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 skills add MSApps-Mobile/claude-plugins --skill cowork-memgit clone --depth 1 https://github.com/MSApps-Mobile/claude-pluginsWrote 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/msapps-mobile/claude-plugins/cowork-mem)<a href="https://agentmods.dev/skills/msapps-mobile/claude-plugins/cowork-mem"><img src="https://agentmods.dev/badge/skills/msapps-mobile/claude-plugins/cowork-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 5.1 | $0.00157 | $0.01834 |
| Opus 5 | $0.00078 | $0.00917 |
| Sonnet 5 | $0.00031 | $0.00367 |
| Haiku 4.5 | $0.00016 | $0.00183 |
Grade A, and why
cowork-mem 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 6d 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.
How it starts
The opening of the file, as written. The whole thing — 218 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cowork-Mem: Persistent Memory for Cowork
You have access to a persistent memory system that survives across Cowork sessions. It stores observations (decisions, file edits, insights, errors, notes) in a SQLite database with full-text search and semantic (TF-IDF) search, organized into sessions.
How It Works
Memory is automatic — you don't need to manually trigger it every session. Three session hooks run in the background:
- SessionStart: auto-recalls the last session summary before you begin
- PostToolUse: auto-captures meaningful file edits, bash commands, and task completions as they happen
- PreCompact: saves a timestamped marker before context is compacted
This means the memory fills itself. Your job is to add the why — decisions, insights, errors — that the hook can't infer automatically.
The Memory Script
All memory operations go through a single script:
python3 {SKILL_DIR}/scripts/memory_store.py <command> [args]
The database lives at ~/.claude/.cowork-mem/memory.db and persists on the
user's machine across sessions. The COWORK_MEM_DB environment variable
overrides the default path if set.
Semantic Search
In addition to keyword search, you have vector search using TF-IDF similarity:
COWORK_MEM_DB=~/.claude/.cowork-mem/memory.db \
python3 {SKILL_DIR}/scripts/vector_search.py "authentication middleware pattern" --limit 8
Use semantic search when:
- You want conceptually related observations (not just keyword matches)
- The user asks vague questions like "what do we know about auth?"
- You're exploring what the memory knows about a topic before diving into a task
Core Workflow
1. Session Start — Recall First
The SessionStart hook auto-runs session-start before you begin. If memory
was loaded, you'll already have context. If working manually:
python3 {SKILL_DIR}/scripts/memory_store.py session-start --project "project-name"
Briefly tell the user what you remember: "Last time we worked on X, we decided Y and were in the middle of Z." Keep it to 1-2 sentences — don't dump everything.
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.
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.
- 6d ago First seen · 218 lines · 157 tokens per session scan A 2e49bbccd563
cowork-mem is a skill published in the GitHub repository MSApps-Mobile/claude-plugins (9 stars, last pushed 11d ago), licensed MIT. It adds 157 tokens to every session and 1,834 once invoked, about $0.0008 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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