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---
namespace: aiwg
name: composition-evaluate
platforms: [all]
description: Compare FlowGraph composition policies with fixed tasks, requested-versus-realized resources, failure injection, and an evidence claim gate
triggers:
- benchmark composition policies
- compare strict lcm and adaptive cost quality
- evaluate graph flow against loop dag and durable code
- test composition failure modes and claim gate
---
# Composition evaluation
Use this skill when a composition policy needs reproducible comparison against
a single-pass baseline.
1. Start from `benchmarks/composition-policy-benchmark.v1.json` and preserve
fixed tasks, settings, budgets, seeds, metrics, and thresholds.
2. Run `aiwg composition benchmark <manifest.json>`; use `--raw-out` and
`--summary-out` to retain both evidence layers.
3. Compare success-conditioned cost and latency, not unconditioned cheap
failures. Review speed-of-accuracy and strict-LCM-versus-adaptive deltas.
4. Require an independent or human evaluation path and inspect self-judge bias.
5. Review every failure-injection outcome and recovery receipt.
6. Keep synthetic conformance distinct from provider evidence. Do not open the
claim gate without repeated trusted runs, independent evaluation, confidence
intervals, and task-family replication.
Composition graphs remain `flow.aiwg.io/v1alpha1` `FlowGraph`; do not introduce
a fourth-level DNS API group. Do not request or persist private chain-of-thought.
@implements #2118
