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Skill1.6k repo starsupdated 5d ago

opencode-delegate

>-

Install in Claude Code
Copy
git clone --depth 1 https://github.com/amElnagdy/delegate-skills /tmp/opencode-delegate && cp -r /tmp/opencode-delegate/skills/opencode-delegate ~/.claude/skills/opencode-delegate
Then start a new Claude Code session; the skill loads automatically.

SKILL.md

# OpenCode Delegate

You are the **orchestrator**. This skill lets you hand a bounded coding task to a separate
**implementer** — the OpenCode CLI — then review what it produced and land it yourself. You write
the brief and own the judgment; OpenCode does the typing in its own session; you verify and commit.

Nothing here is specific to one orchestrating agent. The loop needs only the ability to run a shell
command and read a file, so any agent with those two capabilities — Claude Code, OpenCode driving a
sibling session, or a comparable one — can drive it. (It is designed for and run on Claude Code; treat
other orchestrators as designed-for, not yet proven.)

## When NOT to use this

- The task is small enough to just do inline — delegation overhead is not worth it.
- The `opencode` CLI is not installed or not authenticated (run `opencode auth login`).
- You want to write the code yourself, or you only need a review (use the `plan` agent via `--read-only`).

## Prerequisites (check once)

1. `opencode --version` succeeds. If not, install (`npm i -g opencode-ai`, or the native installer from
   opencode.ai) and `opencode auth login`.
2. **Confirm which `opencode` is on PATH.** `command -v opencode` shows the active binary and
   `opencode --version` its version. The relay records the version it ran into `result.json`, so a stale
   binary is visible after the fact.
3. A model provider is authenticated — `opencode auth list` shows at least one credential.
4. You are in (or will point `--cd` at) the target git repository.

## Choose the implementer model

OpenCode has **no safe default** — a bare `opencode run` errors — so a fresh run needs a model via
`--model` or a fleet `--lane` that sets one (a resumed run inherits its session's model). Naming the
model is the one decision a single-model backend like codex-delegate never had, and it has two owners:

- **The human owns which models are allowed.** `opencode models` lists hundreds of entries, most billed
  per token (OpenRouter and the like); only the human knows which are their flat-rate subscriptions, and
  the CLI can't tell them apart. So the usable set is theirs — ideally stated once in the repo's
  `AGENTS.md` or their `CLAUDE.md` (e.g. "delegate mechanical work to `opencode-go/…`, hard logic to
  `…`").
- **You, the orchestrator, pick per task — from that set.** Match the model to the brief: a cheap, fast
  model for a mechanical sweep (rename, migration, removal); a strong one for a subtle bug or a
  money/security path.
- **If no usable set is stated, ask — don't guess.** Guessing from the catalog risks a metered model and
  a surprise bill. Name the constraint to the human and let them choose.

More depth: [references/writing-the-brief.md](references/writing-the-brief.md).

## The loop

Run these five steps per task. Steps 1, 4, and 5 are your judgment; 2 and 3 are mechanical.

### 1. Write the brief

OpenCode sees **only** the text you send plus what it can read from the working tree — no chat history,
no shared context. Everything the task needs goes in the brief: the goal, the current state, what to
change, what to leave untouched, the project's **actual** gate commands (discover them from the repo's
AGENTS.md/CLAUDE.md/Makefile — do not assume), and a report contract. Tell OpenCode it will **not**
commit (you will). Keep one task per brief. Full guidance and a template:
[references/writing-the-brief.md](references/writing-the-brief.md).

### 2. Dispatch

Send the brief to OpenCode with the bundled helper. It wraps `opencode run`, captures the run, and
writes a structured `result.json` — so your only job is "run a command, read a file." (`<skill-dir>`
below is this skill's installed directory — the folder containing this `SKILL.md`. Claude Code prints
it as "Base directory for this skill" when the skill loads; on other orchestrators use that same
directory — if unsure where it landed, run `find ~ -name relay.mjs -path '*opencode-delegate*'` and
substitute the directory above it.)

```bash
node "<skill-dir>/scripts/relay.mjs" --brief brief.txt --model <provider/model> --cd /path/to/repo
# --model (or a --lane that sets model) is required on a fresh run
# fleet lane from delegate-setup:           add --lane <name>  (dials apply; flags still win)
# read-only (review/diagnosis, no edits):   add --read-only   (uses the plan agent)
# continue the previous OpenCode session:   add --resume-last  (delta brief only; keeps the model)
# hard time limit (watchdog):               add --timeout 2h  (default: off; implementation runs routinely need 1-2h)
# see all options:                          node .../relay.mjs --help
```

The helper defaults to the write-capable `build` agent and writes its artifacts to a temp dir, so the
repo under review stays clean. It **never commits** — see step 5. Mechanics, flags, and the
`result.json` shape: [references/dispatch-and-poll.md](references/dispatch-and-poll.md).

### 3. Wait for completion

The helper blocks until OpenCode finishes, so back it with whatever your orchestrator offers and resume
when it returns:

- **Claude Code:** run the Bash call with `run_in_background: true`; you are notified on completion.
- **Plain shell / other agents:** run it in the foreground for short tasks, or background it and poll
  the result file — `… &` in bash/zsh (including Git Bash/WSL), or your shell's equivalent (`Start-Job`
  in PowerShell, `start /b` in cmd). The run is done when `result.json` exists with a `status`. (A
  pre-run usage error — bad args or an empty brief — instead exits with code 2 and writes no result
  file, so check the exit code too. A missing `opencode` binary exits 127 but *does* write a
  `result.json` with status `opencode_unavailable`.)

Do not trust progress trackers over reality: a run is finished when `result.json` is written and the
process has exited. Read the working tree, not a status line. The implementer's full report is
the `finalMessage` field in `result.json` (also printed