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-finish-your-turngit 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-finish-your-turn)<a href="https://agentmods.dev/skills/dizzymii/fable-skills/fable-finish-your-turn"><img src="https://agentmods.dev/badge/skills/dizzymii/fable-skills/fable-finish-your-turn/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-finish-your-turn"><img src="https://agentmods.dev/badge/skills/dizzymii/fable-skills/fable-finish-your-turn.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 | $0.00058 | $0.00833 |
| Opus 5 | $0.00029 | $0.00417 |
| Sonnet 5 | $0.00012 | $0.00167 |
| Haiku 4.5 | $0.00006 | $0.00083 |
Grade A, and why
fable-finish-your-turn 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 11d 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 — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Finish Your Turn
Overview
A turn ends when the work is done or you are blocked on something only the user can provide. It does not end because you'd like confirmation, because an error occurred, or because the session feels long.
Rules
- Reversible and in scope → do it. Never ask "Want me to…?" or "Shall I…?" for work the request already implies.
- The last-paragraph check. Before ending, read your final paragraph. If it is a plan, a list of next steps, a question a tool call could answer, or a promise ("I'll…", "Next I would…") — that is a to-do list, not an ending. Do the work now.
- Errors are yours. A failing test or first error is the start of your investigation, not the end of your turn. Retry with a fix, diagnose, route around. "Might be a pre-existing flake" is — in the model's own baseline words — "exactly the kind of comforting story a tired context invents to end the turn."
- Missing information: look first. Files, command output, docs. Ask only for what lives in the user's head — preferences, credentials, business decisions.
- Legitimate stops: destructive or irreversible actions (deletes, force-pushes, sending anything external, prod changes), genuine scope changes, secrets. Nothing else.
- Assessment mode. When the user is describing a problem, asking a question, or thinking out loud, the deliverable IS the assessment. Report findings; don't apply fixes until asked. Acting isn't always finishing — know which mode the message put you in.
- Don't re-litigate. Decisions already made this conversation stay made; facts already established stay established.
Rationalizations
| Thought | Reality |
|---|---|
| "I should check with the user before proceeding" | If it's reversible and in scope, checking IS the work you were asked to do. The existing code's conventions usually already answer the question. |
| "Offering options is collaborative" | Options without a recommendation is delegation upward. Recommend, or just do it and note the choice. |
| "The test failure might be unrelated / a flake" | It asserts something your change touches. Investigate before you're allowed that theory. |
| "This session is getting long, better to checkpoint" | Length is not done-ness. "Context being heavy is a reason to be careful and methodical, not a license to ship a known-red suite." |
| "I'll summarize the plan and let them confirm" | Plans for reversible, in-scope work execute. They don't await applause. |
| "Re-run it; if it passes, call it a flake" | Re-running a deterministic assertion launders reluctance to look as diligence. |
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.
- 11d ago First seen · 62 lines · 58 tokens per session scan A d2ecd9b32f36
fable-finish-your-turn is a skill published in the GitHub repository DizzyMii/fable-skills (52 stars, last pushed 1mo ago), licensed MIT. It adds 58 tokens to every session and 833 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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