Show HN: I taught Claude Code to file Indian income-tax returns (ITR)

Developer Karan B. released itr-wala, an open-source tool that lets users file Indian income-tax returns (ITR) from a terminal via AI agents like Claude Code, with all tax math computed by deterministic Python code rather than an LLM. The tool runs 47 golden tests derived from statute, a 104-test input validator, and a property-based fuzzer that has swept over 350,000 cases to catch bugs such as surcharge marginal-relief errors and floating-point rounding edges. It splits work so the AI reads documents and interviews users while Python handles slab calculations, rebates, surcharges, cess, and interest, and requires users to handle only payment, submission, and e-verification.

File your Indian income tax return from your terminal. No CA, no ₹3,000 fee, no 3 hours on the portal. Every rupee of tax math computed by tested code, not by an LLM. ⏳ AY 2026-27 deadlines: ITR-1/2 → 31 July 2026 · ITR-3/4 non-audit → 31 August 2026. Claude Code /plugin marketplace add karanb192/itr-wala /plugin install itr-wala@itr-wala Or the plain-skill route Claude by default; also: -s codex, -s gemini, -s all curl -fsSL https://raw.githubusercontent.com/karanb192/itr-wala/main/install.sh | bash Prefer not to pipe curl into bash? Good instinct. Clone the repo, read install.sh ~80 lines , then run it. Then open your agent and say "file my ITR" . Hand it your Form 16 and AIS. It does the rest - except the three things only you should ever do: pay, submit, e-verify . Every AI-tax demo you saw this season had the same silent flaw: the model was doing the arithmetic. LLMs are magnificent at reading a Form 16 and terrible at applying s.87A marginal relief. One transposed digit and your "free filing" costs you a tax notice. itr-wala splits the work the way it should be split: | The AI does | Deterministic Python does | |---|---| | Reads your Form 16, AIS, broker P&L | Every slab, rebate, surcharge, cess calculation | | Interviews you for missed deductions | Old vs new regime comparison | | Explains every number in plain language | 87A marginal relief, 111A/112A/VDA special rates | | Walks you through the portal | 234A/B/C interest, 234F late fee | | Schema validation that rejects typo'd inputs | | | Cross-checks your TDS against 26AS/AIS totals | The math is defended in three layers, all shipped in the repo and run in CI on every commit: 47 golden tests - every expected value hand-derived from the statute first: the 87A rebate cliff and its marginal relief, capital-gains exemption ordering, s.71 loss set-off, the surcharge tiers including the exclusive-income tests for the 25%/37% slabs and the 15% ceiling on capital-gains tax , and 234A/B/C/F interest down to the month-counting and challan-date edge cases. A 104-test suite for the input validator - the gate that rejects malformed, mistyped, or PAN-bearing inputs before they can reach the engine. A property-based fuzzer scripts/fuzz engine.py - generates thousands of randomized, boundary-biased returns and asserts invariants the law implies: more income can never mean less tax in the new regime, cess is exactly 4%, rounding follows s.288A/288B, recommendations match the cheaper legal option. Seeded and deterministic; CI replays 3,000 cases on every commit, and 350,000+ were swept before release. The skill runs the golden suite in front of you before touching your return: bash $ python3 skills/itr-wala/scripts/test tax engine.py ............................................... Ran 47 tests in 0.002s OK Installed as a plugin and can't find the path? Just ask the agent to "run the itr-wala self-test". If your CA can show you their test suite, hire them. These layers exist because they catch real bugs. Hand-deriving every scenario caught an early build that denied surcharge marginal relief on capital-gains-heavy incomes, and the fuzzer caught a one-in-350,000 floating-point rounding edge where ₹52,880 more salary computed ₹10 less tax. Both are fixed and pinned as regression tests. That find-fix-pin loop is the thing a prompt-only tax tool cannot run. Self-test - the engine proves its math before you trust it. Documents - drop Form 16 + AIS JSON into a folder; it tells you exactly where to download each one. Extract & validate - every number transcribed verbatim into income.json , then a strict validator cross-checks totals against your documents. Unknown key? Rejected. TDS doesn't match 26AS? Flagged. Deduction hunt - a proactive interview 80C, 80D, NPS, HRA, home loan… , because the portal will never ask you. Both regimes, computed - a comparison table with the exact rupee savings. The regime gap is routinely five figures; this table is where it shows up. Filing pack - every portal field mapped to its value, in order, plus the final payable/refund figure the portal must match to the rupee. The portal, together - it narrates each schedule; you type. It never sees your password or OTP. You alone click Pay, Submit, and e-Verify. Real output, reproducible from the bundled fictional example - python3 skills/itr-wala/scripts/tax engine.py skills/itr-wala/assets/example-income.json : Income-tax computation - FY 2025-26 AY 2026-27 ================================================================ NEW REGIME Gross total income 26,06,700 Total income 25,06,700 TOTAL TAX 3,00,350 NET PAYABLE -ve=refund 720 OLD REGIME Gross total income 22,09,300 Total income 18,74,300 TOTAL TAX 3,39,730 NET PAYABLE -ve=refund 43,530 ================================================================ RECOMMENDED: NEW regime saves Rs. 42,811 - The Python scripts run entirely on your machine . Tax math never leaves. - Documents you ask the AI to read are processed by the model - that part does leave your machine, like anything you paste into an AI tool. The skill tells you this up front and invites you to redact PAN/Aadhaar/account numbers first : they're not needed for computation, and that's enforced as a mechanism, not a plea - the validator rejects any input file containing a PAN-shaped or Aadhaar-shaped string . - A generated .gitignore keeps tax documents out of your repos. - Built by someone who files his own taxes with it https://karanbansal.in - and who happens to do security for a living DEFCON/OWASP speaker, Head of AI at an application-security company . In scope AY 2026-27, resident individuals : salary multiple employers, retirement exemptions like gratuity and leave encashment in both regimes , house property including s.71 loss set-off, equity/MF capital gains 111A/112A/112, grandfathering-aware exemption ordering , debt MF, crypto/VDA, lottery and online-game winnings 115BB/115BBJ , interest & dividends, family pension with the s.57 iia deduction, s.89 arrears relief, presumptive income 44AD/ADA basics , all Chapter VI-A deductions, both regimes, surcharge with marginal relief, advance-tax interest computed to actual challan dates, late fees, belated returns including the s.115BAC 6 rule that locks belated filers out of the old regime - it will tell you, not let you find out from a notice , ITR-1/2/3/4 form selection. Out of scope - it will say so and point you to a CA rather than guess: non-residents/RNOR, F&O and intraday, audit cases, foreign tax credit Form 67/DTAA , ESOP deferral, the property indexation option, buyback capital-loss entries, agricultural income above ₹5,000. Partial coverage is computed honestly; the rest is never silently approximated. Hard boundaries, always: never your password or OTP, never clicks Pay/Submit/e-Verify, never fabricates a deduction. Lowest legal tax. Can I trust an LLM with my taxes? No - that's the point. You're trusting a tested Python engine with the math and an LLM with reading PDFs and explaining things, which are the two things each is actually good at. Run the test suite yourself. But the LLM still reads the documents - what if it misreads a number? True, and worth being precise about: transcription is the one step the model touches, so a misread digit is the residual risk. That's why every figure is cross-checked against independent documents Form 16 vs 26AS vs AIS - a single-document misread fails validation , recorded next to its source citation, and shown to you in the filing pack before anything is filed. If the model misreads and every cross-check misses it, you'll see the wrong number with its citation - not a hidden one. Why not just use ClearTax/Quicko/a CA? Use whatever you trust. This is for people who'd rather review every number themselves than pay ₹3,000+ to hope someone else did. The filing pack it generates is also a great ₹0 first draft to hand a CA for a cheap review. Is this allowed? Yes. You prepare your own return and file it yourself on the government portal - same as using the portal's own forms, just with better preparation. This tool never submits anything on your behalf. What happens next year? Rates live in one constants block, pinned to AY 2026-27, with the test suite enforcing them. The skill refuses to compute other years rather than silently using stale slabs. New Finance Act → one PR → tests updated. Windows? WSL works today; native Windows paths are on the roadmap. macOS and Linux are first-class. | Tool | How | |---|---| Claude Code recommended - updates with /plugin marketplace update itr-wala | /plugin marketplace add karanb192/itr-wala → /plugin install itr-wala@itr-wala | | Claude Code plain skill | curl -fsSL https://raw.githubusercontent.com/karanb192/itr-wala/main/install.sh | bash | | OpenAI Codex CLI | … | bash -s codex installs to ~/.agents/skills + ~/.codex/skills ; invoke with $itr-wala | | Gemini CLI | … | bash -s gemini | | Everything | … | bash -s all | Requirements: python3 3.9+ stdlib only - zero pip installs , git for the curl installer. - Generate the offline-utility upload JSON against the official published schema upload one file instead of typing 20 schedules - RSU/ESPP + Schedule FA depth the most underserved, highest-anxiety segment - Revised-return s.139 5 workflow through 31 Mar 2027 - belated returns already work, so this repo doesn't expire on Aug 1 - Native Windows installer · one-click .skill bundle for Claude desktop This is meant to be a community tool. Rates change every Finance Act, portal notes rot mid-season, and edge cases surface all year. PRs and issues are welcome - see CONTRIBUTING.md /karanb192/itr-wala/blob/main/CONTRIBUTING.md . The one hard rule: any change to a tax figure ships with a hand-derived test and its statutory source. It's filing season - bug reports get priority, wrong-rate reports get top priority. Computation bug: open an issue with a minimal income.json that reproduces it. Start from skills/itr-wala/assets/example-income.json and change only what's needed. Never paste your real numbers, documents, PAN, or portal screenshots with identifiers. The validator refuses PAN-shaped strings for exactly this reason. Doc/portal-flow bug: quote the reference file and line; the portal changes often and field notes rot fastest. shivprime94/file-itr https://github.com/shivprime94/file-itr MIT - the first Indian ITR skill; its hard-won portal field notes and AIS SFT-code research informed our reference docs. This project's thesis is different deterministic engine + validators + tests vs. pure prompting , but they walked first. robbalian/claude-tax-filing https://github.com/robbalian/claude-tax-filing - proved the scripts-not-vibes pattern for US returns. anthropics/skills https://github.com/anthropics/skills - the skill-structure conventions this follows. MIT - see LICENSE /karanb192/itr-wala/blob/main/LICENSE . Reference material adapted from the MIT-licensed file-itr https://github.com/shivprime94/file-itr . itr-wala is open-source software, not a chartered accountant, and nothing here is professional tax advice. It computes with tested code and shows you everything, but you review, you file, and responsibility for your return stays with you. When in doubt, hand the generated filing pack to a CA - it's built for exactly that. Found it useful? Send it to the friend who still hasn't filed. ⭐