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/yonatangross/orchestkit/memorynpx skills add yonatangross/orchestkit --skill memorygit clone --depth 1 https://github.com/yonatangross/orchestkitWrote 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/yonatangross/orchestkit/memory)<a href="https://agentmods.dev/skills/yonatangross/orchestkit/memory"><img src="https://agentmods.dev/badge/skills/yonatangross/orchestkit/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 | $0.00064 | $0.01827 |
| Opus 5 | $0.00032 | $0.00914 |
| Sonnet 5 | $0.00013 | $0.00365 |
| Haiku 4.5 | $0.00006 | $0.00183 |
Grade A, and why
memory scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memory - Read & Access Operations
Unified read-side memory skill with subcommands for searching, loading, syncing, history, and visualization.
Cross-session read strategy (Opus 5 / CC 2.1.111+): Opus 5 reads filesystem memory reliably across sessions. When loading context at session start, prefer the layered read order:
~/.claude/projects/<slug>/memory/MEMORY.md(durable index — load first, always).claude/chain/state.json+ most recentNN-*.jsonhandoff (session continuation)- MCP
mcp__memory__search_nodesfor anything the filesystem index doesn't answer (typed graph traversal)Layer 1 is cheap (small index file), Layer 2 is scoped (session-specific), Layer 3 is selective (only when needed). Avoid dumping the full knowledge graph into context — use the index to narrow the search first.
Argument Resolution
SUBCOMMAND = "$ARGUMENTS[0]" # First token: search, load, history, viz, status
QUERY = "$ARGUMENTS[1]" # Second token onward: search query or flags
# $ARGUMENTS is the full string (CC 2.1.59 indexed access)
Usage
/ork:memory search <query> # Search knowledge graph
/ork:memory load # Load context at session start
/ork:memory history # View decision timeline
/ork:memory viz # Visualize knowledge graph
/ork:memory status # Show memory system health
CRITICAL: Use AskUserQuestion When No Subcommand
If invoked without a subcommand, ask the user what they want:
AskUserQuestion(
questions=[{
"question": "What memory operation do you need?",
"header": "Operation",
"options": [
{"label": "search", "description": "Search decisions and patterns in knowledge graph"},
{"label": "load", "description": "Load relevant context for this session"},
{"label": "history", "description": "Decision timeline + knowledge-graph viz (--mermaid)"},
{"label": "status", "description": "Check memory system health"}
],
"multiSelect": false
}]
)
What ships with it
13 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/memory-commands.md 4.2 KB
- references/mermaid-patterns.md 8.7 KB
- references/session-resume-patterns.md 912 B
- rules/_sections.md 344 B
- rules/deduplication-strategy.md 1.8 KB
- rules/entity-extraction-patterns.md 1.9 KB
- scripts/graph-utils.mjs 6.0 KB runs code
- scripts/playground-template.html 57 KB
- scripts/render-graph.mjs 11 KB runs code
- scripts/render-playground.mjs 11 KB runs code
- scripts/staleness_cron.py 5.4 KB runs code
- scripts/staleness_lib.py 6.5 KB runs code
- test-cases.json 2.5 KB
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 · 178 lines · 64 tokens per session scan A 64bf61e95742
memory is a skill published in the GitHub repository yonatangross/orchestkit (225 stars, last pushed yesterday), licensed MIT. It adds 64 tokens to every session and 1,827 once invoked, about $0.0003 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 2026-09-03.
Other skills, from other repositories
semantix
Install and use the semantix memory kernel as a middleware in your agent: extract user preferences / workflows / experience from past sessions, retrieve and inject them on demand. One binary + your agent's own tools.
forgetful-recall
Recall past knowledge before working — prior decisions, solved problems, preferences, project history. Use at the start of any task, when the user references earlier work, when re-entering a project after time away, or before proposing an approach that may already have history. Covers query shaping, scoping…
session-search
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moraine
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semantic-search
Zero-dependency TF-IDF search across MUSE memory, roles, and skills. Use when user wants to find information across their project context.
sitrep
Situational awareness — where am I, what was I doing, what's next. Context recovery after compression, confusion, or mid-session reorientation.