Integrate founding explorations and bootstrap operational radar

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> Imported discovery draft; recipes are non-normative. Verify versions and use METHOD.md for selection.
# Benchmark atlas — Task Router
Version 0.1 · 13 September 2026
Pick five. Recipes at the bottom.
## Living instruments (preferred)
| ID | Benchmark | Best-used-for layers | Still discriminating? |
| --- | --- | --- | --- |
| HLE | Humanity’s Last Exam | know + reason (expert) | yes |
| FMath | FrontierMath / Erdős | reason (research math) | yes, tiny N |
| GPQA | GPQA Diamond | know + reason (grad science) | fading at the very top |
| SciCode | SciCode | reason + tool (scientific code) | yes |
| SWE-V | SWE-bench Verified | tool + plan (repo repair) | yes, some saturation at top |
| SWE-P | SWE-bench Pro | tool + plan (harder engineering) | yes |
| DeepSWE | DeepSWE | tool + plan (agent coding) | yes |
| FCode | Frontier Code | tool + plan (front of coding agents) | yes |
| Term4 | Terminal-Bench 4.0 | tool + plan (CLI / research ops) | yes (v4 reset) |
| OSW2 | OSWorld 2.0 | perceive + tool + plan (desktop) | yes, lots of headroom |
| ARC3 | ARC-AGI-3 | reason (interactive abstraction) | yes; **harness-sensitive** |
| GDPv | GDPval-AA v2 | know + reason (occupation work) | yes |
| GDPpdf | GDP.pdf | know + reason (long professional docs) | yes |
| Brief | AA-Briefcase | know + reason (knowledge work pack) | yes |
| AutoB | AutomationBench-AA | tool + plan (office agents) | yes |
| Omni | AA-Omniscience / SimpleQA | know + reliable (facts) | yes |
| Crit | CritPt | reliable (critique / catch errors) | yes |
| LCR | AA-LCR | reason (long-context) | yes |
| AAIX | AA Intelligence Index (current ver.) | composite | yes, version-locked |
| ECI | Epoch Capabilities Index | long-run general capability | yes, for history |
| LiveC | LiveCodeBench | tool (contest coding, contamination-aware) | yes |
| Browse | BrowseComp / web-research evals | tool + know (search) | use when task is open-web |
## Saturated / secondary (at most one of five)
MMLU-Pro, MATH-500, AIME (year-locked), HumanEval, IFEval, Arena Elo.
## Default five-benchmark recipes
| Task family | Five |
| --- | --- |
| Hard general question / research memo | HLE, GDPpdf, Brief, Omni, Crit |
| Graduate science explanation | GPQA, HLE, SciCode, Crit, Omni |
| Research mathematics | FMath, HLE, SciCode, LCR, Crit |
| Production software change | SWE-P, DeepSWE, Term4, LiveC, Crit |
| Greenfield coding / scripts | LiveC, SWE-V, Term4, Crit, Omni |
| Computer-use / “do this in the GUI” | OSW2, Term4, AutoB, ARC3, Crit |
| Office automation / agent workflow | AutoB, GDPv, Term4, OSW2, Brief |
| Long-document diligence | GDPpdf, LCR, Brief, Crit, Omni |
| Open-web investigation | Browse, Omni, Crit, Brief, HLE |
| Multimodal perception + act | OSW2, ARC3, AutoB, GDPv, Crit |
| Cheap classification / extraction | Omni, Crit, Brief, GDPv, AAIX |
| “What model should we buy?” meta | AAIX, GDPv, SWE-P, Term4, OSW2 |
## Changelog
- 2026-09-13: v0.1 atlas. Rebuild whenever a major eval saturates or an index rebases.

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# Capability Advisor — operational method
The normative method is [TaskModelEvaluationMethod](../TaskModelEvaluationMethod.md).
Use policy IDs `benchmark-selection-v0.1` and `model-ranking-v0.1`.
1. Record task, deliverable, acceptance criteria, risk class, constraints, tools,
budget and requester-accessible deployments. Score the six clarity components 0–1.
2. Map required capabilities and hard gates. Select five distinct benchmark versions
with task-specific weights summing to one; document relevance, redundancy,
weaknesses, provenance and dates. The atlas is only a discovery aid.
3. Preserve model, effort, harness, provider and deployment identity for results.
Treat missing results as missing. Label normalized benchmark scores as proxies.
4. Rank eligible profiles by comparative task fitness. Frontier maximizes fitness;
Topnotch includes fitness >= .90 of Frontier. Efficient minimizes expected total
task cost within Topnotch, using dated prices and explicit workload assumptions.
5. Evaluate Sufficient against the risk threshold using calibrated success evidence.
If missing, report `no_evidenced_sufficient_model`; Budget is then undetermined.
Do not derive retries by dividing by an uncalibrated benchmark score.
6. Explain confidence dimensions and evidence gaps. Estimate cost/runtime p50/p90
only where evidence supports quantiles; otherwise label a scenario range.
7. Compare optional decomposition with a monolithic baseline including coordination,
verification and failure costs. Record actual outcomes for later calibration.
Use [TEMPLATE](TEMPLATE.md). This is a manual workflow in v0.1, not an API promise.

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# Capability Advisor ticket
Status: draft / reviewed
Date and evidence cutoff:
Policy IDs: benchmark-selection-v0.1; model-ranking-v0.1
Task / deliverable / acceptance criteria:
Risk class and explicit sufficiency threshold:
Hard gates / tools / privacy / region / budget:
Clarity components (0–1): objective, context, constraints, acceptance, output, environment
Capability profile:
## Five measurements
| Benchmark + version | Observation ID / source / date | Weight | Relevance and validity | Gaps / redundancy |
| --- | --- | --- | --- | --- |
| 1 | | | | |
| 2 | | | | |
| 3 | | | | |
| 4 | | | | |
| 5 | | | | |
Weights sum to one. No composite index substituted for a measurement.
## Candidates and decision
| Profile + deployment + harness + effort | Eligibility | Fitness proxy | Calibrated success / evidence | Expected cost |
| --- | --- | --- | --- | --- |
Frontier:
Topnotch:
Efficient:
Sufficient: no_evidenced_sufficient_model until supported
Budget: undetermined until supported
Price observation IDs and dates; input/cache/output/reasoning/tool/retry/verifier assumptions:
Cost and runtime p50/p90 (or explicitly labeled scenario ranges):
Confidence by component and what would change the decision:
Evidence gaps:
Optional decomposition vs monolithic baseline:
Outcome: actual configuration, acceptance result, cost, tokens, runtime, retries, failure mode:

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# Worked example — evidence-limited routing
Task: produce a sourced technical diligence memo and migration plan for a coding-agent stack.
This is a manual workflow illustration, not a live model recommendation.
Missing context: current stack, task distribution, acceptable failure rate, region,
and access to candidate deployments. Acceptance: reviewed memo plus reproducible cost model.
Risk policy: important, provisional threshold .90.
Candidate instruments: SWE-bench Multilingual (repository work), Terminal-Bench
(shell work), BrowseComp (source discovery), GDPval (deliverables), BFCL (tool use).
Their exact versions, result dates, independence and requester harness match need
verification. No weights or model results are invented to fill the ticket.
Frontier / Topnotch / Efficient: undetermined pending eligible profile evidence.
Sufficient: `no_evidenced_sufficient_model`. Budget: undetermined.
Cost/runtime: unknown until prices and representative traces are observed.
Next: collect versioned results and deployment prices, run representative work samples,
then compare retrieval → analysis → independent verification against monolithic execution.
Record measured outcomes; do not assert an unsupported percentage saving.
The original Grok example, with named winners and assumed savings, is preserved in
the source ZIP and superseded by this evidence-limited example.