eyaltoledano/claude-task-master · error

Failed to generate tasks using generateObject fallback

Error message

Failed to generate tasks using generateObject fallback

What it means

This error is thrown at the end of processWithGenerateObject in parse-prd-streaming.js when the AI SDK generateObject fallback could not produce a parseable tasks result. The streaming parse path first tries normal streaming; if that fails it retries with generateObject, and if that retry also returns nothing usable, this terminal error is raised.

Source

Thrown at scripts/modules/task-manager/parse-prd/parse-prd-streaming.js:620

				estimateTokens(JSON.stringify(tasks));
			const inputTokens =
				result.telemetryData?.inputTokens || context.estimatedInputTokens;

			context.progressTracker.updateTokens(inputTokens, outputTokens, false);
		}

		return {
			parsedTasks: tasks.tasks,
			estimatedOutputTokens:
				result.telemetryData?.outputTokens ||
				estimateTokens(JSON.stringify(tasks)),
			actualInputTokens: result.telemetryData?.inputTokens,
			telemetryData: result.telemetryData,
			usedFallback: true
		};
	}

	throw new Error('Failed to generate tasks using generateObject fallback');
}

/**
 * Prepare final result with cleanup
 */
function prepareFinalResult(
	streamingResult,
	aiServiceResponse,
	estimatedInputTokens,
	progressTracker
) {
	let summary = null;
	if (progressTracker) {
		summary = progressTracker.getSummary();
		progressTracker.cleanup();
	}

	// If we have actual usage data from streaming, update the AI service response

View on GitHub (pinned to c0c98d367c)

Solutions

1. Verify the AI provider API key is set and valid in your environment/mcp.json (e.g. ANTHROPIC_API_KEY / relevant provider key).
2. Check model availability and provider status; switch to a different configured model via --model or config.
3. Reduce the PRD size or lower num-tasks so output fits within context/token limits.
4. Check network/proxy connectivity to the AI provider endpoint.
5. Retry the parse-prd command; if persistent, run with debug logging to see the underlying generateObject failure.

Example fix

// before
npx task-master parse-prd --input=huge-prd.md --num-tasks=50
// after
npx task-master parse-prd --input=prd.md --num-tasks=10 --force

const apiKey = process.env.ANTHROPIC_API_KEY || providerKeyFromConfig;
if (!apiKey) throw new Error('AI provider API key not configured');
const prdText = fs.readFileSync(prdPath, 'utf8');
if (!prdText.trim()) throw new Error('PRD file is empty');
if (prdText.length > 150000) throw new Error('PRD too large; split it before parsing');

function hasTasksResult(r) {
  return r != null && typeof r === 'object' &&
    Array.isArray(r.tasks) && r.tasks.length > 0;
}

try {
  const result = await tmCore.tasks.parsePrd(prdPath, { numTasks: 10 });
} catch (err) {
  if (err.message.includes('Failed to generate tasks')) {
    console.error('AI generation failed. Check API key, model availability, and PRD size.', { cause: err });
    // optionally retry once with a smaller task count or fallback model
  } else throw err;
}

When it happens

Trigger: processStreamResponse falls back to processWithGenerateObject after a streaming failure, and the generateObject call throws, returns null/undefined result, or returns a result without tasks despite retrying.

Common situations: Invalid or unauthenticated API keys, AI provider outages or rate limits, PRD content too large for the model context, malformed PRD text producing schema-invalid output, network connectivity problems.

Related errors

• ${result.message} || Update failed for task ${taskId}. The s
• File storage does not support updateTaskWithPrompt. Client-s
• File storage does not support expandTaskWithPrompt. Client-s
• Input file ${prdPath} is empty or could not be read.
• Failed to load prompt template: ${error.message}

AI-assisted analysis of eyaltoledano/claude-task-master@c0c98d367c (2026-08-29). Data as JSON: /api/errors/f1c0aade614cbe69. Report an issue: GitHub.