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 ArkaAiAdmin/Agentic-Memory --skill memory-architecturegit clone --depth 1 https://github.com/ArkaAiAdmin/Agentic-MemoryWrote 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/arkaaiadmin/agentic-memory/memory-architecture)<a href="https://agentmods.dev/skills/arkaaiadmin/agentic-memory/memory-architecture"><img src="https://agentmods.dev/badge/skills/arkaaiadmin/agentic-memory/memory-architecture/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/arkaaiadmin/agentic-memory/memory-architecture"><img src="https://agentmods.dev/badge/skills/arkaaiadmin/agentic-memory/memory-architecture.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 | $0.00063 | $0.02709 |
| Opus 5.5 | $0.00025 | $0.01084 |
| Sonnet 5.5 | $0.00013 | $0.00542 |
| Haiku 4.5 | $0.00006 | $0.00271 |
Grade A, and why
memory-architecture 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.
| `sync_client.py` | 656 | HTTP sync client (urllib push/pull) | Cross-machine sync | How it starts
The opening of the file, as written. The whole thing — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memory Architecture (Maintainer)
A one-page mental model of the agentic-memory system, sized for someone about to change it.
The one-liner
Markdown files are the source of truth. SQLite is a derived index that can be rebuilt from them. The agent sees the system through MCP tools + hooks; the maintainer sees it through Python modules + cron jobs.
The three layers
┌──────────────────────────────────────────────────────────────────────┐
│ LAYER 3 — SURFACE │
│ 107 registered tools (17 CORE + 87 ADMIN + 3 DEPRECATED; 18 visible — 17 CORE + 1 memory_maintenance router) │
│ 4 user-facing hooks in hooks/ + 1 log helper module (_log_error.py) │
│ 39 cron scripts (all in `cron/` subdirectory) │
│ ~18 CLI commands │
└──────────────────────────────────────────────────────────────────────┘
│
▼
┌──────────────────────────────────────────────────────────────────────┐
│ LAYER 2 — PIPELINE (Python, ~104k LOC production, ~98k LOC test) │
│ │
│ WRITE PATH: │
│ save_pipeline.save_memory() (1,623 lines, saga → save/) │
│ → saga (5 steps: memory, FTS5, embeddings, chunks, KG) │
│ → audit log + cache invalidation + user_profile │
│ │
│ READ PATH: │
│ search_pipeline.py → search/orchestrator.py (1,995 LOC) │
│ → _expand_query (100+ synonym map) │
│ → 3-channel parallel: FTS5 + usearch + KG │
│ → _hybrid_fusion (6-factor weighted blend) │
│ → Qwen3-0.6B reranker (BGE-m3 fallback) │
│ → quality_gates (O(N log N) sliding-window near-dup dedup) │
│ │
│ SAFETY: │
│ memory_injection (4-category prompt-injection scan, retrieval) │
│ quality_gates (filter low-confidence results) │
└──────────────────────────────────────────────────────────────────────┘
│
▼
┌──────────────────────────────────────────────────────────────────────┐
│ LAYER 1 — STORAGE (SQLite at memory/memory.db, Schema v37) │
│ │
│ memories / memories_fts / memory_chunks / memory_chunks_fts │
│ memory_embeddings (BLOB, dim=256, f16, ssm_state) │
│ memory_vec_keys / memory_vec_idx (usearch BLOB) │
│ memory_field_crdt (v13) / arc_ghosts / arc_stats (v14) │
│ kg_facts / kg_entities / kg_edges / kg_extraction_stats │
│ backlinks (wiki-style [[link]] extraction) │
│ memory_audit_log / memory_ctr_feedback │
│ user_access_log / user_profile_access_log │
│ shared_memories (CRDT cross-agent pool) │
│ sync_log / task_queue / review_schedule / concept_drift │
│ drift_alarms (v15) / file_mtimes / schema_version │
│ ~49 user-visible tables (including FTS virtual and operational) │
└──────────────────────────────────────────────────────────────────────┘
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 · 155 lines · 63 tokens per session scan A 2ca432bacaa8
memory-architecture is a skill published in the GitHub repository ArkaAiAdmin/Agentic-Memory (0 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 63 tokens to every session and 2,709 once invoked, about $0.0003 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 2026-08-31.
Other skills, from other repositories
knowledge-ingest
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mem0-oss-to-platform
Plan, then execute, a migration of a project from the mem0 open-source / self-hosted SDK (local Memory class) to the mem0 Platform / hosted SDK (MemoryClient). TRIGGER when: the developer wants to move, switch, or migrate mem0 off OSS/self-hosted to the hosted API, e.g. "migrate my mem0 setup to the platform", "switch…
forget
Remove a personal fact, preference, relationship detail, topic, or prior event from Muse's active memory and stop existing copies or automations from bringing it back. Use for explicit requests such as 'forget that', 'don't remember this about me', or 'remove that from your memory'. Do not use when 'forget it' merely…
Cortex
LifeOS memory, prior-session recall, and learning capture. USE WHEN capture this learning, document this learning, what did we learn recently, recent learnings, cortex, knowledge, knowledge base, search knowledge, what do we know about, archive, harvest, knowledge status, develop note, add to knowledge, add a people…
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…