agentleFS
EnjoyoerEnjoyoer/loadout/skills/orchestration/trial/SKILL.md

trial

Skill0 starsChanged 26 days agoMITView on GitHub

Use when the owner says "trial" or "replay", or asks whether an idea (a video, an X bookmark, a skill or workflow change) would help before adopting it.

1 other project uses a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

12 rules. About 0 are common, 11 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈11

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  • could be automatic: a setting could enforce it
  1. Distinctive:

    Test an idea against our own past work before adopting it.

    line 8
  2. Very specific:

    Look in every host's agent histories (paseo ls --global, paseo logs) and in each project's STATUS.html, LESSONS.md and owner reports.

    line 17
  3. Distinctive:

    If a rule has no help cases at all, mark it Drop and stop working on it.

    line 21
  4. Distinctive:

    If there's no evidence, write "unknown", not "same".

    line 28
  5. Distinctive:

    Use the same model and prompt each time: once with the current text and once with the proposed text.

    line 32
  6. Distinctive:

    never push, merge, message other agents, or touch live services or real accounts.

    line 36
  7. Distinctive:

    stop if the replay would need any of those.

    line 37
  8. Distinctive:

    Use one analysis worker. Read-only GPT is fine for this.

    line 40
  9. Distinctive:

    Use one reviewer at a time.

    line 41
  10. Distinctive:

    Stop once the verdict is clear, even if you haven't used every case or replay.

    line 43
  11. Distinctive:

    Write a table to the scratch folder with these columns: rule, help cases, harm cases, unknown, replay result, verdict.

    line 46
  12. Distinctive:

    Ask only if you are blocked.

    line 54

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Trial

Test an idea against our own past work before adopting it. Do everything up to a verdict; never adopt the change yourself.

1. Split the idea into rules

  • Break the idea into separate rules that can each be tested on its own.
  • For each rule, write down:
    • the symptom it should fix;
    • the harm it could cause, for example a review cap that cuts off a real finding.

2. Find cases (last 14 days, at most 20)

  • Look in every host's agent histories (paseo ls --global, paseo logs) and in each project's STATUS.html, LESSONS.md and owner reports.
  • Collect both kinds:
    • Help cases: the symptom happened.
    • Harm cases: the rule would have stopped something that turned out to be useful.
  • If a rule has no help cases at all, mark it Drop and stop working on it.
  • Listings are capped. If a host returns exactly the cap (200), page through with --since windows and also read that host's own stored agent records under its Paseo home, until you have the whole 14 days. List any agent whose log can't be read as a coverage gap.
  • Touch a file in the trial folder at least every 5 days, so the 7-day scratch expiry doesn't delete the evidence.

3. Judge each case

  • For every case, write: does the rule apply, and would the outcome have been better, worse or the same?
  • Back every judgment with evidence: the agent id plus a short quote, or a file path.
  • If there's no evidence, write "unknown", not "same".

4. Replay at most 3 cases

  • Pick the most informative cases and rerun each from its original state, in a scratch copy under ~/.cache/fleet-scratch/<project>/trial-<topic>/.
  • Use the same model and prompt each time: once with the current text and once with the proposed text.
  • Count only what you saw happen in those runs. A reasoned prediction is not a result.
  • Launch every replay agent with --new-workspace and its cwd set to the scratch clone (no remote); from inside an agent, paseo run --cwd is ignored without it. Check the agent's cwd before sending the prompt. A default cwd can land in the real repo.
  • During a replay:
    • never push, merge, message other agents, or touch live services or real accounts;
    • stop if the replay would need any of those.

Budget

  • Use one analysis worker. Read-only GPT is fine for this.
  • Use one reviewer at a time.
  • No nested sub-agents.
  • Stop once the verdict is clear, even if you haven't used every case or replay.

Verdict

  • Write a table to the scratch folder with these columns: rule, help cases, harm cases, unknown, replay result, verdict.
  • Each verdict is one of Adopt, Adopt modified (say what changed) or Drop.
  • A help case only shows that the symptom happened. Adopt and Adopt modified stay "provisional" until a replay shows the improvement. Report coverage gaps next to the verdicts.
  • Report to the owning PM in at most 6 lines. Include harms and unknowns plainly; never hide a rule that did harm.
  • End the report with: Trial: N cases, R replays, verdicts: ....
  • The owning PM decides what to adopt. Skills belong to the skills owner.

Asking the owner

Ask only if you are blocked. Put all the context in the question: what blocks you, the options, and your recommendation.

X bookmarks

A bookmark that proposes a tool or workflow change uses this skill as its A/B plan. If it gets no help cases, it closes as Drop without a replay.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.