Agent-safe evaluation-artifact profile

Offline policy-evaluation reports are large and easy to misread. An agent that sees only a headline score such as V_hat can draw a confident, wrong conclusion. This profile compiles an evaluation artifact into phase-aware, agent-safe context that foregrounds support health, uncertainty, and caveats — and only then the headline estimate.

TL;DR

What	Where
The script	examples/architectures/eval_artifact_profile/main.py
The fixtures	examples/architectures/eval_artifact_profile/fixtures/
Captured output	examples/architectures/eval_artifact_profile/OUTPUT.md
Local README	examples/architectures/eval_artifact_profile/README.md

Run it:

python examples/architectures/eval_artifact_profile/main.py

(Or make architectures / make example.)

What it is (and isn't)

A context-shaping profile, not a statistics library. It does no estimation — that belongs to the artifact producer (for example skdr-eval). The profile, compile_eval_context(artifact, phase), decides what to show an agent, in what order, at each phase. Three fixtures (ok / caution / high_risk) exercise it.

Behaviour by phase

• Route — summary metadata only: artifact type, available diagnostics, whether it needs interpretation or policy gating. No metrics, no estimate.
• Interpret — the full diagnostic view: support health → warnings → (limitations, for high-risk) → assumptions → delta with uncertainty → decision stability → limitations → headline estimate → full-artifact handle.
• Answer — a compact human-safe summary: what was evaluated, whether the evidence is usable, the decision it supports, and the blocking caveats. The estimate leads the summary only for an ok artifact.

The safety invariants

Enforced by the profile and verified by check_invariants() and the test suite:

1. Never present V_hat without support diagnostics. Any phase whose output contains the value estimate also contains a support-health item earlier in the list; the route phase never exposes it.
2. High-risk artifacts foreground caveats before estimates.

main() asserts these at runtime, so a regression breaks make example rather than silently shipping unsafe context shaping.

Read next

• The Concepts guide covers ContextItem, Phase, and the prompt renderer used here.
• The context firewall is the complementary tool for keeping the raw artifact bytes out of the prompt.