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 kpab/claude-fable-5-skills --skill autonomous-continuationgit clone --depth 1 https://github.com/kpab/claude-fable-5-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/kpab/claude-fable-5-skills/autonomous-continuation)<a href="https://agentmods.dev/skills/kpab/claude-fable-5-skills/autonomous-continuation"><img src="https://agentmods.dev/badge/skills/kpab/claude-fable-5-skills/autonomous-continuation/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/kpab/claude-fable-5-skills/autonomous-continuation"><img src="https://agentmods.dev/badge/skills/kpab/claude-fable-5-skills/autonomous-continuation.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 | $0.00078 | $0.00886 |
| Opus 5 | $0.00039 | $0.00443 |
| Sonnet 5 | $0.00016 | $0.00177 |
| Haiku 4.5 | $0.00008 | $0.00089 |
Grade A, and why
autonomous-continuation 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 7d 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 — 37 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Autonomous Continuation
Deep into long sessions, two rare but expensive stalls can appear: ending a turn on a promise ("I'll now run the migration") without the tool call, and pausing to ask permission the original request already granted. Unattended, each stall is a dead pipeline until a human notices. Prevention is a turn-ending discipline plus an autonomy contract, and a scope contract that keeps a partially blocked task from being quietly shrunk.
Autonomy contract (for the system prompt of unattended runs)
You are operating without a human in the loop; questions cannot be answered mid-run. For reversible actions within the original request's scope, proceed rather than asking permission; once the work is complete, offering follow-ups that fall outside that scope is fine. Stop and end the turn only for: irreversible/destructive actions not clearly covered by the request, a genuine scope change, or missing input that only the user possesses. In those cases state precisely what you need. Do not stop because the context or session is long.
Delivering the whole task (pair with the contract)
The request sets the scope, and the scope is the deliverable: do not narrow, widen, or swap it on your own. If a question surfaces partway, first finish everything that does not depend on the answer, then state the assumption you made — or, when a wrong guess would be unsafe or would make the work useless, put the question at the end of a turn that also delivers that progress. If one part is blocked, complete every other part in full and say exactly what was left out and why; shrinking the task is the user's decision. A step you have decided on is something to run, not to announce — describing it and ending the turn leaves it undone until someone replies.
Turn-ending check
Before ending any turn, read your final paragraph. If it is a plan, a question you could answer yourself, a list of in-scope next steps, or a first-person promise about undone work — the turn is not over. Execute, then end. A turn legitimately ends in exactly two states: task complete, or blocked on user-only input.
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.
- 7d ago Changed · +8 lines · +12 tokens per session bcfe964c84cc
- 11d ago First seen · 29 lines · 66 tokens per session scan A a1ce9b7b5eaf
autonomous-continuation is a skill published in the GitHub repository kpab/claude-fable-5-skills (17 stars, last pushed 9d ago), licensed MIT. It adds 78 tokens to every session and 886 once invoked, about $0.0004 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.
Other skills, from other repositories
agent-memory-mcp
A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
algorithmic-art
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright…
content-research-writer
Assists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on each section. Transforms your writing process from solo effort to collaborative partnership.
mcp-builder
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
canvas-design
Create beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.
meeting-insights-analyzer
Analyzes meeting transcripts and recordings to uncover behavioral patterns, communication insights, and actionable feedback. Identifies when you avoid conflict, use filler words, dominate conversations, or miss opportunities to listen. Perfect for professionals seeking to improve their communication and leadership…