stillworks 0.1.1

Take a snapshot of what your code does, then see if your edit moved anything. For code with no tests. Zero dependencies.

stillworks

Take a snapshot of what your code does. After you change it, see if anything moved.

You have to edit a file that has no tests. Afterwards, how do you know you only changed the thing you meant to change?

stillworks lock runs your code and writes down what it gives back. stillworks check runs it again after your edit and tells you if any answer is different. That's the whole idea.

It's a safety net for one risky change, not a test suite you keep. Set it up in under a minute, delete it when you're done.

Two verbs: lock and check. Zero dependencies. Plain CLI, so every coding agent can use it (Claude Code, Codex, OpenCode, Cursor, aider — anything that can run a shell command). Python ≥ 3.9, stdlib only, MIT license.

pip install 'stillworks[all]'   # all four agent tools (see below)
pip install stillworks          # or just this one, zero dependencies

stillworks lock src/pricing.py --fuzz 8   # before: record real behavior
# ... let your AI agent refactor pricing.py ...
stillworks check                          # after: did behavior change?

CHANGED  apply_discount#3  (apply_discount)
         args: ((100.0, 'GOLD'), {})
         was:  85.0
         now:  90.0
BEHAVIOR CHANGED: 24 records — 1 CHANGED, 23 OK

Exit code 1 — the merge gate closes. If the change was intentional: stillworks accept apply_discount#3, and it becomes the new baseline.

Should you just write tests instead?

Often, yes — and you should. A real test suite (pytest, plus approvaltests, syrupy or pytest-regressions for snapshots) says what the code is meant to do. That's more valuable than what it happens to do today, and it's worth keeping around. If you can write those tests, or have an AI write them for you — that works, and it beats this tool.

Use stillworks when you're not there yet:

• The code has no tests and you're changing it today. Snapshot it, make the change, check, delete the snapshot. Nothing left to maintain.
• You don't actually know what it's supposed to do. Nobody does; the person who wrote it left. What it does now is the only thing you can hold on to.
• It's not Python, or you can't import it. --cmd "make report" works on anything you can run from a terminal.
• You want the check working in the next minute. No test framework, no setup, one command.

What it does not promise. It records what your code did, not what it should do. If the code has a bug today, the snapshot keeps the bug. A green check means nothing moved — it never means this is correct. And it has no special magic: anything can run your code and compare, including you and including an AI. What you're buying here is that there's no test code to write.

Three ways to capture behavior

mode	command	best for
Sampled inputs	stillworks lock src/mod.py --fuzz 8	annotated Python functions — seeded inputs, including the literals your own branches compare against
Record a run	stillworks lock src/mod.py --run scripts/daily.py	real usage — records every call your script makes into the module
Commands	stillworks lock --cmd "python report.py 2024" --cmd "make summary"	any language — records exit code, stdout, stderr

Modes combine — in a single lock invocation (lock replaces any existing baseline and warns when it does):

stillworks lock src/mod.py --fuzz 8 --run scripts/daily.py --cmd "make summary"

Exceptions are recorded as behavior too: if divide(1, 0) raises ZeroDivisionError today, a refactor that silently returns 0 is a CHANGED, not a pass.

Nondeterministic functions (time, random, network) are detected at lock time — each record is replayed immediately, and anything that doesn't reproduce is flagged and excluded from gating rather than becoming a flaky test.

The workflow with a coding agent

stillworks lock src/billing.py --run scripts/month_end.py   # 1. baseline
# 2. "hey Claude, refactor billing.py to use the new tax API"
stillworks check                                            # 3. gate
stillworks accept tax_total#2                               # 4. bless intended diffs
stillworks report -o EVIDENCE.md                            # 5. attach to the PR

The report is a human-readable evidence document: what was locked, what reproduced, what changed and who accepted it — for the reviewer who has to trust the merge. (report without -o prints to stdout.) All commands take --project DIR to operate on another directory.

For coding agents: CLI, skill, or MCP

• CLI (recommended): it's just a shell command — every agent already knows how to use it. Tell your agent: "use stillworks lock before editing and stillworks check after."
• Claude Code skill: copy skill/ into .claude/skills/stillworks/ and the agent locks/checks automatically around risky edits.
• MCP server: stillworks mcp serves the four operations over stdio for agents that prefer tools to shells. Zero-dependency, subprocess-isolated.

{ "mcpServers": { "stillworks": { "command": "stillworks", "args": ["mcp"] } } }

What else is installed

$ stillworks tools
  stillworks  0.1.1  record what your code does now, catch when it changes
  unedit      0.1.1  a safety net for letting an agent loose on your files
  agentdiff   —      see what the agent actually changed, before you merge
  agentlog    0.2.0  what did your coding agent actually do today?

  missing: agentdiff
  install:  pip install agentdiff-cli
  or all four:  pip install 'stillworks[all]'

It finds the others on your PATH and asks each for its version — it never imports them, so the extra stays genuinely optional and each tool keeps its own release cycle. Always exits 0; it reports, it does not judge. --json for scripts.

No pip available (managed environments, PEP 668)? It's stdlib-only, so a checkout works as-is:

git clone https://github.com/iselur/stillworks && PYTHONPATH=stillworks python3 -m stillworks --help
# or: pipx install stillworks

Prior art (and what's different)

The idea is characterization testing — Michael Feathers, Working Effectively with Legacy Code (2004): when code has no tests, record what it does and pin that. Snapshot-testing libraries like approvaltests, syrupy, and pytest-regressions do this well inside a test suite you write, and they are the better tool once that suite exists — they give you names, fixtures, and intent alongside the snapshots.

stillworks differs in one deliberate way: there is no test code to write. It captures behavior from annotations, from a real script run, or from shell commands (any language), compares with one CLI verb, and needs no test framework, no server, and no dependencies — which is exactly what a coding agent, or a human mid-refactor, can use in thirty seconds. That is a convenience difference, not a stronger guarantee: a snapshot test asserting the same recorded values is worth exactly as much.

Honest limits (v0.1)

• Function recording targets module-level Python functions. Methods and class-heavy code: use --cmd probes (they work for anything executable).
• --fuzz is seeded sampling, not coverage-guided fuzzing. It needs positional parameters annotated with int/float/str/bool/list/ dict. Unannotated params, Optional/Union/Literal/Enum/custom types, and functions with required keyword-only params are skipped — and named in the output, with a hint to use --run or --cmd.
• Default parameter values are not exercised by --fuzz; a behavior change hiding behind a default only shows up via --run or --cmd capture.
• Functions returning generators/iterators are compared by materializing the first 200 items during --fuzz/check; during --run recording they are skipped (the iterator must reach your script unconsumed).
• lock and check execute your code — functions with side effects (writes, sends, charges) run once per record per verb. Point it at pure or read-only code paths, or use --cmd against a sandbox.
• Arguments are pickled into .stillworks/lock.json for replay; exotic unpicklable inputs are counted and skipped, not silently dropped. Treat the lockfile like a fixture: don't lock functions whose arguments are secrets, and don't check lockfiles from sources you don't trust (unpickling runs code).
• stdout of recorded function calls isn't captured (command records capture it fully).

What stillworks is not

Not a test framework and not a replacement for one — if the code is going to live a long time, it deserves tests that say what it should do. Not a security scanner. Not an LLM product (it never calls a model, needs no API key, sends nothing anywhere). It does one thing: catch behavior changes you didn't intend, on code that has nothing else guarding it.

Part of a small family

Four tools for working with coding agents, same house style: zero dependencies, MIT, no API key, nothing leaves your machine. None of them call a model — that is the point, since the thing being checked already is one.

• stillworks — record what your code does now, catch when it changes later ← you are here
• agentdiff — see what the agent actually changed, before you merge
• agentlog — what did your coding agent actually do today?
• unedit — a safety net for letting an agent loose on your files

One install gets all four, and stillworks tools says which ones you have:

pip install 'stillworks[all]'
stillworks tools

License

MIT. Contributions welcome — especially capture modes for more languages.