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 matrixorigin/memoria --skill deploymentgit clone --depth 1 https://github.com/matrixorigin/memoriaWrote 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/matrixorigin/memoria/deployment)<a href="https://agentmods.dev/skills/matrixorigin/memoria/deployment"><img src="https://agentmods.dev/badge/skills/matrixorigin/memoria/deployment/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/skills/matrixorigin/memoria/deployment"><img src="https://agentmods.dev/badge/skills/matrixorigin/memoria/deployment.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 10 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
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 | $0.00028 | $0.01662 |
| Opus 5.5 | $0.00011 | $0.00665 |
| Sonnet 5.5 | $0.00006 | $0.00332 |
| Haiku 4.5 | $0.00003 | $0.00166 |
Grade A, and why
deployment 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 1mo 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.
Services: API on `:8100`, MatrixOne on `:6001`. Verify: `curl http://localhost:8100/health` How it starts
The opening of the file, as written. The whole thing — 196 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Docker Compose (Single Instance)
cd Memoria
cp .env.example .env # Set MEMORIA_MASTER_KEY, MEMORIA_EMBEDDING_API_KEY
docker compose up -d
Services: API on :8100, MatrixOne on :6001. Verify: curl http://localhost:8100/health
Environment Variables
Required
| Variable | Description |
|---|---|
MEMORIA_MASTER_KEY |
Admin API key (min 16 chars) |
Database
| Variable | Default | Description |
|---|---|---|
MEMORIA_DB_HOST |
matrixone |
MatrixOne host |
MEMORIA_DB_PORT |
6001 |
MatrixOne port |
MEMORIA_DB_USER |
root |
Database user |
MEMORIA_DB_PASSWORD |
111 |
Database password |
MEMORIA_DB_NAME |
memoria |
Database name |
Embedding
| Variable | Default | Description |
|---|---|---|
MEMORIA_EMBEDDING_PROVIDER |
local |
local or openai |
MEMORIA_EMBEDDING_MODEL |
all-MiniLM-L6-v2 |
Model name |
MEMORIA_EMBEDDING_API_KEY |
— | Required if provider is openai (single-backend) |
MEMORIA_EMBEDDING_BASE_URL |
— | Custom endpoint, OpenAI-compatible (single-backend) |
MEMORIA_EMBEDDING_ENDPOINTS |
— | JSON array for multi-backend round-robin. When set, supersedes BASE_URL/API_KEY. Format: [{"url":"https://api1.example.com/v1","api_key":"sk-1"},{"url":"https://api2.example.com/v1","api_key":"sk-2"}]. All endpoints must serve the same model. Requests rotate round-robin; failed/rate-limited endpoints are skipped automatically. |
MEMORIA_EMBEDDING_DIM |
0 (auto) |
Embedding dimension |
Distributed
| Variable | Default | Description |
|---|---|---|
MEMORIA_INSTANCE_ID |
Random UUID | Unique instance ID. Set to Pod name in K8s |
MEMORIA_LOCK_TTL_SECS |
120 |
Distributed lock TTL. Heartbeat renews every TTL/3 |
Governance
| Variable | Default | Description |
|---|---|---|
MEMORIA_GOVERNANCE_ENABLED |
false |
Enable background governance scheduler |
MEMORIA_GOVERNANCE_PLUGIN_BINDING |
default |
Repository binding name |
MEMORIA_GOVERNANCE_PLUGIN_SUBJECT |
system |
Subject key for binding resolution |
MEMORIA_GOVERNANCE_PLUGIN_DIR |
— | Local plugin dir (dev mode, skips signature) |
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.
- 1mo ago First seen · 196 lines · 28 tokens per session scan A be088a6e9235
deployment is a skill published in the GitHub repository matrixorigin/memoria (614 stars, last pushed today), licensed Apache-2.0. It adds 28 tokens to every session and 1,662 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-30.
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