david-silver Eval report.

Validation plan

What the agent should do next

1. 1Inspect repository, README/SKILL.md, license, and recent commits before production use.
2. 2Install in an isolated workspace or sandbox with no production secrets available.
3. 3Run the smallest representative task and record files touched, commands run, network access, and outputs.
4. 4Compare the selected skill against at least one alternative when the eval status is review or failed.
5. 5Promote only after the agent reports a successful verification result and unresolved warnings are accepted.

Do not use when

Conditions that require another skill

• teams that need a vendor-supported SLA
• production agents without a repository review
• Core principles contain duplication: the first three principles all express the same 'discard human data to break performance ceiling' idea with cosmetic rewording.
• No OpenAgentSkill engagement data yet
• The skill lacks concrete RL engineering heuristics (e.g., baseline subtraction, eligibility traces, exploration scaling) that are present in the source corpus, making it less actionable for actual ML engineering.
• Frameworks and heuristics sections omit source attributions (src_XXX tags) that would improve traceability and credibility.