Happier is an open-source, end-to-end encrypted client that lets people run AI coding-agent sessions on a computer and continue controlling them from a phone, browser, or desktop app. It is for developers who use agents such as Claude Code, Codex, Gemini, or OpenCode across multiple devices, with self-hosting available. The catalogue entries are add-ons for configuring or extending this client and its supported coding-agent workflows.
Borrowing it
Nothing to install: this file belongs to happier-dev/happier. 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/happier-dev/happier/dev/.agents/skills/handoff-report/SKILL.mdgit clone --depth 1 https://github.com/happier-dev/happierWrote 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/happier-dev/happier/handoff-report)<a href="https://agentmods.dev/skills/happier-dev/happier/handoff-report"><img src="https://agentmods.dev/badge/skills/happier-dev/happier/handoff-report/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/happier-dev/happier/handoff-report"><img src="https://agentmods.dev/badge/skills/happier-dev/happier/handoff-report.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 19 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00070 | $0.00793 |
| Opus 5.5 | $0.00028 | $0.00317 |
| Sonnet 5.5 | $0.00014 | $0.00159 |
| Haiku 4.5 | $0.00007 | $0.00079 |
Grade A, and why
handoff-report 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.
How it starts
The opening of the file, as written. The whole thing — 49 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Handoff Report
Structure any substantive report so the reader can act on the first paragraph and audit the rest. Full doctrine: docs/agent-craft.md §5 and §7.
Order
- Outcome first. The first sentence answers what the reader would ask for if they said "just the TLDR": what happened, what was found, or what is blocked. Not the journey, not the setup.
- Failures and scope changes in the first block. A failed check, a skipped step, a scope change, an error worked around — these go up front even when embarrassing, never mid-report. The most informative event is the one you are tempted to smooth over.
- Reasoning, auditable. Evidence pointers with every load-bearing statement:
file.ts:line, the log excerpt, the measurement, the command that produced the number. Trust should rest on checkable references, not on tone. - Residual risk last, explicitly. What remains unverified, what to check next, what would invalidate the conclusion. If there is genuinely no residual risk, say that — the reader cannot distinguish "no risk" from "risk section omitted".
Labeling
- Every load-bearing statement is sortable by the reader into observed (ran it, read it, saw it) / derived (follows from observations by stated reasoning) / assumed (plausible, unverified) — without asking you.
- Use cheap explicit markers: "verified:", "inferred from X:", "assumption:". Never let sentence confidence do the labeling; fluent prose reads as fact regardless of bin.
- For derived claims, state the derivation ("X because A + B") so the reader can audit the step and see which assumptions it inherits.
- Hedging is not labeling. "Probably" makes every sentence equally gray; a label says exactly what is known and what is guessed.
- Distinguish "I didn't find X" (an observation about your search — say which search) from "X doesn't exist".
Style
- Brevity comes from selecting what matters, not compressing the writing. Complete sentences, terms spelled out, no codenames or shorthand invented mid-task.
- Write for the teammate who stepped away and is catching up — they did not watch the process unfold.
- Report faithfully: if tests failed, say so with the output; if a step was skipped, say that; if something is done and verified, state it plainly without hedging.
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 · 49 lines · 70 tokens per session scan A 1be1026361a9
handoff-report is a skill published in the GitHub repository happier-dev/happier (2,072 stars, last pushed yesterday), licensed MIT. It adds 70 tokens to every session and 793 once invoked, about $0.0003 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.
Other skills, from other repositories
agtx-oneshot
One-shot a whole project on an agtx board: decompose the goal, run every task unattended, unblock the workers, and merge each one. Use when the user wants a long autonomous run rather than a single session.
agtx-sweep
Sweep this conversation into agtx tasks and push them to the kanban board. Use when the user wants to capture, decompose, or hand off conversation results to the agtx board.
agtx-execute
Execute an approved implementation plan. Implement the changes, then write a summary to .agtx/execute.md and stop.
agtx-plan
Plan a task implementation. Analyze the codebase, create a detailed plan, write it to .agtx/plan.md, then stop and wait for user approval before making any changes.
agtx-research
Explore the codebase to understand a task before planning. Write findings to .agtx/research.md and stop. This is a read-only exploration — do not modify any files.
agtx-review
Self-review completed work. Check for correctness, edge cases, and code quality. Write review to .agtx/review.md and stop.