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/pedrol-cmd/brain-drinWrote 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/pedrol-cmd/brain-drin/session-handoff)<a href="https://agentmods.dev/commands/pedrol-cmd/brain-drin/session-handoff"><img src="https://agentmods.dev/badge/commands/pedrol-cmd/brain-drin/session-handoff/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/pedrol-cmd/brain-drin/session-handoff"><img src="https://agentmods.dev/badge/commands/pedrol-cmd/brain-drin/session-handoff.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 | $0.00016 | $0.00241 |
| Opus 5.5 | $0.00006 | $0.00096 |
| Sonnet 5.5 | $0.00003 | $0.00048 |
| Haiku 4.5 | $0.00002 | $0.00024 |
Grade A, and why
session-handoff 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
Session Handoff
Your Task
Create a handoff document that lets a new Claude session continue exactly where this one left off.
- Read the full conversation context
- Generate a handoff document:
# Session Handoff — [date]
## What We Were Doing
[1-2 sentences: the task and current state]
## Decisions Made
[Bullet list of decisions and their rationale]
## Changes Made
[Files modified/created, with one-line description each]
## Current State
[What's working, what's broken, what's in progress]
## Next Steps
[Ordered list of what to do next, with enough context to act]
## Key Context
[Anything a new session needs to know that isn't obvious from the code]
- Save to
.drin/memory-compiler/handoffs/[date]-[topic].md
Rules
- Include enough context to resume without reading the entire conversation
- Reference specific files and line numbers
- Don't include conversation noise — only decisions and state
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 · 43 lines · 16 tokens per session scan A 724ab2802931
session-handoff is a command published in the GitHub repository pedrol-cmd/brain-drin (12 stars, last pushed 6mo ago), licensed MIT. It adds 16 tokens to every session and 241 once invoked, about $0.0001 per session on Opus 5.5. 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 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.