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 RobinNorberg/oh-my-copilot --skill remembergit clone --depth 1 https://github.com/RobinNorberg/oh-my-copilotWrote 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/robinnorberg/oh-my-copilot/remember)<a href="https://agentmods.dev/skills/robinnorberg/oh-my-copilot/remember"><img src="https://agentmods.dev/badge/skills/robinnorberg/oh-my-copilot/remember.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 5.1 | $0.00020 | $0.00295 |
| Opus 5 | $0.00010 | $0.00148 |
| Sonnet 5 | $0.00004 | $0.00059 |
| Haiku 4.5 | $0.00002 | $0.00030 |
Grade A, and why
remember 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 2d 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.
This is a copy
100% identical to remember — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Remember
Use this skill when the user wants to preserve or organize useful knowledge discovered during a session.
Goal
Promote durable, reusable knowledge into the right memory surface instead of leaving it buried in chat history.
Memory surfaces
- Project memory — durable team/project knowledge
- Notepad priority — short high-signal context for the next turns
- Notepad working — temporary active-session notes
- Docs / AGENTS / CLAUDE files — durable instructions and conventions when they truly belong there
Workflow
- Gather the relevant session findings.
- Classify each item:
- durable project fact
- temporary working note
- operator preference or instruction
- duplicate / stale / conflicting information
- Propose the best destination for each item.
- Write or update only the appropriate memory surface.
- Call out duplicates or conflicts that should be cleaned up.
Rules
- Do not dump everything into one store.
- Prefer project memory for durable team knowledge.
- Prefer notepad for short-lived working context.
- Keep entries concise and actionable.
- If something is uncertain, mark it as uncertain rather than storing it as fact.
Output
- What was stored
- Where it was stored
- Any duplicates/conflicts found
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.
- 2d ago First seen · 42 lines · 20 tokens per session scan A 611e56e4eb01
remember is a skill published in the GitHub repository RobinNorberg/oh-my-copilot (5 stars, last pushed today), licensed MIT. It adds 20 tokens to every session and 295 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to remember, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
lane-memory
A file-based store for durable project facts that cannot be reliably inferred from source code or its module map.
conversation-memory
Persistent memory systems for LLM conversations including short-term, long-term, and entity-based memory.
data-structure-protocol
Give agents persistent structural memory of a codebase — navigate dependencies, track public APIs, and understand why connections exist without re-reading the whole repo.
ejentum-reasoning-harness
MCP server exposing four cognitive harness modes (reasoning, code, anti-deception, memory). Each call returns an engineered scaffold (failure pattern, procedure, suppression vectors, falsification test) the agent ingests before generating.
geminiignore-finops
Configure and optimize .geminiignore files for AI context window efficiency and token cost reduction (FinOps).
hierarchical-agent-memory
Scoped CLAUDE.md memory system that reduces context token spend. Creates directory-level context files, tracks savings via dashboard, and routes agents to the right sub-context.