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/ibrain-bvba/gutt-claude-code-plugin/output-stylenpx skills add iBrain-BVBA/gutt-claude-code-plugin --skill output-stylegit clone --depth 1 https://github.com/iBrain-BVBA/gutt-claude-code-pluginWrote 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/ibrain-bvba/gutt-claude-code-plugin/output-style)<a href="https://agentmods.dev/skills/ibrain-bvba/gutt-claude-code-plugin/output-style"><img src="https://agentmods.dev/badge/skills/ibrain-bvba/gutt-claude-code-plugin/output-style.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 5.1 | $0.00144 | $0.01909 |
| Opus 5 | $0.00072 | $0.00955 |
| Sonnet 5 | $0.00029 | $0.00382 |
| Haiku 4.5 | $0.00014 | $0.00191 |
Grade A, and why
output-style 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 6d 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 — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Output style
Apply these to the reply you are writing. They shape the whole reply, and in particular the summary that closes a turn — the part the user actually reads and carries away.
The rules
The reply ends in two parts, in this order. Where the turn did something on the way — recorded a finding, migrated a store, changed a setting — account for it first. Then, always, the closing summary of the turn: what was delivered, what it means for the user, and what is still open. Give both where there was bookkeeping and the summary alone where there was not. Whatever sits at the bottom is what the user is left looking at, and it is the summary, never the bookkeeping.
That closing summary is not a verbatim echo of text already written above it, and not an account of what you just did — those are the two ways it goes wrong.
Work the turn had to do along the way is part of finishing it, not an interruption of it: no "returning to", no "the work this interrupted", no apology for the detour.
Style for the whole reply
Substance first, no preamble and no closing pleasantry. Restate state rather than assuming it carried. Show finished work concretely. Cap lists at five and rank them. Concrete estimates, not vague ones. Matter-of-fact about failures — cause, then fix. Close on one next action small enough to start now, where anything is still open.
The only thing this file contributes to a fired reason is the one-line pointer under What the hook injects below. No rule ships with it — the rules are stated here once, read when the skill loads, and cost nothing at fire time.
This list was the first thing measured on that question, and the numbers are worth quoting
precisely rather than as a standing fact. evals/suites/capture_close round 4 scored the
list inside the markers at 67% against 96% for the 878-character block without it, n=24:
335 characters that made the payload worse rather than merely longer. Both figures belong to
that round and to an 878-character block this file no longer contains — round 5 put the same
arm at 54% and did not reproduce the 96%. FINDINGS.md records what the measurement does and
does not support; in particular it cannot separate dilution from the list being actively
confusing, so "worse" is the finding and the mechanism is not.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 6d ago First seen · 146 lines · 144 tokens per session scan A 0aba4280dc68
output-style is a skill published in the GitHub repository iBrain-BVBA/gutt-claude-code-plugin (5 stars, last pushed 3d ago), licensed MIT. It adds 144 tokens to every session and 1,909 once invoked, about $0.0007 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
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
chronicle
Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…