What causes "No text stream provided" in eyaltoledano/claude-task-master?

Ensure the AI stream is actually fetched and non-empty before calling parse (check the response body/text exists).

No text stream provided

Error message

No text stream provided

What it means

The StreamParser's public parse() method requires a text stream (string or stream of AI output) to process. It throws a plain Error immediately if the argument is falsy (null, undefined, or empty), before any parsing begins. This is a fail-fast guard: the parser cannot produce structured JSON output without input text, so it aborts rather than silently returning empty results.

Source

Thrown at src/utils/stream-parser.js:361

		this.currentSize = newSize;
	}
}

/**
 * Main orchestrator for stream parsing
 */
class StreamParserOrchestrator {
	constructor(config) {
		this.config = new StreamParserConfig(config);
		this.progressTracker = new ProgressTracker(this.config);
		this.bufferValidator = new BufferSizeValidator(this.config.maxBufferSize);
		this.jsonParser = new JSONStreamParser(this.config, this.progressTracker);
		this.fallbackParser = new FallbackParser(this.config, this.progressTracker);
	}

	async parse(textStream) {
		if (!textStream) {
			throw new Error('No text stream provided');
		}

		await this.processStream(textStream);
		await this.waitForParsingCompletion();

		const usedFallback = await this.attemptFallbackIfNeeded();

		return this.buildResult(usedFallback);
	}

	async processStream(textStream) {
		const processor = new StreamProcessor((chunk) => {
			this.bufferValidator.validateChunk(
				this.progressTracker.accumulatedText,
				chunk
			);
			this.progressTracker.addText(chunk);
			this.jsonParser.write(chunk);

View on GitHub (pinned to c0c98d367c)

Solutions

Ensure the AI stream is actually fetched and non-empty before calling parse (check the response body/text exists).
Log or inspect the value passed to parse; if it comes from a promise or nested property, verify the upstream call succeeded.
Guard the call site: if (!textStream) skip parsing or re-fetch the stream instead of invoking the parser.
If the stream legitimately may be absent, catch this Error and treat it as a no-op rather than a failure.

Example fix

// before
const result = await parser.parse(aiResponse.choices[0].text);
// after
const text = aiResponse?.choices?.[0]?.text;
if (!text) {
  throw new Error('AI response contained no text to parse');
}
const result = await parser.parse(text);

Defensive patterns

Strategy: validation

Validate before calling

function canParse(textStream) {
  return typeof textStream === 'string'
    ? textStream.length > 0
    : textStream != null; // streams/readables pass through
}
// call site
if (!canParse(stream)) {
  throw new Error('Refusing to parse: no AI text stream available');
}
const result = await parser.parse(stream);

Type guard

function hasTextStream(v) {
  return v != null && (typeof v === 'string' || typeof v[Symbol.asyncIterator] === 'function');
}

Try / catch

try {
  await parser.parse(stream);
} catch (err) {
  if (err.message === 'No text stream provided') {
    // recover: re-fetch stream or skip
  } else {
    throw err;
  }
}

Prevention

Always fetch and inspect the AI response before constructing the parser.
Use optional chaining on upstream response objects and fail early with your own descriptive error.
In tests, assert mocks return a non-empty stream string.
Never pass possibly-undefined variables straight into parse().

When it happens

Trigger: Calling streamParser.parse(null), parse(undefined), parse(''), or parse(await somePromiseThatResolvedToUndefined); passing a variable that was never assigned because the upstream AI stream failed to initialize; destructuring a config object and forwarding a missing stream property.

Common situations: Developers wiring the parser to an LLM client whose response object shape changed (e.g. accessing response.text on a failed response), calling parse before the stream is opened, or conditionally skipping stream fetch logic so the variable stays undefined in tests or mocked environments.

Understand the failure class

Background: "missing required argument" and "the following required arguments were not provided": what required-argument errors mean and how to fix them — this error's family across 20 libraries.

Related errors

AI-assisted analysis of eyaltoledano/claude-task-master@c0c98d367c (2026-08-29). Data as JSON: /api/errors/024f5b8c0e041cea. Report an issue: GitHub.