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 skills/naimkatiman/continuous-improvement/handoffnpx skills add naimkatiman/continuous-improvement --skill handoffgit clone --depth 1 https://github.com/naimkatiman/continuous-improvementWrote 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/naimkatiman/continuous-improvement/handoff)<a href="https://agentmods.dev/skills/naimkatiman/continuous-improvement/handoff"><img src="https://agentmods.dev/badge/skills/naimkatiman/continuous-improvement/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 | $0.00052 | $0.00975 |
| Opus 5 | $0.00026 | $0.00487 |
| Sonnet 5 | $0.00010 | $0.00195 |
| Haiku 4.5 | $0.00005 | $0.00097 |
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 5d 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 — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/handoff — Hand the session off to a fresh agent
Ported verbatim in behavior from mattpocock/skills in-progress/handoff (MIT, © 2026 Matt Pocock). Cold-storage snapshot at third-party/mattpocock-skills/skills/in-progress/handoff/SKILL.md; SHA pin in third-party/MANIFEST.md.
What this skill does
Write a handoff document summarising the current conversation so a fresh agent can continue the work. Save it to a path produced by mktemp -t handoff-XXXXXX.md (read the file before you write to it).
Suggest the skills to be used, if any, by the next session.
Do not duplicate content already captured in other artifacts (PRDs, plans, ADRs, issues, commits, diffs). Reference them by path or URL instead.
If the user passed arguments, treat them as a description of what the next session will focus on and tailor the doc accordingly.
When to fire it
- End of a working session that did not finish the task — you want the next agent to pick up cold without re-reading the whole transcript.
- Context budget approaching the ceiling and
/compactwould lose load-bearing state — write a handoff doc first, then compact. - Switching from one repo or branch to another mid-session — capture what was decided in the active context before the swap.
- Before invoking a long-running autonomous loop (
/ralph,/loop) that will run while you are away.
What goes in the doc
The handoff is a brief, not a transcript. A useful one fits on one screen and answers, in order:
- Goal — the one-sentence outcome the user is steering toward.
- Current state — what is actually true on disk / in the system right now (branch, last commit, open files, last verified step).
- Decisions made this session — only what is not already in commits, PRDs, ADRs, or the plan doc.
- Open questions — blocking choices the next agent needs the user to answer before continuing.
- Next concrete step — the single action the next agent should take first.
- Skills to load — names of the skills the next session should activate (e.g.
verification-loop,superpowers:writing-plans,gateguard).
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.
- 5d ago First seen · 59 lines · 52 tokens per session scan A a15a1e07536b
handoff is a skill published in the GitHub repository naimkatiman/continuous-improvement (7 stars, last pushed 10d ago), licensed MIT. It adds 52 tokens to every session and 975 once invoked, about $0.0003 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 2026-08-31.
Other skills, from other repositories
reflect
Per-project self-improvement - reads the .harness ledger and feedback memories, then proposes gated rule/threshold/ADR changes so the project stops repeating mistakes. Run periodically.
remember
Review auto-memory entries and propose promotions to CLAUDE.md, CLAUDE.local.md, or shared memory. Also detects outdated, conflicting, and duplicate entries across memory layers.
ucai-patterns
Use when the user asks about Claude Code best practices, how to write agents, how to use hooks, how to manage context, or how to work effectively with Claude Code's native systems.
dream
Memory consolidation - review, merge, prune, and index memory files. Run periodically to keep memories organized and up-to-date.
meta-synthesis
Reads /context/skill-sessions.md (the session log every execution skill writes to) to detect patterns that repeat across 2+ sessions, proposes new guardrails for /context/meta-patterns.md, and proposes brain updates for confirmed learnings. Run on-demand or roughly weekly — not a scheduled background job. Trigger on…
meta-learn
Deliberate deep-dive capture for a completed skill session that deserves more than the automatic one-line row every T1/T2 skill already logs at its own close — asks three extraction questions (what surprised you, what was wrong, what was missing), turns real answers into specific, falsifiable pattern statements, and…