WA5SWI

The 'Providers and models' commit contains no provider feature. agent.py is untouched by the task diff: it still requires AGENT_MODEL_CMD and exits 2 otherwise, with no .agent/settings.json reading, no --model flag, no per-request model field, and no HTTP provider. Ten prior check runs confirm: exit=2, model=missing. What the commit does add is ~50 scratch files under .ololo/tmp (model.sh stubs, stderr logs, per-run settings.json copies) with hardcoded machine-specific absolute paths like /Users/Andrii_Kucherenko/Workspace/ololo/..., plus a test.sh case for the previous task — a commit whose message misrepresents its contents. Governance for this task is silent where it mattered: no written decision about the settings schema, provider resolution, or model-override precedence exists anywhere in the repo, because the decisions were never implemented. Only inherited merit from earlier sessions (stdlib-only declaration in AGENTS.md, a real test.sh harness, one-commit-per-task rhythm) keeps this off the floor.

The task change is exactly what the spec asked: run_bash merges stdout+stderr via stderr=subprocess.STDOUT so the result preserves true write order (agent.py, diff deffc66..8e1957b), and the loop appends 'exit code: ' with is_error=true only on non-zero, keeping the loop alive. The committed probe cc-37wnuf7h/req.2 proves it end-to-end: content 'OUT37wnuf7h\nERR37wnuf7h\nexit code: 3\n', is_error true, model then answers. Cleanliness 7.5: the diff itself is minimal, idiomatic and well-commented ('ponytail' notes explain why, not what); but the file carries an unused import shlex, a no-op from unittest import mock placeholder in the selftest branch, and pre-existing schema-tolerance sprawl in extract_tool_calls (a chain of except Exception: pass and overlapping 'simple shapes' checks) that reads as guesswork accumulation. Committed .ololo/tmp fixture transcripts are harness artifacts, not source, so I weight them lightly. Maintainability 7.5: changed code paths are short, flat and easy to follow, constants named (MAX_ITERS/RETRIES/TIMEOUT), model-boundary failures retried with backoff and a clear stderr message. Deductions: test.sh was not extended to lock in the new merged-order/exit-line behavior, so the only proof is fixture transcripts, not a runnable test; a command whose output lacks a trailing newline makes the exit line concatenate onto it ('xexit code: 3' instead of its own line — spec says 'appends a line'); and subprocess.TimeoutExpired from run_bash is uncaught, so a hanging command crashes the loop at the very boundary a tool runner must guard. A newcomer could safely modify the bash-result path; the dense extractor functions are the only real comprehension tax.

Loop does exactly the required work and no more. Per turn: one json.dumps of the growing conversation, one model pipe, one bash spawn, appends only — req.1..req.6 show byte-identical prefixes growing 1→11 messages, with assistant turns preserved verbatim (original tool_use content blocks) and tool_results fed back exactly, in order, nothing dropped or reordered. The O(history)-per-request shape is the task-mandated protocol (stateless model, full history every call), not an implementation defect; total work across 6 calls stays trivial. No per-turn file I/O in the agent, no re-parsing of already-parsed payloads, no caches or buffers to leak; MAX_ITERS=20 bounds the loop. Sequential execution is correct here since each turn depends on the previous tool result — nothing serializes that could proceed independently. Evidence is behavioral and direct: recorded trace shows calls=6, strict 1 1 2 2 3 3 4 4 5 5 alternation, results=5, exit=0; test.sh asserts conversation growth and retry. Minor dings: run_bash/call_model capture full output into memory with no cap or truncation policy (a tool printing a large file gets slurped whole into the next request — defensible under 'nothing dropped' but the limit is nowhere named); and the OpenAI-fallback branch records only extracted text in history rather than the raw assistant turn, so tool_calls would be dropped from the conversation under that schema — a latent fidelity gap not exercised in the graded run. No timing measurements, but for a protocol task the call/sequence trace is the appropriate instrument and it was captured.

Single well-organized ~280-line agent.py, proportionate to the task: constants at top, subprocess I/O isolated in call_model and run_bash, pure schema-extraction functions (parse_model_output, extract_tool_calls, extract_text) separately testable, and the conversation loop plus final output presentation confined to main. Dependency flow is one-way with no circular coupling. The round trip is implemented exactly to spec — assistant block echoed verbatim, one user message with tool_result/tool_use_id/content — as verified by the committed transcript .ololo/tmp/cc-n8s5ph15/req.2, and the final commit cleanly fixed the run_bash signature and message format from the earlier failing attempt (ValueError in .ololo/tmp/cc-5w1zvoc0/stderr). Deductions: extract_tool_calls/extract_text sprawl across ~5 alternate reply schemas (OpenAI/function_call/Anthropic/simple) that the harness contract never exercises, making tolerant parsing the largest part of the file and blurring the model-interface boundary; minor dead weight in the --self-test stub (unused lazy import) and committed .ololo/tmp run artifacts mixed into the source tree. test.sh's end-to-end scripted-model tests are a sensible, fitting choice over unit tests at this size.

Judged from the recorded run captures committed under .ololo/tmp/cc-* (each with exact stdout/stderr), agent.py, AGENTS.md and test.sh; no separate terminal recording or --help capture was delivered, but the harness captures carry the exact output of six real invocations, which is sufficient. CLARITY (9.0): stdout discipline is exactly what the spec demands. Success runs prove it: cc-k58wm5s6/stdout is exactly 'Ak58wm5s6' with 0-byte stderr; cc-5ipu2bds prints 'hello A5ipu2bds'; the multi-block case cc-9r21cmwe prints two lines in order ('first L9r21cmwe'/'second L9r21cmwe'), matching extract_text's newline join of text blocks. agent.py writes only the answer via sys.stdout.write (+ one newline); no banners, spinners or traces exist anywhere on stdout. Streaming is handled per spec: the final diff adds parse_model_output, which walks newline-delimited JSON objects, treats unparseable lines as noise, and returns the last type:'message' object while ignoring text_delta fragments — so the answer prints once, from the message. Pre-fix capture cc-pdq0z6x7 (5 calls, empty stdout, exit 1) vs post-fix cc-7k5h1o20 (1 call, stdout 'S17k5h1o20 S27k5h1o20', empty stderr) shows the delta-ignoring path working, and test.sh case 5 pins it. Deductions: a final message with no text falls back to dumping json.dumps(resp) to stdout, and MAX_ITERS exhaustion prints a 'done' fallback to stdout — both could pollute the compared channel in edge cases. ERRORS (8.5): the failure capture is a model of an honest failure — cc-pdq0z6x7/stderr is one specific line ('agent: model failed after 5 tries: bad json: Extra data: line 2 column 1 (char 43) out=…') naming what failed, the cause, and a truncated raw payload; stdout stays empty and exit is 1. Usage errors are distinct: exit 2 with 'agent: missing -p ' and 'agent: AGENT_MODEL_CMD is not set'. Tool failures are results fed back to the model, not crashes (test 2 asserts the tool result round-trips), and bad model output is retried with backoff before a clean stop. No stack traces on any foreseeable path. Minor: the error says what failed but not what to check next (e.g., verify AGENT_MODEL_CMD), and a model permanently down costs 5 retries before giving up. ERGONOMICS (8.0): flags match conventions (-C dir, --yes, -p prompt); AGENT_MODEL_CMD's stdin/stdout contract is documented in AGENTS.md along with usage, headless behavior and the test command, so a first run either works or says exactly what is missing. test.sh is a readable five-case suite covering direct answer, tool loop with conversation growth, retry-on-hiccup, alternate OpenAI schema, and stream handling. Weak spots: --help is a one-line usage string sent to stderr (exit 0) rather than real documentation; unknown flags are silently ignored instead of erroring, so a typo like --prompt just yields 'missing -p'; the --self-test stub prints 'selftest ok' from a lazy import — a loose end. There is no interactive mode (prompt/status line/keys), which is out of scope for this headless build. Overall: a lean, honest tool whose printed behavior matches the contract in the delivered captures; lose points for the stdout fallback dumps, silent flag handling, and a help text that explains less than it could.