/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
$ npx -y skills add evo-hq/evo --skill report --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/report
Context preview
The summary Claude sees to decide when to auto-load this skill.
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
SKILL.md
report.SKILL.mdname: 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:
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.
Read more
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:
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.
Get started with autoresearch on any codebase - with two simple commands. Do you want to do more with autoresearch or need a custom, hands-on deployment? Request access to evo platform or email hello@evo-hq.com.
Other skills on evo.
- /discover
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
Open skill - /infra-setup
Non-user-invocable provider/setup reference for evo backend switching, prerequisite checks, and auth/install guidance.
Open skill - /optimize
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
Open skill - /ship
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
Open skill - /subagent
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
Open skill - /discover
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
Open skill

