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/msapps-mobile/claude-plugins/mem-searchnpx skills add MSApps-Mobile/claude-plugins --skill mem-searchgit 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/mem-search)<a href="https://agentmods.dev/skills/msapps-mobile/claude-plugins/mem-search"><img src="https://agentmods.dev/badge/skills/msapps-mobile/claude-plugins/mem-search.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 | $0.00088 | $0.00479 |
| Opus 5 | $0.00044 | $0.00239 |
| Sonnet 5 | $0.00018 | $0.00096 |
| Haiku 4.5 | $0.00009 | $0.00048 |
Grade A, and why
mem-search 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 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.
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.
What it actually says
mem-search: Smart Memory Search
Search cowork-mem with two complementary modes — keyword FTS5 and semantic TF-IDF. Use both for important queries; keyword finds exact matches, semantic finds related ideas.
Quick Search
Keyword (FTS5 — fast, exact):
python3 {SKILL_DIR}/scripts/memory_store.py search "<query>" --limit 10
Semantic (TF-IDF — finds related concepts):
COWORK_MEM_DB=~/mnt/.claude/.cowork-mem/memory.db \
python3 {SKILL_DIR}/scripts/vector_search.py "<query>" --limit 10
Fetch full detail on specific results:
python3 {SKILL_DIR}/scripts/memory_store.py get obs_abc123 obs_def456
When to Use Each Mode
| Mode | Best for |
|---|---|
| Keyword | Exact tool names, file paths, error messages |
| Semantic | "what did we decide about auth", "any DB issues", "deployment problems" |
Search Workflow
- Start with semantic search — it catches paraphrases
- If results are weak, run keyword search as a fallback
- For any result worth reading in full, call
get <id> - Synthesize what you found into 1-2 sentences before acting on it
Filter by Type
# Only past decisions
python3 {SKILL_DIR}/scripts/memory_store.py search "<query>" --type decision
# Only errors and solutions
python3 {SKILL_DIR}/scripts/memory_store.py search "<query>" --type error
Types: decision, file_edit, tool_use, insight, error, note, summary
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 · 59 lines · 88 tokens per session scan A 2cbf5d6c61d6
mem-search is a skill published in the GitHub repository MSApps-Mobile/claude-plugins (9 stars, last pushed 8d ago), licensed MIT. It adds 88 tokens to every session and 479 once invoked, about $0.0004 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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