# Ml Result Review > Use when concluding an ML experiment - produce a sober conclusion that separates confirmed results from exploratory observations and states the highest verified rung. - **Type:** Skill - **Install:** `agentstack add skill-pengzhangzhi-superpowers-ml-ml-result-review` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [pengzhangzhi](https://agentstack.voostack.com/s/pengzhangzhi) - **Installs:** 0 - **Category:** [Agent Skills](https://agentstack.voostack.com/c/agent-skills) - **Latest version:** 0.1.0 - **License:** MIT - **Upstream author:** [pengzhangzhi](https://github.com/pengzhangzhi) - **Source:** https://github.com/pengzhangzhi/superpowers-ml/tree/main/skills/ml-result-review ## Install ```sh agentstack add skill-pengzhangzhi-superpowers-ml-ml-result-review ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About # ML Result Review ## Overview You are concluding an ML experiment, not selling it. Passing tests showed the code path runs; they never showed the method works. Your job here is a SOBER conclusion that resists over-claiming, written so your human partner can decide on real evidence. **Core principle:** Confirmed, exploratory, and failed are different things. Keep them apart. This is downstream of `superpowers-ml:ml-feedback-ladder` (which owns the rungs) and `superpowers-ml:verification-before-completion` (evidence before claims). Cite the highest rung you actually reached, never the one you hoped for. ## What "Confirmed" Means A result is CONFIRMED only when the required full or equivalent evaluation completed under the declared primary metric and met the locked success criterion. - Met the locked criterion under the locked metric = confirmed. - Better-looking but not the locked test = exploratory, not confirmed. - **Operational interruptions (preemption, requeue, node failure) are not scientific failures.** A requeued run that still completed the locked evaluation is confirmed. Note the interruption; do not downgrade the result for it. Never claim the method beats a baseline without the full or equivalent evaluation under the locked primary metric. ## The Review Format Write the conclusion under these explicit headings, in order: ### CONFIRMED What met the locked success criterion under the primary metric. One line per claim, each tied to the evaluation that proved it. If nothing is confirmed, write "None." ### EXPLORATORY Interesting observations that were NOT the locked test: secondary metrics, partial runs, eyeballed curves, single seeds. Label clearly so no one mistakes these for results. ### FAILED / INCOMPLETE Runs that did not finish the locked evaluation, and WHY. Distinguish scientific failure (method/config wrong) from operational interruption (infra). An operational interruption belongs here only if it actually prevented the evaluation from completing. ### HIGHEST VERIFIED RUNG State the top rung (R0-R7) actually reached and the artifact that proves it (log path, metric value, checkpoint, decision memo). Use the canonical wording from `superpowers-ml:ml-feedback-ladder`. ### EVIDENCE GAPS What remains unproven. What a skeptic would still doubt. Which rungs are not yet climbed. ### RECOMMENDED NEXT The single next experiment that closes the most important gap. Name its target rung. This is what you hand your human partner to decide on. ## Force The Supported / Not-Supported Split Every conclusion must separate what the evidence supports from what it does not. Model the language exactly: ``` Supported: implementation trains stably through R5 pilot. Not supported yet: variant beats baseline at full scale. Exploratory: early loss looked better, but this was not the locked primary metric. ``` If you cannot phrase a claim as "Supported:" with its evidence, it is not supported. Demote it. ## Reporting Line Close with the standard rung statement, naming the highest GREEN rung and what is still unverified above it, e.g.: > Verified through R5 (short pilot). Not yet verified by full study. ## Red Flags - STOP - "It works" / "the method wins" without the locked full evaluation - Quoting a secondary or early metric as if it were the locked one - Treating a preemption or requeue as a scientific failure - Claiming a rung you did not reach, or omitting the artifact for it - An empty EVIDENCE GAPS section (there are always gaps) - A conclusion with no RECOMMENDED NEXT ## The Bottom Line Separate confirmed from exploratory from failed. State the highest rung you actually climbed, with its artifact. Name what is still unproven. A sober "not supported yet" is a real result. An over-claim is a liability. ## Source & license This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [pengzhangzhi](https://github.com/pengzhangzhi) - **Source:** [pengzhangzhi/superpowers-ml](https://github.com/pengzhangzhi/superpowers-ml) - **License:** MIT Install and usage instructions live in the source repository linked above. ## Pricing - **Free** — Free ## Security capabilities Automated source analysis of v0.1.0 — what this tool can access: - **Network access:** no - **Filesystem access:** no - **Shell / process execution:** no - **Environment & secrets:** no - **Dynamic code execution:** no *"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.* ## Versions - **0.1.0** — security scan: passed — Imported from the upstream source. ## Links - Listing page: https://agentstack.voostack.com/l/skill-pengzhangzhi-superpowers-ml-ml-result-review - Seller: https://agentstack.voostack.com/s/pengzhangzhi - Browse the marketplace: https://agentstack.voostack.com/browse --- Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.