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Claude Haiku 5.5 (effort default (no --effort flag) · thinking on) on Plan the startup order of a self-hosted container stack (conditions, profiles, optional and disabled services, error precedence, cycles)

AClaude Haiku 5.5default · thinking on · Claude Code 2.1.299 (headless -p) · cloud · 2026-10-20 · by @bobsiopener

Trust 80%Fully autonomoussuccess · first try
Estimated cost
$0.01
Wall time
55s
Human step-ins
0
Outcome
Pass

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Summary

Exact prompt

# Plan the startup order of a self-hosted container stack Our home server runs a compose-style stack (`compose.json` is the JSON form of the compose file). `plan.py` should work out, without starting anything, in which **step** each service would start, and refuse broken stacks with a precise error. The draft ignores most rules. Rewrite `plan(compose, targets=None, profiles=())` in `plan.py` (Python 3 stdlib only), keeping `PlanError(code, detail)` with its `.code` and `.detail` attributes. ## Model 1. `compose["services"]` maps service names to dicts. `depends_on` is absent, a list of names, or a dict `{dep: options}` where options may be `{}`/`null` and may contain `condition` (default `service_started`) and `required` (default `true`). The list form means `service_started`, required. 2. A service is **disabled** if `deploy.replicas` is `0`. 3. **Active set.** If `targets` is `None`: start from every non-disabled service with no `profiles` (missing or empty) or with at least one profile in `profiles`. If `targets` is a list: start from exactly those (error `unknown_target`, detail = name, for the first target in list order that is not a service; then `disabled`, detail = name, for the first disabled target). Then add dependencies transitively: any dependency that exists and is not disabled is added **regardless of its profiles**. 4. **Dependency errors**, checked over active services in name order, and for each over its dependencies in name order; raise the first one found, detail = `(service, dependency)` as a tuple: - stage A: dependency not a service -> `missing_dependency`; dependency disabled -> `disabled_dependency`. Both only when the dependency is required; non-required missing/disabled dependencies are dropped silently and are not checked in stages B, C or later. All stage A checks run before any stage B check. - stage B: condition not one of `service_started`, `service_healthy`, `service_completed_successfully` -> `bad_condition`. All of stage B runs before stage C. - stage C: `service_healthy` on a dependency with no `healthcheck` or with `healthcheck.disable` true -> `no_healthcheck`; `service_completed_successfully` on a dependency whose `restart` is `always` or `unless-stopped` -> `never_completes`. 5. **Cycles** (checked after stage C): if the remaining dependency graph of active services has cycles, raise `cycle` with detail = sorted list of **every** service that is on some cycle (any member of a strongly connected group of 2+ services, or a service depending on itself). Services that merely depend on a cycle are not listed. 6. **Steps.** A service with no remaining dependencies starts at step 0. Otherwise its step is the maximum over its dependencies of: dependency's step + 1 for `service_started`, + 2 for `service_healthy` or `service_completed_successfully`. 7. **Result.** Return a list of waves: `waves[k]` is the sorted list of active services starting at step k, for k = 0 .. max step (steps nobody uses give `[]`). 8. **Scale.** A generated chain-and-fan stack with 3,000 services and dependency depth 2,000 must be planned in under 5 seconds on our shared test box (no `RecursionError`). On `compose.json` with defaults the answer is `[["db", "redis"], [], ["migrate"], [], ["app"], ["proxy"]]`. ## Scoring Hidden check groups (partial credit = fraction passed; all must pass): `basic_waves` (1, 6, 7), `profiles_and_targets` (3), `optional_and_disabled` (2, 3, 4A), `error_precedence` (4, exact code and detail; a detail sequence may be a tuple or a list), `conditions` (4B-C, 6), `cycles` (5, exact detail), `fixture_answer`, `randomized_agreement` (200 random small stacks: same waves, or same error code and detail), `scale` (8).

Staged error precedence with exact (service, dependency) details, profile pull-in, required:false dropping, condition-dependent step offsets, an exact cycle-member list (strongly connected components, not 'anything downstream') and a depth-2,000 stack that breaks naive recursion. Original benchmark task written for usecaserank.com (not based on a specific public post). Headless, offline run on a reproducible fixture. Each run's notes say how its cost was measured (estimates are marked).

Success criteria: 1. basic_waves 2. profiles_and_targets 3. optional_and_disabled 4. error_precedence 5. conditions 6. cycles 7. fixture_answer 8. randomized_agreement (200 stacks) 9. scale (3,000 services < 5 s)

Setup notes: Use Case Scout batch 8 case i04-compose-startup-plan (offline fixture). Prepared with batch8/prepare.sh; hidden key/tests kept outside the agent's work dir. Prompt = TASK.md verbatim. Scored with the scout's scorer: `python score.py WORKDIR KEYDIR`. Tools: Read/Write/Edit/Glob/Grep/Bash, web disabled. Single run, no retries. 1-min load average at scoring: 2.12. Claude Code's own reported cost for claude-haiku-5.5: $0.011563. Score: 9/9. Cost is an ESTIMATE: measured tokens x pricing.json list price (Claude Pro subscription, nothing billed); input_tokens include cache reads and writes. Single run.

Estimated cost List-price estimate; not actually billed.

Metrics

Estimated cost
$0.01
Wall time
55s
Human step-ins
0
Turns
5
Model usage
ModelInput tokOutput tokCost
AClaude Haiku 5.5anthropic/claude-haiku-5.5effort default (no --effort flag) · thinking on129,74012,321$0.01

Reproduce this run

  1. Use the use case prompt on the use case page.
  2. Same setup: Claude Haiku 5.5 (anthropic/claude-haiku-5.5, effort default (no --effort flag) · thinking on) via Claude Code 2.1.299 (headless -p), cloud.
  3. It counts as a success only if it meets every success criterion: 1. basic_waves 2. profiles_and_targets 3. optional_and_disabled 4. error_precedence 5. conditions 6. cycles 7. fixture_answer 8. randomized_agreement (200 stacks) 9. scale (3,000 services < 5 s)
  4. Log model, tokens, wall time, human step-ins and the evidence log, then submit it as a reproduction. A different model? Submit a head-to-head rerun.

How runs are scored: Methodology.

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  "result": "I rewrote `plan()` in `plan.py` to follow the spec, keeping `PlanError(code, detail)`. The fixture returns `[[\"db\", \"redis\"], [], [\"migrate\"], [], [\"app\"], [\"proxy\"]]`, and a 3,000-service chain of depth 2,000 plans in about 0.01 s with no recursion.\n\nI checked it with a scratch script in `/tmp/plan_tests/`, outside the work directory. It covers:\n- profiles and targets (`ops` profile pulls in `backup`, which lands in step 1)\n- `unknown_target` and `disabled` target errors\n- `missing_dependency` and `disabled_dependency` errors, plus the silent drop of non-required missing dependencies\n- `bad_condition`, `no_healthcheck`, and `never_completes`\n- `cycle` detail for a self-loop and a two-node cycle, with services that only depend on a cycle left out\n\nThe spec's hidden check groups aren't available here, and the randomized comparison needs a reference implementation I don't have. So the checks above are my own, not the grader's.\n\nI also added a small `__main__` block that prints the waves for a compose file path, which you can drop if you don't want it.\n\nJudgment calls where the spec was silent:\n- A `healthcheck` of `{}` counts as \"no healthcheck\", the same as a missing or null one.\n- `\"required\": null` or `\"condition\": null` fall back to the defaults.\n- The transitive dependency closure applies in both the `targets=None` and list-target modes.\n- An empty active set returns `[]`.\n\nThe directory isn't a git repo, so I didn't commit anything.",
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