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/attack-conclusion/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/attack-conclusion)<a href="https://agentmods.dev/skills/happier-dev/happier/attack-conclusion"><img src="https://agentmods.dev/badge/skills/happier-dev/happier/attack-conclusion/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/attack-conclusion"><img src="https://agentmods.dev/badge/skills/happier-dev/happier/attack-conclusion.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 | $0.00089 | $0.01622 |
| Opus 5.5 | $0.00036 | $0.00649 |
| Sonnet 5.5 | $0.00018 | $0.00324 |
| Haiku 4.5 | $0.00009 | $0.00162 |
Grade A, and why
attack-conclusion 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Attack Your Conclusion
Before handing over a conclusion, switch roles completely: you are no longer the author defending it, you are the reviewer paid to break it, with the same energy spent building it. Full doctrine: docs/agent-craft.md §6 and §8.
The test of whether you actually switched roles: did you go looking for evidence that would change your mind, or only re-inspect the evidence that formed the conclusion?
The standard attacks — in order of cheapness, each as a runnable check
- Alternative cause or falsifier. Ask what else could explain the same evidence. When the evidence supports a materially different candidate, name it and run the cheapest discriminating observation; when the mechanism is directly established, do not manufacture a second hypothesis—identify and run the cheapest observation that could falsify the conclusion instead.
- Neighboring cases. The fix works for the reproduced case. Run the case next door: the empty list, the second invocation, the other platform, the resumed session, the concurrent caller.
- Blast radius. What consumes what you changed? Search callers, readers, subscribers, tests, serialized forms. "Nothing else uses this" is a claim — re-derive it, don't assert it.
- Environment gap. Does the conclusion survive where the code actually runs, or only in the harness? Host tests encode the same assumptions the author had. For user-visible behavior, use the risk-appropriate browser/device gate in
.agents/skills/happier-testing. - Hypothesis lock. Are you explaining the evidence, or explaining your first hypothesis? Re-read the raw evidence pretending you just arrived and have no favorite.
Run the cheap attacks; an attack that is just worry is not an attack. If you cannot state what would falsify the conclusion, it is not a conclusion yet — it is a preference.
Architecture-impact attack
Apply root Scope-preserving solution economy during this attack: preserve the complete feature outcome, challenge unsupported implementation machinery rather than the feature itself, and try folding behavior into the canonical owner before accepting a split-brain or parallel path.
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 Changed c238c236286a
- 1mo ago Changed f5c547050810
- 1mo ago First seen · 67 lines · 89 tokens per session scan A d18e24e86c9d
attack-conclusion is a skill published in the GitHub repository happier-dev/happier (2,083 stars, last pushed today), licensed MIT. It adds 89 tokens to every session and 1,622 once invoked, about $0.0004 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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