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/rajanchavada/rosetta/agentic-memorynpx skills add RajanChavada/Rosetta --skill agentic-memorygit clone --depth 1 https://github.com/RajanChavada/RosettaWrote 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/rajanchavada/rosetta/agentic-memory)<a href="https://agentmods.dev/skills/rajanchavada/rosetta/agentic-memory"><img src="https://agentmods.dev/badge/skills/rajanchavada/rosetta/agentic-memory.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 | $0.00020 | $0.03472 |
| Opus 5 | $0.00010 | $0.01736 |
| Sonnet 5 | $0.00004 | $0.00694 |
| Haiku 4.5 | $0.00002 | $0.00347 |
Grade A, and why
agentic-memory 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 3d 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 — 580 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agentic Memory Skill
Overview
This skill provides a sophisticated memory management system that preserves tribal knowledge, maintains a clear memory hierarchy, and ensures important context never disappears. It implements THE MEMORY CONTRACT - explicit rules that all agents must follow.
THE MEMORY CONTRACT - AGENT BEHAVIOR RULES
Rule 1: Tribal Knowledge Preservation (CRITICAL)
NEVER let important learnings disappear.
When you encounter tribal knowledge (implicit rules, undocumented patterns, workarounds, "why we do X this way"):
-
PROMPT THE USER with clear reasoning:
This seems like tribal knowledge: [description]. Archive to .ai/archive/tribal-knowledge.md? -
AWAIT APPROVAL before archiving
-
Archive is APPEND-ONLY - never modify existing entries
Tribal knowledge indicators:
- "We always do it this way" (no documented reason)
- Undocumented workarounds for known issues
- Implicit architectural decisions
- Team conventions not in code or docs
- "Don't touch X without Y" warnings
- Historical context from old issues/PRs
Rule 2: Memory Hierarchy (STRICT ORDER)
The memory system has 5 levels. Always read and update in this order:
-
PROJECT_MEMORY.md - Architectural decisions, domain rules, "Why"
- Location:
.ai/memory/PROJECT_MEMORY.md - Content: Long-lived architectural truths
- Updates: Propose to user before modifying
- Location:
-
AUTO_MEMORY.md - Heuristics, patterns, gotchas, shortcuts
- Location:
.ai/memory/AUTO_MEMORY.md - Content: Agent-maintained learnings and patterns
- Updates: Append freely, promote to PROJECT_MEMORY.md when appropriate
- Location:
-
logs/daily/YYYY-MM-DD.md - Session activity, what was attempted
- Location:
.ai/logs/daily/YYYY-MM-DD.md - Content: Daily session logs with outcomes
- Updates: Auto-log for significant work
- Location:
-
archive/tribal-knowledge.md - Append-only tribal wisdom
- Location:
.ai/archive/tribal-knowledge.md - Content: Undocumented patterns and historical context
- Updates: User approval required, append-only
- Location:
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.
- 3d ago First seen · 580 lines · 20 tokens per session scan A ba83aa4ec6c3
agentic-memory is a skill published in the GitHub repository RajanChavada/Rosetta (3 stars, last pushed 3mo ago), licensed MIT. It adds 20 tokens to every session and 3,472 once invoked, about $0.0001 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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