Orkas is a desktop application for commanding a team of AI agents through one chat, with a commander model assigning work to specialist agents in parallel or in sequence. People use it to coordinate research, writing, presentations, and software tasks while keeping files on their computer. The catalogue includes skills for extending the agents available to Orkas.
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 Orkas-AI/Orkas --skill memory-managergit clone --depth 1 https://github.com/Orkas-AI/OrkasWrote 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/orkas-ai/orkas/memory-manager)<a href="https://agentmods.dev/skills/orkas-ai/orkas/memory-manager"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas/memory-manager/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/orkas-ai/orkas/memory-manager"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas/memory-manager.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00002 | $0.00735 |
| Opus 5 | $0.00001 | $0.00367 |
| Sonnet 5 | $0.00000 | $0.00147 |
| Haiku 4.5 | $0.00000 | $0.00073 |
Grade A, and why
memory-manager 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 8d 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 — 31 lines — stays where its author put it; the contents beside it link to each section on GitHub.
memory-manager
Use this protocol only for durable context that should affect future conversations. Do not persist current task progress, temporary plans, one-off status, or TODO and dependency state.
Choose the destination
Apply both axes: directive versus descriptive, and global versus project scope. Choose exactly one destination for each item unless the user explicitly requests two distinct durable records. Do not mirror descriptive knowledge into project instructions merely because later work should use that knowledge; "base future proposals on this fact" remains project memory, not a standing rule.
- Use
cross_session_memorywithtarget: "agent"for Commander's durable orchestration lessons and user corrections about how Commander should coordinate, route, synthesize, or ask for missing information. - Use
cross_session_memorywithtarget: "user"for stable global user facts and preferences: identity, communication style, expertise, tech stack, or a preference that should apply outside the current project. - Use
cross_session_memorywithtarget: "shared"for stable non-user global facts, shared decisions and conventions, or repository and environment facts that every agent should know. - In a Project conversation, use
cross_session_memorywithtarget: "project"for durable descriptive project facts, decisions, outcomes, milestones, and conventions. - Use
project_instructionsfor durable directives that should steer every future conversation in this project: its goal, scope, standing rules, and project-specific preferences or constraints.
Do not duplicate a global user preference or a descriptive project fact in project instructions. Do not put Commander-specific orchestration lessons in user or shared memory. Put concrete work items, live progress, and TODO status in project_tasks, not memory or project instructions.
Mutate safely
- Resolve the intended store, target, and current record. Use a read-only lookup when the exact record or current project instructions are not already identified; never invent a record identifier.
- Add new durable context, replace a correction to an existing record, and remove only an exact intended record. If several records match a replace or remove request, show the candidates and ask one concise clarifying question without mutating any of them.
- Treat
project_instructionsas a full replacement. Preserve every existing rule that still applies and send the complete intended text, not a partial patch. - Write in the user's current UI language while preserving proper nouns, commands, paths, URLs, and exact quoted text.
- Name the exact tool, operation, and target even when tools are unavailable and you can only propose the mutation. A prose label such as "project memory" is not a substitute for
cross_session_memorywithtarget: "project". - Call the exact mutation tool when available. Claim that a change succeeded only after its tool result confirms success; otherwise report the error or describe the intended mutation as a proposal.
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.
- 8d ago First seen · 31 lines · 2 tokens per session scan A 6f6dc8f418c5
memory-manager is a skill published in the GitHub repository Orkas-AI/Orkas (1,885 stars, last pushed yesterday), licensed MIT. It adds 2 tokens to every session and 735 once invoked, about $0.0000 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.
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