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 jellydn/my-ai-tools --skill handoffsgit clone --depth 1 https://github.com/jellydn/my-ai-toolsWrote 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/jellydn/my-ai-tools/handoffs)<a href="https://agentmods.dev/skills/jellydn/my-ai-tools/handoffs"><img src="https://agentmods.dev/badge/skills/jellydn/my-ai-tools/handoffs/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/skills/jellydn/my-ai-tools/handoffs"><img src="https://agentmods.dev/badge/skills/jellydn/my-ai-tools/handoffs.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00012 | $0.01170 |
| Opus 5.5 | $0.00005 | $0.00468 |
| Sonnet 5.5 | $0.00002 | $0.00234 |
| Haiku 4.5 | $0.00001 | $0.00117 |
Grade A, and why
handoffs 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 21d 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.
How it starts
The opening of the file, as written. The whole thing — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Session Handoff Plan
Creates a detailed handoff plan of the conversation for continuing the work in a new session.
The user specified purpose:
$ARGUMENTS
You are creating a summary specifically so that it can be continued by another agent. For this to work you MUST have a purpose. If no specified purpose was provided in the <purpose>...</purpose> tag you must STOP IMMEDIATELY and ask the user what the purpose is.
Do not continue before asking for the purpose as you will otherwise not understand the instructions and do not assume a purpose!
Goal
Create a detailed summary of the conversation so far, paying close attention to the user's explicit purpose for the next steps. This handoff plan should be thorough in capturing technical details, code patterns, and architectural decisions that will be essential for continuing development work without losing context.
Process
Before providing the final handoff, produce a concise evidence-based summary for the user. Do not expose private chain-of-thought or <analysis> tags. Include decisions, current state, blockers, and the exact next action instead of a chronological transcript or full code dumps.
- Identify the user's explicit purpose and the current work state.
- Verify important paths, branch/status, recent command results, and unresolved blockers.
- Capture only decision-relevant file names, symbols, short snippets, and links.
- Mark uncertain or stale information explicitly.
Your plan should include the following sections:
- Primary Request and Intent: Capture all of the user's explicit requests and intents in detail
- Key Technical Concepts: List all important technical concepts, technologies, and frameworks discussed.
- Files and Code Sections: Enumerate specific files and code sections examined, modified, or created. Pay special attention to the most recent messages and include full code snippets where applicable and include a summary of why this file read or edit is important.
- Problem Solving: Document problems solved and any ongoing troubleshooting efforts.
- Pending Tasks: Outline any pending tasks that you have explicitly been asked to work on.
- Current Work: Describe in detail precisely what was being worked on immediately before this handoff request, paying special attention to the most recent messages from both user and assistant. Include file names and code snippets where applicable.
- Next Step: List the next step that you will take that is related to the most recent work you were doing. IMPORTANT: ensure that this step is DIRECTLY in line with the user's explicit requests, and the task you were working on immediately before this handoff request. If your last task was concluded, then only list next steps if they are explicitly in line with the users request. Do not start on tangential requests without confirming with the user first. Include this section only if there is an actionable next step.
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.
- 21d ago Changed · -2 lines 581a687b6cb9
- 1mo ago First seen · 130 lines · 12 tokens per session scan A 8becc6a93fac
handoffs is a skill published in the GitHub repository jellydn/my-ai-tools (124 stars, last pushed today), licensed MIT. It adds 12 tokens to every session and 1,170 once invoked, about $0.0000 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 2026-08-30.
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