Quell reads your docstrings, Pydantic models, and type annotations, extracts every testable requirement, finds which ones have no test, generates pytest tests via a rule engine, verifies each test through a 5-gate pipeline, and writes only proven tests to disk.

Does Quell require an LLM API key?

The rule engine runs entirely in-process — no source code is ever transmitted. ~75% of edge cases are handled with no network call and no API key. LLM fallback is opt-in and only sends the function signature, never the full body.

What is the 5-gate pipeline?

Every generated test must pass: Gate 1 (AST valid Python), Gate 2 (not already in a test file), Gate 3 (no shell calls or file writes), Gate 4 (passes against original code), Gate 5 (fails when the requirement is violated). Only gate-5-verified tests are written to disk.

What is the Production Readiness Score (PRS)?

PRS = (WRITTEN × 1.0 + SCAFFOLDED × 0.5) / total_requirements × 100. Tiers: 80-100 Production Ready, 60-79 Review Needed, 0-59 Needs Work.

How is Quell different from GitHub Copilot or Qodo for test generation?

Quell reads specifications that already exist in your code — it does not generate tests from scratch. It finds requirements already documented in your docstrings, Pydantic models, and type annotations that have no test. The 5-gate pipeline, especially Gate 5 (violation injection), verifies each test actually catches the bug it claims to catch. This verification step is not present in Copilot, Qodo, or Hypothesis.

Can Quell be used in CI pipelines?

Yes. Run quell ci src/ --threshold 80 to fail CI if PRS falls below 80. Set prs_threshold in pyproject.toml under [tool.quell]. Works with GitHub Actions, GitLab CI, and any system that checks exit codes.

Can Claude Code or Cursor use Quelltest directly?

Yes. Quelltest ships a local MCP server: install with pip install quelltest[mcp], then add {"mcpServers": {"quelltest": {"command": "quelltest-mcp"}}} to your project's .mcp.json. The agent can then call find_edge_cases, write_verified_tests, get_prs_score, prove_file, and reproduce_bug directly — no terminal needed. A Claude Code plugin is also available via /plugin marketplace add quelltest/quelltest-lib.

Does the Quelltest MCP server send my code anywhere?

No. The local MCP server (quelltest-mcp) runs entirely on your machine over stdio — no cloud, no network calls, no telemetry. The separate opt-in Claude.ai connector only ever transmits sanitized metrics (PRS score, bucket counts, test names, flag locations); a sanitizer blocks source code, function bodies, and docstrings structurally.

How do I add Quelltest as a Claude.ai connector?

In Claude.ai, go to Settings, then Connectors, then Add custom connector, and enter https://mcp.quelltest.com. Claude discovers the OAuth endpoints automatically and walks you through authorization.

npm quickstart

Install Quelltest, scan a source directory, review JSON output, and preview safe test scaffolds.

npm install -D quelltest
npx quell find src/
npx quell find src/ --json > quell-report.json
npx quell score src/ --threshold 60
npx quell generate src/ --json

Read a finding

Each finding includes a stable ID, file, line, category, evidence, and a suggestion. Categories include throws, boundary, nullish, jsdoc, schema, and async.

Generate safely

quell generate is a dry run by default. Review the proposed scaffolds first. Add --write only when you want files written under tests/quelltest/.

npx quell generate src/ --write

Generated scaffolds are marked SCAFFOLDED until they are connected to your application and verified by your chosen runner.