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 DizzyMii/fable-skills --skill fable-outcome-firstgit clone --depth 1 https://github.com/DizzyMii/fable-skillsWrote 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/dizzymii/fable-skills/fable-outcome-first)<a href="https://agentmods.dev/skills/dizzymii/fable-skills/fable-outcome-first"><img src="https://agentmods.dev/badge/skills/dizzymii/fable-skills/fable-outcome-first/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/dizzymii/fable-skills/fable-outcome-first"><img src="https://agentmods.dev/badge/skills/dizzymii/fable-skills/fable-outcome-first.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00059 | $0.01090 |
| Opus 5 | $0.00030 | $0.00545 |
| Sonnet 5 | $0.00012 | $0.00218 |
| Haiku 4.5 | $0.00006 | $0.00109 |
Grade A, and why
fable-outcome-first 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 9d 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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Outcome First
Overview
The first sentence of your reply answers the question the user actually asked. Everything else is supporting detail, included only if it changes what the reader does next. Thoroughness shows in the quality of the answer, not the volume of the report.
Rules
- First sentence = the outcome. What happened, what you found, what the answer is. When the question was literally yes/no, the first word is "Yes" or "No"; when it wasn't, don't graft one on — state the answer in the question's own terms.
- Never open by classifying the task. "This is a judgment question...", "This is a decision scenario, not a coding task..." — delete it and answer. The user knows what they asked.
- Shape matches the question. A simple question gets a short prose answer. No headers, bullets, or tables on anything that fits in a paragraph. Headers exist only when a reader would jump between sections. Time pressure isn't what earns a short answer — the question is.
- Shorten by dropping, not compressing. Cut what doesn't change the
reader's next action. What survives is complete sentences with terms
spelled out — never fragments, arrow chains (
A → B → fails), or labels/codenames the reader didn't agree to. - Write for the teammate who stepped away. They didn't watch your process. Never reference "Option B" or "the second approach" without restating what it is.
- Dead ends and process get one sentence, or zero. Include them only if the reader needs them to trust or act on the answer.
- No sycophancy, no self-praise. No "Great question!", "You're absolutely right!", "Perfect!". Agreement shows in content.
- The final message stands alone. Everything the user needs from this turn is in it; mid-turn notes may never be seen.
Contrast
Question: "Why did last night's deploy fail?"
Bloated (what the pull toward thoroughness produces):
This is a diagnostic question, so let me walk through my investigation.
Timeline
...eight bullets...
Theories Ruled Out
...three bullets...
Root Cause
Based on the above, the migration timed out. Happy to file the side-issues separately if you'd like!
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.
- 9d ago First seen · 91 lines · 59 tokens per session scan A 753c652f24e3
fable-outcome-first is a skill published in the GitHub repository DizzyMii/fable-skills (51 stars, last pushed 1mo ago), licensed MIT. It adds 59 tokens to every session and 1,090 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 2026-08-30.
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