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.
git clone --depth 1 https://github.com/monoes/monomindWrote 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/commands/monoes/monomind/memory-search)<a href="https://agentmods.dev/commands/monoes/monomind/memory-search"><img src="https://agentmods.dev/badge/commands/monoes/monomind/memory-search/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/monoes/monomind/memory-search"><img src="https://agentmods.dev/badge/commands/monoes/monomind/memory-search.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00017 | $0.00629 |
| Opus 5.5 | $0.00007 | $0.00252 |
| Sonnet 5.5 | $0.00003 | $0.00126 |
| Haiku 4.5 | $0.00002 | $0.00063 |
Grade A, and why
memory:memory-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 yesterday.
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 — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
memory search
Search stored memory using semantic, keyword, or hybrid search.
Usage
npx monomind memory search [options]
Options
| Flag | Short | Type | Default | Description |
|---|---|---|---|---|
--query |
-q |
string | — | Search query text |
--namespace |
-n |
string | default |
Namespace to search |
--limit |
-l |
number | 10 |
Maximum results to return |
--threshold |
— | number | 0.7 |
Minimum similarity threshold (0–1) |
--type |
-t |
string | hybrid |
Search type: semantic, keyword, hybrid |
--build-hnsw |
— | boolean | false |
Build pure-JS HNSW index before search (O(log n) vs O(n) linear) |
--format |
— | string | — | Output format: json |
Examples
# Semantic search
npx monomind memory search --query "authentication patterns"
# Keyword search
npx monomind memory search -q "JWT" --type keyword
# Hybrid search with namespace
npx monomind memory search -q "error handling" -n "project-x" --type hybrid
# Build HNSW index first for large datasets
npx monomind memory search -q "config" --build-hnsw --limit 20
# High-precision search with threshold
npx monomind memory search -q "OAuth flow" --threshold 0.9
# JSON output
npx monomind memory search -q "auth" --format json
Search Types
| Type | Description | Best For |
|---|---|---|
semantic |
Vector similarity search | Concept/meaning matching |
keyword |
BM25 full-text search | Exact term matching |
hybrid |
Combined semantic + keyword | General purpose (recommended) |
HNSW Index
Use --build-hnsw when searching large memory stores (1,000+ entries). The pure-JS HNSW index gives O(log n) approximate-nearest-neighbor queries (vs O(n) linear scan) after the one-time build cost.
MCP Tool
mcp__monomind__memory_pattern-search({
query: "authentication patterns",
namespace: "default",
limit: 10,
threshold: 0.7,
type: "hybrid"
})
See Also
memory store— store new memoriesmemory list— list all memoriesmemory retrieve— retrieve by exact key
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.
- yesterday First seen · 79 lines · 17 tokens per session scan A 16b61026e508
memory:memory-search is a command published in the GitHub repository monoes/monomind (23 stars, last pushed yesterday), licensed Apache-2.0. It adds 17 tokens to every session and 629 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-10-26.
Other commands, from other repositories
claude-flow-memory
Interact with Claude-Flow memory system.
sessions
Manage OpenAI Codex session history, aliases, and session metadata.
checkpoint
Create an identified recovery point and inspect exact restoration differences.
recall
Retrieve scoped lessons and evaluate their assumptions, conflicts, and applicability.
save-session
Save current session state to a dated file in /.codex/session-data/ so work can be resumed in a future session with full context.
checklist
Generate a custom checklist for the current feature based on user requirements.