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 softspark/ai-toolkit --skill output-modegit clone --depth 1 https://github.com/softspark/ai-toolkitWrote 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/softspark/ai-toolkit/output-mode)<a href="https://agentmods.dev/skills/softspark/ai-toolkit/output-mode"><img src="https://agentmods.dev/badge/skills/softspark/ai-toolkit/output-mode/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/softspark/ai-toolkit/output-mode"><img src="https://agentmods.dev/badge/skills/softspark/ai-toolkit/output-mode.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 | $0.00048 | $0.00516 |
| Opus 5.5 | $0.00019 | $0.00206 |
| Sonnet 5.5 | $0.00010 | $0.00103 |
| Haiku 4.5 | $0.00005 | $0.00052 |
Grade A, and why
output-mode 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.
What it actually says
Output Mode
This rule comes from app/rules/output-mode.md in ai-toolkit. It applies to
every task in this workspace, not only when it is loaded.
Output Mode
output-mode: concise
Default response mode for this project is concise. The brand-voice skill (when present in ai-toolkit) auto-loads its concise rules; assistants without that skill should still apply the directives below.
Concise Mode Directives
- No preamble. Skip "I'll now...", "Sure, let me...", "Great question!" and similar warm-ups. Start with the answer.
- Lead with the result. Conclusion or output first; explanation only if asked or non-obvious.
- Max 3 sentences per closed question. Yes/no, single-fact, or "where is X" answers stay under three sentences.
- Tables and lists over prose when comparing options, listing steps, or showing values.
- No trailing summaries. If the diff or output already shows what changed, do not restate it.
- Drop filler adjectives. No "nice", "great", "powerful", "robust" unless the user asked for evaluation.
- Cite file paths as
path:lineinstead of paragraphs describing where things live. - Reserve longer prose for: architecture proposals, trade-off analyses, plans with risks. Everything else: terse.
When to escalate to verbose
- User explicitly asks: "explain in detail", "walk me through", "give me the full picture".
- Reporting a non-obvious failure mode where missing context would mislead.
- Architecture / RFC / ADR / trade-off documents — those have their own structure.
How to override
- Per-session:
/brand-voice default(or/brand-voice strictfor even tighter) - Per-project: change this rule's
output-mode:value in the project'sCLAUDE.md - Permanent removal: re-run
ai-toolkit install --skip rulesor strip the<!-- TOOLKIT:output-mode -->block manually
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 · 42 lines · 48 tokens per session scan A 4a36d62b0abf
output-mode is a skill published in the GitHub repository softspark/ai-toolkit (180 stars, last pushed yesterday), licensed Apache-2.0. It adds 48 tokens to every session and 516 once invoked, about $0.0002 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 2026-09-03.
Other skills, from other repositories
cline-fix-volatile-msg
Ladder-aware Cline Anthropic caching — verify the rolling read/write ladder on the wire, then add the tools breakpoint and tune TTL. Updated for the 2026-08 AI-SDK monorepo.
continue-gemini-explicit
Continue's Gemini provider doesn't use the cachedContents API at all. Add explicit caching for sessions over the minimum token threshold.
roo-fix-volatile-msg
Ladder-aware Roo Code Anthropic caching — verify the rolling read/write ladder on the wire, then close the real gaps (Vertex 4-block budget, MiniMax path).
aider-1h-ttl
Aider uses 5min TTL by default and works around long pauses with keepalive pings. Wire up the 1h TTL beta instead.
cline-openai-cache-key
Cline OpenAI native provider sends no promptcachekey. Add a stable per-task key so cachedtokens stops being zero.
continue-enable-defaults
Continue's prompt caching is opt-in via config and off by default. Flip the default to systemAndTools.