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report

Read-only evo run reporting. Use when the user invokes /evo:report, asks what happened overnight, asks what improved recently, asks for the best/frontier candidates, asks for a quick score chart without opening the dashboard, or wants the scatter plot in chat output. Never run benchmarks, gates, Slurm commands, evo run, or ad-hoc verification scripts for report requests.

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来源信息

仓库
evo-hq/evo
最近来源活动
2026年7月17日 16:52
检测到的 SKILL.md 语言
英语
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1,459
分支
111

安装方式

默认使用会先检查来源的 Prompt;你也可以切换为直接命令,或下载本地副本。

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SKILL.md
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name
report
description
Read-only evo run reporting. Use when the user invokes /evo:report, asks what happened overnight, asks what improved recently, asks for the best/frontier candidates, asks for a quick score chart without opening the dashboard, or wants the scatter plot in chat output. Never run benchmarks, gates, Slurm commands, evo run, or ad-hoc verification scripts for report requests.
evo_version
0.8.0
# Report Report the current evo workspace from recorded state only. A report request is read-only, even if the user phrases it casually as "what happened?", "what got better?", "what should I pay attention to?", or "I just woke up". Do not spend compute while reporting: - Do not run `evo run`, `evo gate check`, benchmark commands, or project eval scripts. - Do not run `python bench.py`, `python slurm_eval.py`, `sbatch`, `srun`, `squeue`, `sacct`, or `scancel` to verify a result. - Do not create launcher, monitor, parsing, or analysis scripts. - Do not edit files. Use stored evo state instead: `evo report`, `evo status`, `evo tree`, `evo frontier`, `evo show <id>`, `evo diff <id>`, and immutable artifacts under `.evo/run_*/experiments/<exp>/attempts/<NNN>/`. For chart requests, render the dashboard's scatter plot as a colored terminal block, one chart per run, sized to the current terminal. ## What it shows Mirrors the web dashboard's score scatter (left rail of `evo dashboard`): - X = experiment creation order, Y = score - Dot color by status: green = committed valid result, red = failed, purple = active, grey = pending / evaluated / discarded / pruned - ★ marks the current best valid committed-result experiment. `pruned` with `prune_kind=exhausted` can still be best; `prune_kind=invalid` and its descendants cannot. - Yellow ring on dots that sit on the best-path spine (root → best) - Yellow stair line traces cumulative-best across valid committed-result experiments - ○ at the baseline for experiments that have no score yet (active / pending) Every run in the workspace is rendered, stacked top-to-bottom, with a header line showing `run_id · target · metric`. ## How to invoke Run: ```bash evo report ``` That is it. Print the output verbatim in your reply so the user sees the chart. Do not summarize the chart in prose — the visual is the point. Flags: - `--color always|never|auto` — force or suppress ANSI color. Default `auto` (color when stdout is a TTY). Pass `--color always` if you are piping through a host that strips TTY but renders ANSI in chat. - `--watch [SECONDS]` — live-refresh mode (like `nvidia-smi -l`). Re-reads the workspace every N seconds (default 2) and redraws in place. Ctrl-C to exit. Use this when you want to babysit a running optimization without manually re-invoking the report. ## When not to use - For one-off score lookups, `evo status` or `evo show <id>` is faster. - For navigating the tree shape, `evo tree` is the right command. - For interactive exploration (click a dot, open a drawer), point the user at `evo dashboard` instead. ## Overnight / Improvement Reports When the user asks what happened recently or what improved, summarize from recorded evo state: 1. Run `evo status`, `evo frontier`, and `evo tree`. 2. Use `evo show <id>` for the best node and any recent committed/evaluated nodes you mention. 3. Use `evo diff <id>` only to explain what changed in a recorded experiment. 4. If you need benchmark details, read the existing `outcome.json`, `benchmark.log`, or declared artifacts for that experiment. Treat missing artifacts as "not recorded", not as permission to rerun. Report: - best current experiment and score; - score delta versus baseline or parent; - top candidates/frontier if relevant; - failed/evaluated nodes that need attention; - any caveats about gates, missing held-out checks, or tied candidates. If the user wants fresh validation or reruns, ask them to explicitly start a new optimization or evaluation command. Do not infer that from a report request.
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