Aider Delegate

Aider Delegate

You are the orchestrator. Hand a bounded coding task to a separate implementer - Aider - then review what it produced and land it yourself. You write the brief and own the judgment; Aider does the typing in its own run; you verify and commit.

The loop needs only a shell command and file access, so any comparable orchestrator can drive it.

The one thing to know about Aider

Aider commits by default. Two of its defaults would destroy the reviewable diff this skill exists to produce:

• --auto-commits (default True) - Aider commits its own edits after each exchange.
• --dirty-commits (default True) - Aider commits your pre-existing uncommitted work before it starts editing.

The relay always passes --no-auto-commits and --no-dirty-commits, and neither is configurable through it. If you ever drive aider by hand instead of through the relay, pass both yourself, or the work lands as commits you never reviewed. The relay also passes --no-gitignore, because Aider otherwise writes .aider* into .gitignore on startup and dirties the tree you are about to read.

When NOT to use this

• The task is small enough to do inline; delegation overhead is not worth it.
• The aider CLI is not installed, or no model is configured for it.
• You want the implementer to manage its own commits. Aider can, but this skill deliberately turns that off - the diff is the deliverable.

Prerequisites (check once)

1. Install Aider - python -m pip install aider-chat, or the standalone installer from the Aider install docs.
2. Configure a model. Aider reads provider keys from the environment (OPENAI_API_KEY, ANTHROPIC_API_KEY, …) or its own config; see Aider's model docs.
3. Confirm aider --version succeeds.
4. Work in, or point --cd at, the target git repository.

Choose the model

Aider uses its own configured model when --model is omitted. Pass --model <name> to pick another.

Local and self-hosted models

Aider talks to any OpenAI-compatible endpoint, so this is also the skill for delegating to a model running on the user's own hardware - llama.cpp's server, Ollama, vLLM, LM Studio, or anything else that serves the same API. Pair --model with --api-base:

node "<skill-dir>/scripts/relay.mjs" --brief brief.txt --cd /path/to/repo \
  --model openai/<served-model-name> --api-base http://127.0.0.1:<port>/v1

Three things differ from a hosted provider:

• The openai/ prefix is required. It tells Aider to speak the OpenAI protocol to your endpoint; the part after it is whatever name your server reports, not a provider catalog name.
• A placeholder key is still needed. Export any non-empty OPENAI_API_KEY. The client library requires the header even when the server ignores its value.
• Ask for a smaller edit format. Local models often fail Aider's default diff format, which requires exact search/replace blocks. --edit-format whole trades tokens for reliability; keep the brief's scope tight with --file so whole-file rewrites stay cheap.

A local endpoint that is not running looks like a hang, not an error: Aider retries the connection until the relay's --timeout watchdog fires and reports status: "timeout". Confirm the server is up before dispatching a long brief.

Staying offline

No account or provider registration is involved: Aider is a pip install, the endpoint is yours, and OPENAI_API_KEY only has to be non-empty. The relay pins the flags that would otherwise reach the network on their own - --no-check-update, --no-analytics (Aider's own default is random, which opts some sessions in by itself), and --no-detect-urls, without which Aider offers to scrape any URL in the brief and --yes-always accepts that offer silently.

--no-suggest-shell-commands closes the remaining path by which a run could reach the network without being asked to. What stays outside the relay's control is the brief itself: instructions that tell Aider to install a package or call an API will still be carried out, and --auto-lint runs the repository's own tooling. Offline here means nothing in the dispatch path reaches out on its own - not that a sandbox is stopping it.

The loop

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

1. Write the brief

Aider sees only the text you send plus the files in its editing scope - no chat history or shared context. Include the goal, current state, what to change, what to leave untouched, the project's actual gates, and a report contract. Keep one task per brief. See references/writing-the-brief.md.

2. Dispatch

Use the bundled helper. It wraps Aider's headless --message-file mode, captures the run, and writes result.json. (<skill-dir> is the installed folder containing this SKILL.md.)

node "<skill-dir>/scripts/relay.mjs" --brief brief.txt --cd /path/to/repo
# choose a model:                        add --model <name>
# point at an OpenAI-compatible server:  add --api-base <url>
# scope the edit surface:                add --file <path> (repeatable), --read <path> for context only
# dry run, no files modified:            add --read-only
# continue the previous chat:            add --resume-last  (delta brief only)
# hard time limit (watchdog):            add --timeout 2h  (the 30m default suits short runs; implementation briefs routinely need 1-2h)
# see all options:                       node .../relay.mjs --help

The child process's cwd pins the workspace. The brief is delivered with --message-file, so it never rides argv: it stays out of the host process list and clear of the OS argument size cap. The relay writes artifacts under the system temp dir by default and never commits. See references/dispatch-and-poll.md.

3. Wait for completion

The helper blocks until Aider finishes. Run it with the orchestrator's background-command facility, or background it in the shell and poll for result.json. A pre-run usage error exits 2 and writes no result; a missing aider exits 127 and writes status: "aider_unavailable".

Trust process state and the working tree over a progress display. Completion means the process exited and result.json exists. Aider's report is the finalMessage field in result.json (also printed in full on stdout between the report markers).

Aider exits 0 even when it never reached a model, so the relay scans the run for Aider's own endpoint and authentication errors and reports status: "failed" when it finds one. Treat a failed status with an error mentioning the endpoint as a configuration problem, not a coding failure.