Borrowing it
Nothing to install: this file belongs to Aptica-Solutions/a-mcp-runmeter. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Aptica-Solutions/a-mcp-runmeter/main/.claude/commands/handoff.mdgit clone --depth 1 https://github.com/Aptica-Solutions/a-mcp-runmeterWrote 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/aptica-solutions/a-mcp-runmeter/handoff)<a href="https://agentmods.dev/commands/aptica-solutions/a-mcp-runmeter/handoff"><img src="https://agentmods.dev/badge/commands/aptica-solutions/a-mcp-runmeter/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/aptica-solutions/a-mcp-runmeter/handoff"><img src="https://agentmods.dev/badge/commands/aptica-solutions/a-mcp-runmeter/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 | $0.00000 | $0.00486 |
| Opus 5.5 | $0.00000 | $0.00194 |
| Sonnet 5.5 | $0.00000 | $0.00097 |
| Haiku 4.5 | $0.00000 | $0.00049 |
Grade A, and why
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
Write a session handoff note and prepare for context reset. Follow these steps in order.
Step 1 — Read Current State
Read these files before writing anything:
AI-TASKS.md— note which tasks changed status this session (look for [~] and recent [x])CONTEXT.md— acknowledge any prior handoff that was in effect
Step 2 — Draft Handoff Note
Compose a structured handoff using this exact format:
# Session Handoff — [YYYY-MM-DD]
## Accomplished This Session
- [bullet per completed or meaningfully advanced item]
## In Progress — Pick Up Here
[~] [task name or description]
State: [describe exactly where this is — e.g., "file X is done, file Y still needs the Y section"]
Next action: [single sentence — the first thing to do to resume this task]
## Decisions Made
- [decision]: [reason — one line each, only decisions that would surprise a fresh session]
## Open Blockers
- [anything unresolved, waiting on user input, or deferred]
(write "None" if clear)
## Next Step
> [One sentence. The exact first action for the next session.]
## Files Touched (non-obvious only)
- [path] — [why it matters]
Keep it compact — the goal is a cold-start brief, not a full log. Omit sections that are empty except Blockers (write "None" there explicitly).
Step 3 — Write to CONTEXT.md
Write the completed handoff note to CONTEXT.md, replacing any prior content.
Step 4 — Confirm and Hand Off
Show the written handoff to the user. Then output exactly:
Handoff written to CONTEXT.md.
Run /clear to reset the session. The next session will read this note automatically.
If the user asks to revise the handoff, update CONTEXT.md and confirm again.
Notes
- Do not commit
CONTEXT.md— it is session state, not source - If AI-TASKS.md has changed tasks, ensure it is saved before writing the handoff
- The handoff replaces the session checkpoint signal — use /handoff instead of printing the checkpoint block when resetting mid-PBI
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 · 70 lines · 0 tokens per session scan A d7f3b396f52f
handoff is a command published in the GitHub repository Aptica-Solutions/a-mcp-runmeter (0 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 486 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 2026-09-01.
Other commands, from other repositories
remember
Write-side memory: stores decisions, patterns, and outcomes in the MCP memory knowledge graph as entities with typed observations and relations. Use when something worth persisting across sessions was just learned or decided. To search or read existing memory, invoke memory; to debug retrieval internals…
memory
Read-side memory operations on the knowledge graph: search past decisions and patterns, load session context, view decision timelines, render Mermaid graph visualizations. Subcommands: search, load, history, viz, status. Use when finding or reviewing what memory already holds. For storing new knowledge instead, invoke…
dream
Nightly memory consolidation: prunes stale entries, merges duplicates, resolves contradictions, rebuilds the MEMORY.md index. Use when memory files accumulated over many sessions need cleanup. New decisions get stored by remember; searches run through memory; internals live in memory-fabric.
compact-prep
Ask the agent to prepare for conversation compaction by updating any relevant state and providing guidance for the compaction agent and to kick off the session there after.
save-to-md
Save session documentation with Neo4j memory integration.
revise-claude-md
Update CLAUDE.md with learnings from this session.