# yaml-language-server: $schema=https://promptfoo.dev/config-schema.json description: Claude Fable 5 advanced coding with xhigh effort and always-on adaptive thinking prompts: - | {{task}} providers: - id: anthropic:messages:claude-fable-5 config: # Fable 5 always uses adaptive thinking — there is no `thinking` block to # set. Manual budgets (`type: enabled`) are converted to adaptive and # `type: disabled` is omitted because thinking cannot be turned off. # # Fable 5 also rejects manual sampling controls (temperature/top_p/top_k) # at the model level — promptfoo omits them automatically, so don't set # them here. effort: xhigh # Recommended starting point for coding/agentic work (between high and max) # Always-on adaptive thinking consumes output tokens before any visible # text. Budget max_tokens generously — at xhigh effort a tight budget can # be spent entirely on thinking, yielding an empty response. max_tokens: 16000 tests: # Distributed-systems debugging with incomplete information - vars: task: | A payment service intermittently double-charges customers. Here's what you know: 1. The charge endpoint is idempotent — it checks for an existing charge by idempotency key before creating one 2. The idempotency check reads from a Postgres replica; writes go to the primary 3. Replication lag spikes to 2-3 seconds during peak traffic 4. Clients retry on timeout with the same idempotency key 5. Double charges only happen during peak hours 6. Each double charge shows two rows with the same idempotency key but different charge IDs Diagnose the root cause and propose a fix. Explain why the idempotency check fails despite using the same key. assert: - type: contains-any value: ['replica', 'replication lag', 'read-after-write', 'primary', 'race'] reason: Should identify the stale-replica read as the root cause - type: llm-rubric value: | The response should: 1. Identify the root cause (idempotency check reads a lagging replica, so a retry during the lag window misses the in-flight charge) 2. Explain why it only happens at peak (replication lag exceeds the client retry interval) 3. Propose concrete fixes (read idempotency checks from the primary, unique constraint on idempotency key, or insert-first/conflict-based idempotency) 4. Note that a unique constraint is the only fix that closes the race completely # Production-quality code generation with concurrency concerns - vars: task: | Write a TypeScript class implementing a token-bucket rate limiter that: 1. Supports a configurable capacity and refill rate 2. Is safe to call concurrently from async code 3. Exposes acquire() that resolves when a token is available (with optional timeout) 4. Avoids busy-waiting and timer leaks Include proper typing and comments explaining design decisions. assert: - type: contains value: 'class' reason: Should define a TypeScript class - type: contains-any value: ['Promise', 'async', 'await'] reason: Should use async primitives - type: llm-rubric value: | The code should: 1. Implement correct token-bucket math (refill proportional to elapsed time, capped at capacity) 2. Queue waiters instead of busy-waiting 3. Clean up timers when acquire() times out or resolves 4. Use precise TypeScript types (no `any`) 5. Include comments explaining the concurrency-safety reasoning 6. Be production-ready (not a toy example) # Code review with prioritized, nuanced feedback - vars: task: | Review this Express handler and provide feedback: ```js app.post('/upload', async (req, res) => { const file = req.files.document; const dest = path.join('/uploads', req.body.filename); await file.mv(dest); const meta = JSON.parse(req.body.metadata); db.query(`INSERT INTO uploads (path, owner) VALUES ('${dest}', '${meta.owner}')`); res.json({ ok: true, path: dest }); }); ``` Identify issues, suggest improvements, and explain the reasoning behind each suggestion. Prioritize by severity. assert: - type: contains-any value: ['injection', 'traversal', 'sanitize', 'parameterized'] reason: Should identify the SQL injection and path traversal vulnerabilities - type: llm-rubric value: | The review should identify multiple issues, prioritized by severity: 1. SQL injection via string-interpolated query (critical) 2. Path traversal via user-controlled filename (critical) 3. Unhandled JSON.parse exception on malformed metadata 4. No validation that req.files.document exists 5. Unawaited/unchecked db.query result For each issue, it should: - Explain why it's a problem - Suggest specific improvements (parameterized queries, basename/allowlist for paths) - Provide example code where helpful