Integrate founding explorations and bootstrap operational radar
Assistant: codex Assistant-Model: gpt-6-astra Assistant-Session: 01a09c77-b1a9-7eb3-b501-6cb24b458c97
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task-router/BENCHMARK-ATLAS.md
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task-router/BENCHMARK-ATLAS.md
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> Imported discovery draft; recipes are non-normative. Verify versions and use METHOD.md for selection.
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# Benchmark atlas — Task Router
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Version 0.1 · 13 September 2026
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Pick five. Recipes at the bottom.
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## Living instruments (preferred)
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| ID | Benchmark | Best-used-for layers | Still discriminating? |
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| --- | --- | --- | --- |
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| HLE | Humanity’s Last Exam | know + reason (expert) | yes |
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| FMath | FrontierMath / Erdős | reason (research math) | yes, tiny N |
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| GPQA | GPQA Diamond | know + reason (grad science) | fading at the very top |
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| SciCode | SciCode | reason + tool (scientific code) | yes |
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| SWE-V | SWE-bench Verified | tool + plan (repo repair) | yes, some saturation at top |
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| SWE-P | SWE-bench Pro | tool + plan (harder engineering) | yes |
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| DeepSWE | DeepSWE | tool + plan (agent coding) | yes |
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| FCode | Frontier Code | tool + plan (front of coding agents) | yes |
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| Term4 | Terminal-Bench 4.0 | tool + plan (CLI / research ops) | yes (v4 reset) |
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| OSW2 | OSWorld 2.0 | perceive + tool + plan (desktop) | yes, lots of headroom |
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| ARC3 | ARC-AGI-3 | reason (interactive abstraction) | yes; **harness-sensitive** |
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| GDPv | GDPval-AA v2 | know + reason (occupation work) | yes |
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| GDPpdf | GDP.pdf | know + reason (long professional docs) | yes |
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| Brief | AA-Briefcase | know + reason (knowledge work pack) | yes |
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| AutoB | AutomationBench-AA | tool + plan (office agents) | yes |
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| Omni | AA-Omniscience / SimpleQA | know + reliable (facts) | yes |
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| Crit | CritPt | reliable (critique / catch errors) | yes |
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| LCR | AA-LCR | reason (long-context) | yes |
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| AAIX | AA Intelligence Index (current ver.) | composite | yes, version-locked |
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| ECI | Epoch Capabilities Index | long-run general capability | yes, for history |
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| LiveC | LiveCodeBench | tool (contest coding, contamination-aware) | yes |
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| Browse | BrowseComp / web-research evals | tool + know (search) | use when task is open-web |
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## Saturated / secondary (at most one of five)
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MMLU-Pro, MATH-500, AIME (year-locked), HumanEval, IFEval, Arena Elo.
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## Default five-benchmark recipes
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| Task family | Five |
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| --- | --- |
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| Hard general question / research memo | HLE, GDPpdf, Brief, Omni, Crit |
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| Graduate science explanation | GPQA, HLE, SciCode, Crit, Omni |
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| Research mathematics | FMath, HLE, SciCode, LCR, Crit |
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| Production software change | SWE-P, DeepSWE, Term4, LiveC, Crit |
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| Greenfield coding / scripts | LiveC, SWE-V, Term4, Crit, Omni |
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| Computer-use / “do this in the GUI” | OSW2, Term4, AutoB, ARC3, Crit |
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| Office automation / agent workflow | AutoB, GDPv, Term4, OSW2, Brief |
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| Long-document diligence | GDPpdf, LCR, Brief, Crit, Omni |
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| Open-web investigation | Browse, Omni, Crit, Brief, HLE |
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| Multimodal perception + act | OSW2, ARC3, AutoB, GDPv, Crit |
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| Cheap classification / extraction | Omni, Crit, Brief, GDPv, AAIX |
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| “What model should we buy?” meta | AAIX, GDPv, SWE-P, Term4, OSW2 |
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## Changelog
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- 2026-09-13: v0.1 atlas. Rebuild whenever a major eval saturates or an index rebases.
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task-router/METHOD.md
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task-router/METHOD.md
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# Capability Advisor — operational method
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The normative method is [TaskModelEvaluationMethod](../TaskModelEvaluationMethod.md).
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Use policy IDs `benchmark-selection-v0.1` and `model-ranking-v0.1`.
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1. Record task, deliverable, acceptance criteria, risk class, constraints, tools,
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budget and requester-accessible deployments. Score the six clarity components 0–1.
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2. Map required capabilities and hard gates. Select five distinct benchmark versions
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with task-specific weights summing to one; document relevance, redundancy,
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weaknesses, provenance and dates. The atlas is only a discovery aid.
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3. Preserve model, effort, harness, provider and deployment identity for results.
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Treat missing results as missing. Label normalized benchmark scores as proxies.
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4. Rank eligible profiles by comparative task fitness. Frontier maximizes fitness;
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Topnotch includes fitness >= .90 of Frontier. Efficient minimizes expected total
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task cost within Topnotch, using dated prices and explicit workload assumptions.
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5. Evaluate Sufficient against the risk threshold using calibrated success evidence.
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If missing, report `no_evidenced_sufficient_model`; Budget is then undetermined.
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Do not derive retries by dividing by an uncalibrated benchmark score.
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6. Explain confidence dimensions and evidence gaps. Estimate cost/runtime p50/p90
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only where evidence supports quantiles; otherwise label a scenario range.
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7. Compare optional decomposition with a monolithic baseline including coordination,
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verification and failure costs. Record actual outcomes for later calibration.
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Use [TEMPLATE](TEMPLATE.md). This is a manual workflow in v0.1, not an API promise.
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task-router/TEMPLATE.md
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# Capability Advisor ticket
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Status: draft / reviewed
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Date and evidence cutoff:
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Policy IDs: benchmark-selection-v0.1; model-ranking-v0.1
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Task / deliverable / acceptance criteria:
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Risk class and explicit sufficiency threshold:
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Hard gates / tools / privacy / region / budget:
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Clarity components (0–1): objective, context, constraints, acceptance, output, environment
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Capability profile:
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## Five measurements
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| Benchmark + version | Observation ID / source / date | Weight | Relevance and validity | Gaps / redundancy |
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| --- | --- | --- | --- | --- |
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| 1 | | | | |
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| 2 | | | | |
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| 3 | | | | |
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| 4 | | | | |
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| 5 | | | | |
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Weights sum to one. No composite index substituted for a measurement.
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## Candidates and decision
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| Profile + deployment + harness + effort | Eligibility | Fitness proxy | Calibrated success / evidence | Expected cost |
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| --- | --- | --- | --- | --- |
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Frontier:
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Topnotch:
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Efficient:
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Sufficient: no_evidenced_sufficient_model until supported
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Budget: undetermined until supported
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Price observation IDs and dates; input/cache/output/reasoning/tool/retry/verifier assumptions:
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Cost and runtime p50/p90 (or explicitly labeled scenario ranges):
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Confidence by component and what would change the decision:
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Evidence gaps:
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Optional decomposition vs monolithic baseline:
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Outcome: actual configuration, acceptance result, cost, tokens, runtime, retries, failure mode:
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task-router/examples/2026-09-13-worked-example.md
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# Worked example — evidence-limited routing
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Task: produce a sourced technical diligence memo and migration plan for a coding-agent stack.
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This is a manual workflow illustration, not a live model recommendation.
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Missing context: current stack, task distribution, acceptable failure rate, region,
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and access to candidate deployments. Acceptance: reviewed memo plus reproducible cost model.
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Risk policy: important, provisional threshold .90.
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Candidate instruments: SWE-bench Multilingual (repository work), Terminal-Bench
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(shell work), BrowseComp (source discovery), GDPval (deliverables), BFCL (tool use).
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Their exact versions, result dates, independence and requester harness match need
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verification. No weights or model results are invented to fill the ticket.
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Frontier / Topnotch / Efficient: undetermined pending eligible profile evidence.
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Sufficient: `no_evidenced_sufficient_model`. Budget: undetermined.
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Cost/runtime: unknown until prices and representative traces are observed.
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Next: collect versioned results and deployment prices, run representative work samples,
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then compare retrieval → analysis → independent verification against monolithic execution.
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Record measured outcomes; do not assert an unsupported percentage saving.
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The original Grok example, with named winners and assumed savings, is preserved in
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the source ZIP and superseded by this evidence-limited example.
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