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 agentmods add commands/dosatos/minimise/handoffgit clone --depth 1 https://github.com/dosatos/minimiseWrote 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/dosatos/minimise/handoff)<a href="https://agentmods.dev/commands/dosatos/minimise/handoff"><img src="https://agentmods.dev/badge/commands/dosatos/minimise/handoff.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 | $0.00010 | $0.00358 |
| Opus 5 | $0.00005 | $0.00179 |
| Sonnet 5 | $0.00002 | $0.00072 |
| Haiku 4.5 | $0.00001 | $0.00036 |
Grade A, and why
handoff scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Create a handoff to summarize this session's work for next time:
-
Copy template:
TIMESTAMP=$(date +%Y-%m-%d-%H%M) cp worklogs/handoffs/HANDOFF_TEMPLATE.md "worklogs/handoffs/session-$TIMESTAMP.md" -
Edit the file and fill in:
- ✅ What was accomplished (1-3 bullets)
- 🚀 What's next (immediate, blockers, phase)
- 🔧 How to run (test/use commands)
- ⚠️ Gotchas (critical things to remember)
- 📍 Current state (branch, tests passing, status)
-
Update symlink:
ln -sf "session-$TIMESTAMP.md" worklogs/handoffs/session-latest.md
Pro tip: Use your notes above to fill in the template quickly.
Carry forward the execution rule
In the handoff's How to run / Gotchas, remind the next session:
Delegate implementation to
mini job, don't edit inline. It keeps the orchestrating context clean (execution churn stays in the job) and, run via the/minimise:review-planskill, adds the plan-quality gate for free. Direct edits only for trivial one-liners ormini-blocked changes (migrations, internal refactors).
If this session did any implementation directly instead of via mini job, note
that as debt so next session can course-correct.
$ARGUMENTS
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.
- 4d ago First seen · 42 lines · 10 tokens per session scan A 7d650c31f7c1
handoff is a command published in the GitHub repository dosatos/minimise (11 stars, last pushed 14d ago), licensed MIT. It adds 10 tokens to every session and 358 once invoked, about $0.0001 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 2026-08-30.
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.
session-end
I'll summarize this coding session and update the memory system with our accomplishments.
memory-store
Store an insight, decision, or pattern to memory.
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.
neo-review
Get Neo's code review with semantic matching against past findings in memory. Use on a diff or module before merge, especially where earlier mistakes in this codebase are likely to recur. Skip for formatting, lint-catchable issues, and single-line changes.