tsfix

Two-layer TypeScript error recovery for LLM-generated code — fix TS2304, TS2305, TS2551, TS2552, TS2724 deterministically with the same engine that powers VS Code's Quick Fix, and escalate the rest to a single-file LLM mend.

@shipispec/tsfix is what you reach for when you've just generated a few hundred files of TypeScript with an LLM and tsc --noEmit is screaming at you. It runs in two layers:

• Layer 0/1 — Deterministic. Borrows the same TypeScript Language Service that powers VS Code's "Quick Fix" lightbulb and runs it as a CLI. Fixes typos, missing imports, and did-you-mean errors with no LLM, no network, no config.
• Layer 2 — Opt-in. A single-file LLM mend agent (Vercel AI SDK + Anthropic) that picks up what Layer 0 abstains on: TS2339 (property doesn't exist), TS7006 (implicit any), TS2741 (missing required prop), and other cases where the LSP can't statically derive the fix. Driven by type-context injection — when tsc says "Property 'foo' doesn't exist on type 'Bar'", tsfix resolves the Bar declaration via the TypeChecker and feeds its source to the model.

Layer 2 only runs if you explicitly call its API or set ANTHROPIC_API_KEY and use the runMendLoop entry point. The default tsfix --workspace ... CLI is still Layer 0/1 only.

Before / after (Layer 0)

$ tsc --noEmit
src/api.ts:5:2  - error TS2552: Cannot find name 'consol'. Did you mean 'console'?
src/api.ts:8:5  - error TS2305: Module '"react"' has no exported member 'ueState'.
src/api.ts:12:14 - error TS2551: Property 'lenght' does not exist on type 'string[]'. Did you mean 'length'?

Found 3 errors in 1 file.

$ npx @shipispec/tsfix --workspace .
[ts-lsp-fixer] applied 3 fixes across 1 file

$ tsc --noEmit
$ # 0 errors

30-second cold start

cd your-broken-project
npx @shipispec/tsfix --workspace .

No config file. Exit code conventions:

Preview what would change without writing to disk:

npx @shipispec/tsfix --workspace . --dry-run

Machine-readable output for piping into other tools:

npx @shipispec/tsfix --workspace . --json

All flags

The CLI does not run Layer 2 — call the library API for that (below).

What Layer 0 fixes

Against a 14-fixture benchmark spanning typos, did-you-mean cases, multi-file ripples, and 4 API-drift scenarios: 14/14 fixtures pass and 14/25 errors are auto-fixed (56%). The remaining errors are intentionally outside Layer 0's scope and escape to Layer 2.

What Layer 0 does not fix (Layer 2 picks these up)

By design, Layer 0 only applies fixes that are deterministic and non-structural. It refuses to:

• Add or remove function declarations
• Insert type annotations or change types
• Modify control flow (await insertions, async propagation)
• Rewrite JSX trees
• Add object-literal stub properties

The internal allowlist is two-layered: error codes (SAFE_FIXABLE_CODES) and Quick Fix names (SAFE_FIX_NAMES = ['import', 'fixImport', 'spelling', 'fixSpelling']). When the language service offers anything outside that allowlist, Layer 0 abstains and surfaces the error so Layer 2 (or a human) can pick it up.

Layer 2 is built for the cases the LSP can't statically resolve:

• TS2339 — Property doesn't exist on type. The LLM needs to see the type's declaration to decide whether the receiver should grow a field, the call site has a typo with no near-match, or the receiver is the wrong type entirely.
• TS7006 — Implicit any. The LLM picks the right annotation from surrounding context.
• TS2741 — Missing required property. The LLM sees the contextual type and supplies a real value, not a placeholder.

Against a 35-fixture Layer-2 benchmark (3 hand-authored minimal + 2 realistic + 30 ts-morph-generated mutations across TS2339/TS7006/TS2741), 35/35 pass at $0.001/fixture avg, P95 latency ~1.5s on claude-haiku-4-5. Caveat: the 30 generated fixtures are mutations of 3 seeds — real-world diversity will move these numbers.

The four-layer model

Layer 0 — Prevention      (prompt rules, exported-API injection — your problem)
Layer 1 — Deterministic   (this package: LSP auto-fix, CLI default)
Layer 2 — Single-file LLM (this package: opt-in via library API)
─────────────────────────────────────────────────────────────────
Layer 3 — Multi-file LLM  (planned: blast-radius search/replace via findReferences)
Layer 4 — Stub-and-continue (planned: escape hatch)

The bet: roughly half of TypeScript errors in LLM output are deterministically fixable. By catching them in Layer 1 you dodge the LLM tax (latency, cost, nondeterminism) on the easy half. Layer 2 takes the other half — but only when you explicitly invoke it.

Library API

Layer 0/1 — deterministic loop

import { runValidationLoop } from '@shipispec/tsfix';

const result = runValidationLoop({
  workspaceRoot: '/path/to/your/project',
  // Optional:
  // targetFiles: ['src/api.ts'],
  // dryRun: true,
  // logger: { info: console.log, warn: console.warn, error: console.error },
});

result.errorsBefore;          // number
result.errorsAfter;           // number
result.lspFixer.fixesApplied; // number
result.lspFixer.filesEdited;  // string[]
result.passed;                // boolean — true if errorsAfter === 0

Other Layer 0/1 exports:

• runInProcessTsc(opts) — validation only, no fixer. Returns structured diagnostics.
• runLSPFixerPass(opts) — Layer 0 fixer alone, no validation loop wrapper.
• discoverTsFiles(workspaceRoot) — file-walking helper. Skips node_modules, .next, dist, build, out, coverage, .git.

Layer 2 — LLM mend (opt-in)

import { runValidationLoop, runMendLoop } from '@shipispec/tsfix';

// Layer 0/1 first.
const layer1 = runValidationLoop({ workspaceRoot });

if (!layer1.passed) {
  // Layer 2 escalation.
  const layer2 = await runMendLoop({
    context: {
      workspaceRoot,
      diagnostics: layer1.remainingDiagnostics,
      erroredFiles: layer1.lspFixer.filesWithErrors,
      // Optional fields that improve mend quality:
      // taskDescription: 'Build a user CRUD module',
      // featureSpecText: '...the markdown spec...',
      // acceptanceCriteria: '...',
      // installedTypes: '...',  // compact API surface from npm deps
    },
    llm: {
      provider: 'anthropic',
      model: 'claude-haiku-4-5',
      apiKey: process.env.ANTHROPIC_API_KEY,
    },
    maxIterations: 3,
  });

  console.log(layer2.stopReason);  // 'fixed' | 'noProgress' | 'regressed' | 'maxIterations'
  console.log(layer2.totalCostUsd);
}

Other Layer 2 exports:

• mendSingleFile(opts) — one LLM call for one file. The building block under runMendLoop.
• getTypeContext(opts) — resolve a Diagnostic to its declaring type via the TS Language Service and return ±N lines around the declaration. The architectural moat — every other LLM-driven repair tool uses generic grep or repo-maps.
• parseEditBlocks(text) / applyEditBlocks(opts) — Aider-style SEARCH/REPLACE patch parser + 3-tier fuzzy applier.
• Types: MendContext, LayerEvent, Diagnostic, plus the per-function option/result types.

Trust model

Layer 0/1 loads typescript from your workspace's node_modules — it does not bundle its own. This ensures the fixer behaves identically to the tsc your project actually compiles with.

Run tsfix only on workspaces you trust. Loading typescript from an attacker-controlled node_modules is equivalent to running node_modules/.bin/tsc against it.

Network surface (Layer 0/1): none. No telemetry, no calls home, no background processes, no config files written outside --workspace.

Network surface (Layer 2): every mendSingleFile call hits Anthropic's API via the Vercel AI SDK. The source files in MendContext.erroredFiles and the resolved type-context slices are sent in the prompt. If your code is sensitive, do not call Layer 2 — the CLI never does, and the library exports are explicit.

Engines

• Node >=20.9.0
• TypeScript >=5.0.0 (peer dep — must be installed in your workspace)

If your workspace has no node_modules/typescript, tsfix will fail with a clear error:

error: this workspace has no TypeScript installed.
run: npm install --save-dev typescript

Contributing

Adding a Layer-0 fix

1. Probe — write a tiny test workspace with the exact error you want fixable. Drop it under fixtures/<descriptive-name>/ with an expected.json declaring errorsBefore, errorsAfterMax, lspFixesAppliedMin/Max, and mustPass.
2. Verify — run npm run benchmark -- --fixture <name> and inspect what the language service offers (the fix.fixName field).
3. Allowlist change — if fixName is unsafe (fixMissingFunctionDeclaration, addMissingPropertyAndOptional, etc.), document why we don't trust it. Otherwise, add the error code to SAFE_FIXABLE_CODES and the fix name to SAFE_FIX_NAMES in src/tsLanguageServiceFixer.ts.
4. Lock it in — confirm all existing fixtures still pass (npm run benchmark). Open a PR.

Each new code/fix-name pair gets its own fixture. We don't trust the language service blindly — we trust it under specific, pinned conditions.

Adding a Layer-2 fixture

Layer-2 fixtures live under fixtures/ alongside Layer-0 ones, identified by expectedErrorCode (singular) or costUsdMax in their expected.json. The Layer-0 benchmark skips them; npm run benchmark:llm runs them against Anthropic.

• Hand-author one under fixtures/mend-<descriptive-name>/ for new error classes.
• Or generate one via npm run generate-fixtures -- --code=TS2339 --seed=apiRouter.ts --count=10 --rng-seed=42. The generator validates every mutation through Layer 0 first to confirm Layer 0 abstains (otherwise it's not Layer 2 territory).

Pre-publish gates

• npm run benchmark — Layer 0, 14 fixtures, no network.
• npm run benchmark:llm — Layer 2, 35 fixtures, requires ANTHROPIC_API_KEY. Total cost ~$0.04 per run.
• npm run matrix — runs the local tarball against 6 distinct project shapes (Next.js, Vite + React, plain nodenext, plain bundler, plain CommonJS, monorepo with project references). Adds ~3 min; run manually before tagging.

License

MIT.

See also

• CHANGELOG.md — release notes per version.
• ARCHITECTURE.md — internal design rationale (the four-layer model, the workspace lib-path workaround).
• STATUS.md — current snapshot, gaps, and roadmap state.
• tsc-defense-roadmap.md — phased plan.
• docs/internal-orientation.md — the original SpecToShip-context README, kept for contributors who want the design history.