensed MIT. It adds 65 tokens to every session and 1,885 once invoked, about $0.0003 per session on Opus 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 2026-08-31.
Other skills, from other repositories
media-ingest
Ingest video, audio, PDF, book, screenshot, and GitHub repo content into the brain. Multi-format handling with entity extraction and backlink propagation. Covers video-ingest, youtube-ingest, and book-ingest subtypes.
mem0-oss-to-platform
Plan and then execute a migration of a project from the mem0 open-source / self-hosted SDK (the local Memory class) to the mem0 Platform / hosted / managed SDK (the MemoryClient class). Use this whenever a developer wants to move, switch, or migrate their mem0 usage off OSS/self-hosted to the hosted API — e.g.…
Cortex
Operate Cortex, the LifeOS memory system — the typed Knowledge Archive (People, Companies, Ideas, Research with typed related: links) plus recall of prior work sessions, ISAs, and conversations. Search, add, harvest, develop, ingest, distill, graph-navigate, recall. USE WHEN cortex, knowledge, knowledge base, search…
agent-memory
../../../engineering/agent-memory/skills/agent-memory/SKILL.md.
memory
Use when the user asks to remember, recall, forget, update, search, or inspect durable OpenSquilla memory, including profile facts in USER.md and long-term notes in MEMORY.md or memory//.md.
ha-data-stores
Map of Hope Agent's local data stores and safe read-only query workflow. Use when the user asks where Hope Agent stores data, wants to inspect sessions/messages/memory/logs/background jobs/knowledge indexes/settings, asks the model to query local app data, or debugging requires checking persisted state. Trigger…