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.
git clone --depth 1 https://github.com/agentsea/flashbackerWrote 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/commands/agentsea/flashbacker/remember)<a href="https://agentmods.dev/commands/agentsea/flashbacker/remember"><img src="https://agentmods.dev/badge/commands/agentsea/flashbacker/remember/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/commands/agentsea/flashbacker/remember"><img src="https://agentmods.dev/badge/commands/agentsea/flashbacker/remember.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 | $0.00000 | $0.00337 |
| Opus 5.5 | $0.00000 | $0.00135 |
| Sonnet 5.5 | $0.00000 | $0.00067 |
| Haiku 4.5 | $0.00000 | $0.00034 |
Grade A, and why
remember scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
You are helping add important information to the project's long-term memory system.
Context
The user wants to add this information to .claude/flashback/memory/REMEMBER.md: "$ARGUMENTS"
Current REMEMBER.md Content
{{CURRENT_MEMORY}}
Task
Analyze the user's input and add it to the appropriate section in .claude/flashback/memory/REMEMBER.md. The information should be:
-
Categorized correctly - Place it in the most relevant section:
- 📋 Project Overview - For high-level project description
- 🏗️ Architecture & Patterns - For design decisions and architectural info
- 🔧 Development Setup - For setup, dependencies, configuration
- 📝 Conventions & Standards - For code style and project standards
- 🚨 Important Constraints - For limitations, requirements, things to avoid
- 🔗 Key Dependencies - For important libraries, frameworks, services
- 📁 Directory Structure - For file locations and organizational patterns
- 🧠 Lessons Learned - For insights, gotchas, knowledge gained
- 🎯 Current Goals - For high-level objectives and current work
-
Well-formatted - Use consistent formatting with existing content
-
Concise but complete - Capture the essential information clearly
-
Actionable - Make it useful for future sessions
If the input doesn't clearly fit existing sections, add it to "🧠 Lessons Learned" as the default.
Please output the complete updated .claude/flashback/memory/REMEMBER.md file with the new information properly integrated.
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 · 31 lines · 0 tokens per session scan A a204b4211179
remember is a command published in the GitHub repository agentsea/flashbacker (57 stars, last pushed 9mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 337 tokens. 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 2026-08-30.
Other commands, from other repositories
minutes-ideas
Surface recent voice memos and ideas captured from any device. Use when the user asks "what ideas did I have?", "what were my recent memos?", "what did I record while walking?", or wants to recall a captured thought.
learn
Force claude-smart to extract learnings from this session now.
memory-store
Store an insight, decision, or pattern to memory.
analyze-context
USE WHEN you want to analyze project context before starting work on a task. Calls context + recall, then synthesizes goals, decisions, gotchas, and relevant memories into a pre-task brief.
cc-memory
Configure persistent memory that survives across sessions using a layered approach: split rule files for always-loaded context, auto-memory for organic learning, and optional MCP-backed long-term memory for large codebases.
lians-recall
Recall current (non-stale) facts from Lians memory, optionally as-of a past date.