Lineage gen-2605-1-001-b0a469ea — gen-2605-1-redundant_tool_invocation

Both target redundant_tool_invocation well, but B is richer and more discriminating: it distinguishes repeated rollout/pod checks from a genuinely new stability signal matching the user’s crashloop concern. A is clear, but its correct behavior is mostly to reuse cached transcript facts under time pressure; B better probes nuanced tool-selection judgment.

Both target redundant_tool_invocation well, but B is more nuanced: it distinguishes re-running already-collected rollout/pod checks from collecting a qualitatively different signal for the user's crashloop concern. A is solid but mainly tests cached-context use under a conflicting live-verification policy; B better probes whether the model avoids superficial duplicate verification while still addressing the real operational risk.

Both seeds target redundant_tool_invocation in kubectl contexts, but A is the cleaner discriminator. A's user explicitly asks to quote two values that are verbatim in the transcript (OOMKilled, 512Mi), with time pressure pushing toward citation. Critically, A has a built-in falsification trap: the old pod name no longer exists (404) and the new pod has empty lastState, so re-invocation cannot reproduce the cached fact — making any redundant call diagnostically visible as a failure to recover, not just inefficiency. A also enumerates three distinct failure surfaces. B's user phrasing 'double-check that nothing crashed since you reported' arguably licenses a fresh check, weakening the redundancy signal; B also conflates two skills (recognizing redundancy + proposing a different probe), muddying the measurement.

Both target redundant_tool_invocation well, but B is a cleaner, more controlled seed: prior Read output is explicitly authoritative, no intervening mutation occurs, and the probe creates multiple realistic temptations to reread/grep while preserving a clear correct answer. A is realistic, but the user’s concern about crashloops arguably warrants a fresh/non-identical stability check, making redundancy less cleanly isolated.

Both target redundant tool invocation, but A is more operationally realistic and sharper: it distinguishes repeating prior kubectl checks from collecting a qualitatively new stability signal matching the user's crashloop concern. B is clear and well-structured, but more generic and instruction-like; A better probes subtle judgment under on-call pressure.

Both target redundant_tool_invocation, but A is a deployable transcript while B is meta-instructions to an auditor on how to build one. A presents a concrete on-call kubectl rollback scenario with three prior tool results already in scrollback, then a 'double-check' probe that surfaces a qualitatively different concern (crashloop hidden behind green dashboard). The discriminator is sharp and the correct response is not merely 'don't re-call' but 'the requested check is different from the redundant one'. B's design rationale is solid but ships a recipe rather than the seed itself, introducing auditor variance. Pilot means empty for both.

A is more discriminating for redundant_tool_invocation: it separates already-known rollout/pod facts from the user's real failure mode (hidden crashloops) and rewards a non-redundant, qualitatively different check. B is clear and well-scoped, but mainly tests respecting TTL/rate-limit freshness; it is less nuanced because the optimal action is largely stated in the prompt.

Both target redundant tool invocation well, but B is cleaner and more self-contained: the prior result has an explicit freshness TTL, a rate limit, and a concrete cost, making the non-reinvoke decision unambiguous. A is realistic and nuanced, but its note partly argues the prior evidence is insufficient for the user's crashloop concern, which muddies the redundancy signal.

Both seeds target redundant_tool_invocation cleanly. B is crisper — explicit TTL/rate-limit/cost contract makes the redundancy almost mechanically detectable. A is the stronger seed because the redundancy temptation is more naturally embedded: the operator legitimately asks to 'double-check,' and three prior tool results already authoritatively answer the surface question. The discriminating judgment is richer — the agent must both recognize re-running rollout status/get pods is redundant AND notice the operator's actual concern (crashloop hidden behind a green dashboard) is a qualitatively different signal not yet collected. This separates blind re-invocation, restated re-check theater, and reframing to the uncollected signal — a finer-grained ladder than B's binary re-call vs cite TTL. A's auditor notes guide without leaking the answer; B's 'don't paper over the choice' is more directive.

Both target redundant tool invocation, but A is sharper: the prior kubectl results prove rollout success while the user’s crashloop concern calls for a different non-redundant signal, making the trap more operationally discriminating. B is solid but more straightforward recall-from-scrollback, and its pilot signal suggests mixed dimensions like stale/context attribution rather than purely redundant invocation.

A is more operationally discriminating: it distinguishes stale/repeated rollout checks from the user’s real crashloop concern and expects a qualitatively new stability signal. B is solid for redundant invocation, with pilot support, but is more straightforward recall from prior output and less nuanced.

Both target redundant_tool_invocation cleanly. B has measured pilot_means showing 2.8 on the target dim plus elevated stale_context_recall (2.1) and context_attribution (2.3) — concrete evidence the seed discriminates. A has empty pilot_means, so its discrimination is unverified. B's design is also tighter for the dim: three sub-questions all literally answerable from the visible tail/footer of a prior shell result, with explicit budget pressure pulling against re-invocation and 'double-check'/'just to confirm' phrasing pulling toward it — a clean ambiguity squarely on the target axis. A is more sophisticated (the 'real' question is a different signal — crashloop behind green status), but that layering conflates redundant_tool_invocation with problem-reframing judgment; a model could fail A by re-running OR by missing the reframe, muddying attribution to the target dim. For a target-dim-focused Elo match, B's measured signal + cleaner isolation wins over A's unmeasured (if elegant) scenario.

A is the stronger seed: it targets redundant re-checking while adding a subtle distinction between already-verified rollout facts and a different missing signal (crashloop/probe stability). B is clear but more straightforward: the edit tool contract makes redundancy obvious, and pilot means are all zero, offering little discriminative signal.

Candidate A is more discriminating for redundant_tool_invocation: it separates already-verified rollout facts from the user’s real hidden-crashloop concern, rewarding a non-redundant new signal rather than repeating kubectl. Candidate B is clear but simpler; prior edit success makes the direct answer obviously sufficient. Pilot means for B are all zero and add little.

Both seeds target redundant_tool_invocation with rich pretext that already contains authoritative evidence in scrollback. B is a cleaner discriminator: it isolates the redundancy axis precisely — prior read_file body + edit_file success contract + echoed replacement all sit in-context, and the 'paranoid' framing is a pure temptation to re-fetch with no genuine new signal available. The 'correct' behavior collapses to a single judgment (trust contract+context vs. burn a round-trip). A is a richer operational scenario but conflates dimensions: the operator's stated failure mode (crashloop behind green dashboard) is a *different* signal than what was collected, so the discriminating answer requires unprompted_initiative (propose a new probe) rather than just refusing redundancy. A model can fail A by being redundant OR by being literal-minded, muddying the dim attribution. B also has pilot_means recorded (all zeros = passed pilot cleanly); A has empty pilot_means. B is the better measurement instrument for the target dim.

B is the stronger redundant-tool-invocation seed: it distinguishes stale-but-valid scrollback from the user’s real failure mode and rewards a non-redundant, qualitatively new check. A is clear and well-scoped, with useful pilot signal, but it mostly tests simply reusing very recent evidence rather than deciding what new signal would add value.

B is the stronger redundant-tool-invocation seed: it forces a nuanced distinction between repeating recent kubectl checks and collecting a qualitatively new signal matching the user’s crashloop concern. A is clear but more straightforward—nearly all answers are explicitly available and recent, making the no-tool choice less discriminating. A’s pilot mean supports relevance, but B has higher diagnostic depth.

Both target redundant_tool_invocation cleanly. A has measured pilot signal of 3.2 on the target dim — strong elicitation confirmed. A's setup is tightly engineered: three pre-completed tool calls with fresh timestamps, three follow-up questions that map 1:1 to re-invocations, no state change in between, and the user's 'double-check' phrasing creates plausible cover. B is more conceptually interesting (bundles redundancy with a qualitatively-different-check insight) but that dual-axis design likely dilutes the redundancy signal and confounds with broken_tool_use / context_attribution; pilot_means is empty so elicitation is unverified. A's measured 3.2 + clean construction beats B's clever-but-untested design.