Fable 5 Prompt Patterns

A prompt-engineering playbook for Claude Fable 5 (claude-fable-5) — Anthropic's most capable widely released model. Fable 5 follows instructions, paces long agentic loops, and handles thinking differently enough from Opus 4.8 and Sonnet 4.6 that prompts tuned for the 4.x family often regress on it. This skill is for engineers porting production prompts, harnesses, and agent loops to Fable 5 (or claude-mythos-5 under Project Glasswing).

When to use it

• You moved a working Opus 4.7/4.8 prompt to Fable 5 and output quality dropped or turns ballooned.
• You're building long-horizon agents (overnight refactors, multi-hour research) and need timeout/streaming/progress patterns.
• You're deciding between effort levels, or whether to reach for Task Budgets vs max_tokens.
• You're wiring tool-use orchestration (sub-agents, memory, custom send_to_user tools) and want the patterns that actually hold on Fable 5.
• You hit a stop_reason: "refusal" and need a fallback strategy.

What it does

It encodes the Fable-5-specific deltas as ready-to-paste prompt snippets and config rules:

• Thinking is always on. Omit the thinking parameter entirely — {type: "disabled"} and {type: "enabled", budget_tokens: N} both return 400. Depth is controlled by output_config: {effort: ...} (low→xhigh/max), not a token budget. The raw chain of thought is never returned; use display: "summarized" for a readable summary.
• Effort sweeps including low/medium. Fable 5 at low often beats prior models at max. Default high; reserve xhigh/max for the hardest work.
• Anti-overplanning and no-tidying snippets to counter Fable 5's tendency to deliberate or refactor beyond the ask at higher effort.
• Grounded-progress and boundary instructions that nearly eliminate fabricated status reports and unrequested side-actions on long runs.
• Async sub-agent delegation patterns (long-lived peers beat spawn-and-block) and file-based memory prompts.
• Refusal handling: branch on stop_reason before reading content; opt into the server-side fallbacks parameter by default.

Usage example

curl -fsSL --create-dirs -o ~/.claude/skills/fable-5-prompt-patterns/SKILL.md https://claudeskil.com/skills/fable-5-prompt-patterns/SKILL.md

client.beta.messages.create(
    model="claude-fable-5",
    max_tokens=64000,
    output_config={"effort": "high"},        # no `thinking` param — always on
    betas=["server-side-fallback-2026-06-01"],
    fallbacks=[{"model": "claude-opus-4-8"}], # opt-in refusal recovery
    messages=[...],
)
# Stream long turns so a 128K max_tokens doesn't hit HTTP timeouts.

Tips & gotchas

• Same tokenizer as Opus 4.8 — counts barely move from 4.7/4.8, but re-baseline cost (Fable 5 is priced above Opus tier). Coming from 4.6 or older, re-run count_tokens.
• Requires 30-day data retention. A ZDR org gets 400 invalid_request_error on every request — check retention config before debugging the payload.
• Plan for minutes-long turns. A 15-minute single request at high effort on a hard task is normal; build async check-ins and progress UX, not blocking calls.
• De-prescribe migrated prompts. Step-by-step scaffolding from older models reduces Fable 5 quality — state the goal and constraints, A/B with the scaffolding removed.

FAQ

Is this the default Opus upgrade? No. For "upgrade to the latest model," target claude-opus-4-8. Use Fable 5 only when explicitly chosen — pricing exceeds Opus tier.

How do I set a thinking budget? You don't. budget_tokens is removed (400). Use output_config.effort for depth and the beta task_budget (task-budgets-2026-03-13, min 20K) when you want the model to self-pace an agentic loop.

Can I prefill the assistant turn? No — last-assistant-turn prefills 400. Use output_config.format (structured outputs) or a system-prompt instruction instead.