본문으로 건너뛰기
cccskills
무료GitHub에 공개

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.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

설치 방법 보기

포함된 파일(1)

  • SKILL.md3.9 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

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:

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.

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

discover

무료

Initialize evo for the current repository by exploring the codebase, proposing unexplored optimization dimensions, constructing the benchmark inside a baseline worktree, and running the first experiment. Use when the user invokes /evo:discover, mentions setting up evo, wants to instrument a codebase for autonomous optimization, or asks to start a new evo run on a project.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

evo-hq/evo1.5천2026년 10월 5일 업데이트

This skill should be used when picking or diagnosing a training move (SFT, LoRA, DPO/KTO/ORPO, RFT, GRPO/PPO/RLOO, RLHF), or when the user mentions fine-tuning, post-training, training recipe, reward design, or weight updates. Decision tree by reward shape, smoke-run gate, three failure diagnostics, five false-progress patterns. Provider recipes and I/O contract in references/.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

evo-hq/evo1.5천2026년 10월 5일 업데이트

Non-user-invocable provider/setup reference for evo backend switching, prerequisite checks, and auth/install guidance.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

evo-hq/evo1.5천2026년 10월 5일 업데이트

optimize

무료

Drive structured autoresearch iteration after evo:discover and the baseline commit. Use when the user invokes /evo:optimize or asks to try ideas, try variants, run experiments, use available GPUs, improve the current best/frontier, continue an evo search, or compare candidate changes in an evo workspace. The orchestrator plans and spawns optimization subagents; candidate edits/runs belong to those subagents. Width is set via subagents=N (1 for serial workloads, larger for parallel); the loop's structural value applies at any width.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

evo-hq/evo1.5천2026년 10월 5일 업데이트

ship

무료

Land the winning experiment from an evo run as a clean, mergeable change -- open a PR when the repo has a remote, otherwise merge into the working branch. Distills the best-scoring experiment down to the minimal diff that reproduces its behaviour, shaped for the qualities a maintainer merges on (scope discipline, test integrity, style adherence), then attaches an advisory mergeability report. Use when the user invokes /evo:ship, asks to land/merge/ship the best result, or wants to turn a finished optimization into a pull request.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

evo-hq/evo1.5천2026년 10월 5일 업데이트

subagent

무료

Protocol that evo optimization subagents follow when dispatched from /optimize. Auto-loaded by spawned subagents via their host's skill loader. The orchestrator may also invoke this skill to understand the brief shape its dispatched subagents expect + what they're required to emit -- useful when writing briefs or debugging a subagent's behavior.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

evo-hq/evo1.5천2026년 10월 5일 업데이트

evo-hq의 스킬 모두 보기

이 스킬의 문제 신고