XHMQIM

Nothing has moved since my last look at this same commit (ca62fd4), so my rating holds at 3.5. The faults I charged before are all still standing, and the player had this task's own commit as the natural place to fix them.

1. Change discipline — still a false story. get_last_commit_diff at ca62fd4 shows the entire task commit is .ololo/tmp/cc-* debris (model.sh, req.N captures, stderr 'ERROR: max turns (3) reached', the stdout receipt, session JSONs). agent.py (40,334 B), AGENTS.md and test.sh are byte-identical to the previous task commit — the --max-turns cap, JSON receipt, usage summation and session_id all predate the commit that claims them. Worse, the diff confirms debris from earlier tasks' testing (cc-47z625bs bash-fails, cc-7rlihago two providers, cc-9a2f74mh five turns, cc-txbvew7z flaky retry) was also dumped wholesale into this one commit, so every 'feat(...)' message misdescribes what its commit contains.

2. Decisions written down — still the biggest hole. AGENTS.md is unchanged at 480 bytes and records none of the decisions this task exists to make: the receipt schema {result, session_id, turns, usage}, that turns counts call_model invocations and the call past the cap is refused before it is made ('self.turns += 1; if self.turns > self.max_turns: raise ModelError'), that usage sums every reply and is rolled up from subagents in task(), the ERROR:-prefix-to-stderr convention, the 3-attempt/0.3s retry, the undocumented max_turns=50 default, and that session_id is uuid4().hex[:12]. A successor gets all of this only by reading agent.py. The code is correct — I verified cap-before-call, the per-reply accumulation, and the child→parent roll-up — but correctness in code without a word of why or what the wire contract is caps this criterion at 5 by my own standing rule.

3. Tooling enforces nothing for this contract. test.sh still checks one scripted single-call run ('ok: loop answers'); it exercises neither --max-turns, --output-format json, the usage sums nor session_id. No formatter, linter or type checker exists.

4. Hygiene. Still no .gitignore; ~16 run directories with the author's absolute machine paths (/private/tmp/claude-502/...) are committed, including .ololo/settings.json ('allow *') run config.

What keeps this at 3.5 rather than lower, credited before and not re-charged: the features genuinely work (the captured runs in the debris double as evidence — exit=1 with the ERROR line at the cap, and the exact receipt '{"result': 'doneqds9pfyg', 'session_id': '333676632bb8', 'turns': 2, 'usage': {'input_tokens': 2500, 'output_tokens': 90}}'); the stdlib-only, zero-dependency trade remains deliberate and declared; AGENTS.md's three original decisions and the working test.sh command are real.

To move up, the player needs exactly two things: a few paragraphs in AGENTS.md (or a design note) stating the receipt schema, turns/usage accounting, subagent roll-up, ERROR: convention and retry/default semantics; and honest commits going forward — a task commit should carry that task's code and only that task's debris, with .gitignore keeping .ololo/tmp out of history.

Governance-wise this is a thin but honest repo with a big hole exactly where this task's decisions should live.

What's written down: AGENTS.md (480 bytes) records the project's core stance — 'A plain Python 3 (stdlib only) coding agent: the model is a pluggable command (AGENT_MODEL_CMD)' — plus two real commands ('agent: python3 agent.py', 'test: sh test.sh') and a one-paragraph layout. That is a legitimate crisp README for the earlier tasks. Reproducibility is fine: stdlib-only Python, zero third-party dependencies (the right trade at this scale), and the declared test command matches a real, working test.sh. Commit discipline is decent: one commit per task (8 total), each 'feat(): ', no wip spam.

What a successor must guess: this task's load-bearing choices are all silent. The provider registry format, the '/' spec syntax, the precedence chain (AGENT_MODEL_CMD > --model > settings 'model'), and the error-on-undeclared-provider policy exist only in select_model()'s ~15 lines and a one-line docstring; nothing in AGENTS.md or any note explains why or how. The cap rule applies with force here.

The decisive defect: the task explicitly required wiring at least one HTTP provider ('the review panel reads for it'), and the code refuses instead — provider_cmd() raises ModelError("provider type %r is not wired in this reference") for anything but 'command'. There is no Anthropic/OpenAI path, no decision note explaining the refusal, and urllib (stdlib, free) sat right there. That is neither a documented trade nor an implementation.

Test coverage did not grow with the work: test.sh is still the original single smoke test; provider selection, --model override, and the exit-2 error path are exercised only by external check runs whose fixtures — including committed machine-specific paths like /private/tmp/claude-502/... under .ololo/tmp/ — get dumped into every commit as inert artifacts. The repo is steadily polluted with scratch state (a dozen cc-* directories, session logs, absolute host paths) that no doc explains.

Net: a clean stdlib skeleton with honest commits, but the task's central decision (providers/models) is undocumented, untested in-repo, and the HTTP-provider requirement was dropped rather than decided against.

Contract fully proven by three committed probe captures. cc-7hzdfx2p: stdout is exactly 'A7hzdfx2p\n' (10 bytes), stderr empty, model called once (calls=1). cc-nynuw1n6: two text blocks print as two lines in order, byte-count 33 matches, nothing else on stdout. cc-vqjg5et6: the model streams two text_delta fragments first; stdout is still exactly the final message 'S1vqjg5et6 S2vqjg5et6\n' — deltas correctly change nothing. The req.1 files show the harness sends a proper request (system context incl. inherited AGENTS.md, full tool schema), and every stderr is 0 bytes: no banner, no greeting, no spinner, no tool trace leaks headless. Source confirms the discipline: main() ends in a single print(answer); delta events are a no-op callback in headless mode; session save and MCP failures stay off stdout (MCP warnings go to stderr). clarity 9.5: this is the rare submission whose stdout discipline is proven, not promised. errors 7.0: design is right — ModelError prints 'ERROR: ' to stderr with honest exit codes (1 for model failure after 3 retries, 2 for no model configured, and the no-model message names the exact fix: 'set AGENT_MODEL_CMD, or providers + model in .agent/settings.json'); unknown provider lists the declared providers; tool failures become is_error results with useful text ('old_string found 2 times in X; give a longer anchor'), and bash timeouts kill the process group and return partial output. But no failing run was captured for review, and code shows narrow uncaught paths — an invalid model-supplied regex in grep() would crash with a traceback instead of a tool result, and a hook subprocess timeout is unhandled — so the 'failed tool is a result' rule is not airtight. ergonomics 7.5: AGENTS.md is crisp, test.sh is a one-command smoke test through a scripted model, sessions auto-save with --resume/--continue, flags follow conventions (-C/--yes/-p/--model/--output-format/--max-turns/--acp), and the first run without a model fails with an exact, actionable message. The real ding: argparse flags carry no help strings, so --help is a bare usage skeleton, not documentation. No .ololo/-done.md completion note was present. TUI ergonomics (status line, /help, Esc interrupt, y/n prompts) look sensible in code but no interactive recording was delivered, so it is not scored on evidence. Overall: a quiet, honest tool that nails the one-prompt-one-answer contract; the experience would rate higher once its error paths are demonstrated and its --help can teach a new user without the README.

Judged from the tool's own run artifacts saved in the repo (.ololo/tmp/cc-* run records: stdout/stderr/calls/req.N) and the harness code that produced them.

What the user experiences on this rung, from delivered output:

1. Flaky model that recovers (probe cc-pwqurekr): model.sh fails attempt 1 with exit 1, prints junk ('this is not json at all') on attempt 2, answers on attempt 3. calls file = 3, stderr is empty (0 bytes), and the saved session shows the final answer 'okpwqurekr' delivered cleanly. The agent carried on as if nothing happened — exactly the contract. Verified by the prior probe result: exit=0, answer=okpwqurekr, calls=3.

2. Model fails three times (probe cc-68xn1hrb): calls=3, stdout is empty, stderr is exactly one line — 'ERROR: model failed (exit 1)'. Prompt failure (prior probe measured ~1s total, with 0.3s between attempts in agent.py call_model), no traceback, exit code truthfully non-zero. No infinite retry, no minute-long waits.

3. Misconfiguration (probe cc-txbvew7z): 'ERROR: unknown provider 'ghost' (declared: a)' on stderr, stdout empty — names the bad input and lists what is declared. agent.py's select_model also gives an actionable message when nothing is configured ('set AGENT_MODEL_CMD, or providers + model in .agent/settings.json').

Clarity (9.0): stdout carries only the result — in the failing run it is completely empty; the single ERROR line goes to stderr. No banners, spinners, or retry chatter pollute headless output; test.sh's contract (out == 'pong') holds. Colour/layout not used, so nothing decorative to mislead. The only clarity gap: retries are entirely invisible — a human watching a slow model cannot tell attempt 2 from a hang (silent 0.3s sleeps, no 'retrying 2/3' on stderr).

Errors (8.5): the flaky-model path is the strongest part — a failed model is a retryable condition, not a crash; after three failures it stops promptly with a one-line stderr verdict and truthful exit code (cc-68xn1hrb). Deductions: (a) when the model exits 0 but never sends a message, the error reads 'model failed (exit 0)' — the exit code in the message contradicts the actual cause (missing message); it would have surfaced had attempt 3 also printed junk in cc-pwqurekr; (b) the final error never says 'after 3 attempts', so the user can't tell retries happened; (c) non-JSON model output is silently skipped — a user debugging their model.sh gets no hint of what the model actually printed.

Ergonomics (8.3): a first run with a flaky model either answers silently or fails within a second with an unambiguous line; sane defaults (3 attempts, sub-second backoff) need no configuration; the TUI surfaces the same 'ERROR: …' line in its transcript rather than crashing the curses loop. One latent wart: deltas already streamed during a failed attempt are re-emitted on retry, which in the TUI can duplicate ghost partial text (headless stdout is unaffected since only the final answer is printed).

Overall: a quiet, honest harness that fails fast and legibly and recovers invisibly; the residual cost is that 'invisibly' also means you learn nothing about the retries unless they all fail.

Behavior verified correct: req.2 in .ololo/tmp/cc-47z625bs shows the failing command's tool_result as raw 'OUT47z625bs\nERR47z625bs\nexit code: 3' with is_error:true and the loop continuing to a second model turn; the cc-ql909u00 scenario confirms commands run in the -C workdir. The implementation (agent.py Runner.bash, commit 1f0d1a4) uses the right mechanism — one pipe with stderr=subprocess.STDOUT for true write-order interleaving — and funnels failures through ToolError so run_tool reports them to the model without stopping the loop. Code is clean and appropriately plain: short focused functions, clear section banners, terse but consistent naming; product-code duplication is negligible (the near-identical model.sh scripts under .ololo/tmp are campaign fixtures, not the player's product). Deductions for maintainability defects sitting exactly on this task's boundary: (1) the exit-code branch appends 'exit code: ' without ensuring it starts on its own line, so output lacking a trailing newline would corrupt the last line — the timeout branch adds '\n', the exit branch doesn't (inconsistent, and the spec says 'a line'); (2) strict text decoding on the pipe means non-UTF-8 stdout raises UnicodeDecodeError that run_tool's 'except ToolError' does not catch, crashing the loop instead of telling the model; (3) the 120000 ms default timeout is a magic value repeated twice in one function. Pre-existing warts (always-true 'if "tools" in caps or True' in McpServer.start; ~100-line TUI main) are outside this task's scope. No duplication/lint metrics were provided; assessed by direct reading. Cleanliness 8.0, maintainability 7.5.

Model resolution is well-placed and centralized: Harness.select_model implements the exact precedence the task asks for (--model > AGENT_MODEL_CMD > settings default), rejects unknown providers with a helpful message listing declared ones ('unknown provider 'ghost' (declared: a)', artifact cc-txbvew7z), and is reused by the TUI /model command — the three command-provider checks demonstrably pass (cc-7rlihago shows --model routing to provider b with the model name carried in the request). The single-file layout is proportionate for a stdlib-only agent and is cleanly sectioned (settings/context/tools/permissions/hooks/MCP/harness/TUI/ACP), with genuine decoupling of presentation from the harness via events/ask callbacks. But the task's central architectural deliverable — an extensible provider seam with an HTTP implementation behind the same interface — is not realized: provider_cmd() hardcodes type 'command' and raises ModelError('provider type %r is not wired in this reference') for anything else (agent.py, harness section), and call_model() is fused with the sh transport (Popen sh -c, line-JSON text_delta/message parsing, retry loop, usage accounting all inline). There is no interface a second provider could slot into; adding HTTP would mean editing the harness interior, and no HTTP code exists (stdlib-only imports, no HTTP provider type anywhere) — consistent with the 10-point check coming back empty. Boundaries are otherwise reasonable (Harness/Runner/Mcp/AcpServer), with minor reach-across coupling: Runner reads harness internals (h.fs, h.acp_request, h.interrupted), the TUI reaches into h.runner.current to kill subprocesses, and subagents clone provider state by direct field copy. AGENTS.md still documents only AGENT_MODEL_CMD and omits the new providers/settings mechanism — small doc-code drift. Committed .ololo/tmp check artifacts bury the three real source files, though that appears to be campaign snapshot behavior. Verdict: solid, legible structure for its scale, but the one boundary this task was designed to create — providers behind a replaceable interface including an HTTP implementation — is missing.

The commit adds no tests for the rung's contract: test.sh is unchanged from the previous task and still asserts only the happy path (scripted model answers 'pong'); the diff for 484372db touches only .ololo/tmp probe transcripts. The retry/termination behavior was verified manually (cc-pwqurekr: exit-1 then junk then success with calls=3; cc-68xn1hrb: three failures ending in 'ERROR: model failed (exit 1)' on stderr) — and the prior-task results confirm it works — but none of it is captured as a runnable test. There is no test for: recovery after a failed attempt, the exactly-three-attempt ceiling, prompt terminal ERROR on stderr + non-zero exit after three failures, or retry on malformed replies. A regression to range(2)/range(30) or a minute-long backoff would pass the committed suite untouched. No dishonesty (nothing skipped or hard-coded), and the one smoke test has a real assertion, hence not zero. To fix: add sh test cases driving model.sh variants (fail-then-recover; always-fail) asserting stdout answer, call count, exit code, stderr line, and elapsed time; a compact retry-loop unit test would also do.

The per-turn loop has the right cost shape for a protocol that mandates carrying the whole conversation. In run_loop, history accumulation is append-only: each turn does self.messages.append({'role': 'assistant', ...}) then one {'role': 'user', content: results} — O(1) amortized per turn, no rebuild of prior turns, and the captured req.1..req.6 transcripts confirm strictly linear wire growth (+254 bytes/turn) with each assistant tool_use immediately followed by its tool_result in order (sequence 1 1 2 2 3 3 4 4 5 5, results=5). The O(history)-per-call json.dumps in call_model and the O(T²) cumulative bytes across calls are the protocol's own cost, not an implementation defect. I/O is batched: the request body is written with a single p.stdin.write(req) and model output is consumed via buffered line iteration, not per-byte reads. Expensive context assembly (build_system, instruction_files, skills/agents scans, git branch probe) runs once in init rather than per turn; only the trivial self.mcp.tools() re-enumeration happens per call. Memory discipline holds: sessions flush to disk once per submit (save()), and maybe_compact provides the eviction valve for unbounded history growth, so the in-memory conversation is not a leak wearing a hat. Concurrency is not part of this task's load shape — one client, one session, tools sequential by protocol semantics — and nothing holds a global lock across tool I/O in this path. Deductions: (1) no performance measurement anywhere — no timing harness, no recorded before/after; the 6 captured request sizes are the only quantitative observation, and they happen to demonstrate linear scaling rather than being a deliberate benchmark; (2) outside the graded path, the grep tool slurps each whole file (open(f).read().split()) instead of streaming lines, and read_instructions does the same — bounded by file size today but the operation to watch if those tools meet large inputs. The graded loop itself has no pointable defect: the straightforward implementation matches the job, and the transcript evidence shows the cost curve behaving exactly as the protocol requires.

Single-file architecture (agent.py ~40KB, ~700 lines) that is nonetheless well-banded: settings, context assembly, tools, permissions, hooks, MCP client, harness, TUI, ACP each get a labeled section (AGENTS.md honestly documents this layout). Component boundaries exist where they matter: Runner owns tool execution, Harness owns the model loop and state (run_loop appends the assistant reply, runs tools, appends one user message of tool_result blocks keyed by tool_use_id — exactly the round-trip contract, verified against captured req.2 in commit dcf2ed1), Mcp/McpServer encapsulate the JSON-RPC client, AcpServer and tui() are front-ends wired through callbacks (h.events, h.ask) rather than hard references — a decent one-way dependency shape for a stdlib-only harness. Proportionality is defensible: the docstring declares it a deliberately plain reference implementation, and for this campaign's scope one organized file is not under- or over-structured. What holds it back from 8+: Harness is a god object (provider resolution, model transport with retry, compaction, tool dispatch, permission checks, hooks, prompt expansion, session persistence all on one class), expand_prompt fuses slash-command expansion, @-file reads, MCP resource fetches and hook output into one function, and Runner↔Harness (runner.h / harness.runner) plus Harness↔AcpServer (h.fs, h.acp_request) form circular knowledge; run_tool interleaves permission verdicts, hook gating and execution in one path. The tool round trip itself is implemented cleanly and testably at Harness.run_loop, but pieces are not individually replaceable or unit-testable without the whole file. A probe was unnecessary — the structure is fully legible from files and AGENTS.md.