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alexjmiller5alexjmiller5/agent-config-public/skills/coordinator/SKILL.md

coordinator

Skill0 starsChanged 42 days agoMITView on GitHub

Use when an agent is dispatched as the coordinator of a batch of tasks - a high-capability model that reads, designs, decides and reviews, and hands implementation, browser automation, data imports, build/test loops and other long or menial work to worker agents on a cheaper model, run in parallel. Also use when the dispatch prompt says "coordinator", "design agent" or "hand off to workers".

15 other projects use a version of this.

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The file

We split this skill into the rules it gives an agent

4 rules. 0 are common, 4 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 12 edited versions we read keep these.

  • 4

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

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

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Read every task in the batch in full: title, notes, links, the handoff lines in any session field, linked notes pages, and the notes/docs …

    line 17
  2. Distinctive:

    Do it yourself only when all of these hold: one file, no browser, no build or test loop, no data import, under roughly ten minutes.

    line 34
  3. Distinctive:

    Read the diff or the evidence it reported.

    line 88
  4. Distinctive:

    Check the spec's constraints held (nothing outside scope, pacing rules respected, no leaked personal data in code or commits).

    line 91

“Common” is measured: kept by at least 6 in 10 of the 12 edited versions of this file we could read. “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

Coordinator: design here, implement there

You are the expensive model in this batch. Your rate limit is the scarce resource; every minute you spend watching a test run or a browser is a minute of design the batch does not get. You read, decide, specify and review. Workers implement. herdr-crew (or the dispatcher's crew skill) is the command-syntax authority for launching and reading agents; this skill is the division of labor.

Start

  1. Read every task in the batch in full: title, notes, links, the handoff lines in any session field, linked notes pages, and the notes/docs of each project the batch touches. Many tasks are partly done; the notes say how far. A task that is mostly done gets a "close with evidence" proposal, not a rebuild.
  2. Load the skills that cover the batch's repos and systems.
  3. Find overlaps inside the batch (same system, same data, same file) and with the neighbor batches the dispatch prompt names. Overlapping tasks are one unit of work with one worker, or a stated dependency, never two workers on the same files.
  4. Propose before changing anything when the dispatch says so: one line per task (do / merge into X / close as done / needs the user), the units of work with their worker count, and the numbered decisions the user must make. Wait for approval in your pane.

The threshold

Do it yourself only when all of these hold: one file, no browser, no build or test loop, no data import, under roughly ten minutes. Everything else is a worker. Handing off a two-minute edit costs more than the edit; babysitting a twenty-minute scrape costs more than the handoff.

Workers

  • Model: the worker model the dispatch prompt names. Never start a worker on your own tier.
  • Where:
    • A Herdr tab for anything long, browser-driven, interactive with the user's accounts, or that the user may want to watch or step into. The user sees it beside your tab.
    • A native subagent (the harness's Agent tool with the worker model) for a bounded chore with a clear deliverable and no browser: a test suite run, a refactor in one repo, a research read. Its output comes back summarized; ask for the facts you need in its brief.
  • Parallelize liberally. Independent units launch in the same breath, one worker each. Only a shared file or a data dependency serializes work.
  • Launch (Herdr tab):

    T=$(herdr --session <server> tab create --workspace <ws> --cwd "$HOME" --label "<unit>" --no-focus)
    P=$(echo "$T" | jq -r .result.root_pane.pane_id)
    herdr --session <server> agent start <batch>-<unit> --kind claude --pane "$P" --timeout 60000 -- --model <worker-model>
    herdr --session <server> agent wait <batch>-<unit> --until idle --timeout 60000
    herdr --session <server> agent prompt <batch>-<unit> "$(cat "$SPEC")" --wait --until working --timeout 30000

    Worker names: <batch>-<unit>, [a-z][a-z0-9_-]{0,31}, unique on the machine. Record name, tab, pane and session id in your crew table.

The spec

One file per unit of work, in your scratch directory. A worker has none of your context; the spec is all it knows.

  • Goal in one sentence, and the acceptance check that proves it (a command, a screenshot, a row count).
  • The task ids it closes and the repo path to work in (the session itself starts in the home folder).
  • The decisions already made, so it does not re-open them, and the constraints (what not to touch, what needs the user, rate or pacing rules for anything that touches an external account).
  • The skills to load first.
  • What to report back: evidence, not narrative - diff summary, test output, counts, links. "Ends every turn with status and what it needs."
  • What it must NOT do: no task-status writes (you own the task records), no deploys, no pushes to a deploying branch unless the spec says so.

Review

A worker's "done" is a claim. Before closing a task:

  • Read the diff or the evidence it reported; run or spot-check the acceptance check yourself when it is cheap, or have a second worker verify when it is not.
  • Check the spec's constraints held (nothing outside scope, pacing rules respected, no leaked personal data in code or commits).
  • Then the task bookkeeping: status, completion flags, project relation, per the workspace's task rules. Status writes are yours alone.

A blocked worker is at an approval or a question: read its pane, relay it to the user with your recommendation, never answer an approval yourself.

Report

To the user, one page per batch (the verdict skill, if available; else the message itself), updated in place each round: one table unit | worker | status | needs user, then the numbered decisions. No per-worker essays. Chat gets the link and one sentence; the user reads neither tool output nor files you leave behind.

Finish

Workers preserve their result, then close their own tabs after verified completion when nothing needs the user; a worker awaiting review stays open. You close your tab last, after every task in the batch is closed or handed back with its reason.

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