prime-agent-feature-factory

Prime Agent integration for feature-factory. It adds a /feature command and a Prime-specific adapter skill while preserving the factory package's canonical workflow and CLI-owned durable state.

Install

prime-agent package install npm:prime-agent-feature-factory

The package manifest exposes its extension and skill through pi.extensions and pi.skills. Prime Agent installs the runtime feature-factory dependency with it. Node.js 22 or newer is required.

Use

/feature [--autonomous | --headless] <ticket key | feature idea>

Unattended, a run needs two things beyond the invocation, both documented with their reasoning in the repository's operator guide: redirect stdin from /dev/null, because an inherited pipe that never reaches EOF blocks the CLI before it emits a byte and looks exactly like a broken tool; and raise the --autonomous limits, because the defaults of 12 turns, 3 continuations, 80,000 tokens and 30 minutes stop a real run mid-flight in a way that looks like a stall. -p alone prints one response and exits, which initializes a run and then abandons it.

The integration currently drives foreground runs only. It rejects --background before creating or changing a run. The extension exposes the current Prime session and installed agent directory through feature_factory_context; the skill uses Prime RLM children for specialist work and requires their reports through agent messaging.

skills/feature/WORKFLOW.md is a package-local copy of the factory's canonical workflow. pretest and prepack refresh it with the repository sync script so the adapter never relies on a skill loader to inline another package's resource. The CLI remains the only writer of run.json.

Specialist model and thinking level

Every agent file in feature-factory declares model, role, and effort in its frontmatter. This adapter uses role and effort, and ignores the declared model for the same reason the OpenCode adapter does: sonnet and opus are tiers, while Prime requires an exact provider/id selector and fails a spawn given anything else.

effort becomes the child's thinking level directly — every declared value (low, medium, high, xhigh) is one of Prime's THINKING_LEVELS, so nothing is mapped or approximated. A value outside that set is dropped rather than passed, because an unknown level fails the spawn instead of being ignored, and inheriting the parent's level is the safer miss.

A model resolves through the same four levels as the OpenCode plugin, most specific first, so an operator configuring both hosts learns one vocabulary:

profiles[<agent>]  →  profiles[<role>]  →  profiles.default  →  profile

Configure them in .prime/agent/feature-factory.json, project-local first and then ~/.prime/agent/feature-factory.json for every project:

{ "profiles": {
    "planning": { "model": "openai/gpt-5.6-sol", "thinking": "xhigh" },
    "builder":  { "model": "openai/gpt-5.6-sol" },
    "story-reader": { "model": "openai/gpt-5.6-luna", "thinking": "minimal" }
} }

The project file wins outright over the home file; they are not merged, so a project that sets only builder does not inherit the home file's other roles. A malformed or non-object file is skipped rather than raised, because a typo in an optional profile must not stop the extension registering and take /feature down with it.

That file is the configuration surface because Prime registers an extension by path and calls its default export with pi alone — there is no per-extension options object in settings.json or in the package manifest, so anything reachable only by calling the export directly is not configuration.

Roles come from each agent's own frontmatter — planning, story, research, design, builder, test, reviewer — so a new agent inherits its role without needing an entry.

model has no default here, deliberately. Prime's own subagentDefaultModel setting already means "one model for every child", and it applies exactly when a spawn omits model=. Pinning a selector is fail-closed at both layers: an unavailable, unauthenticated or expired selection fails the spawn rather than falling back to another model. That is the behaviour you want — a run should not quietly proceed on a model nobody chose — but it means a wrong selector stops the chain rather than degrading it. Configure one only after rlm.find_models() confirms it from the credentials the run will use.

What this adapter cannot enforce

On OpenCode, each agent's declared tools becomes a permission map, and that is what keeps a reviewer from editing the code it judges. Prime children inherit the parent's tools and skills, and rlm.spawn takes no tool or skill argument, so that separation is instruction here rather than enforcement: the composed prompt states the allowed files and tools, and nothing stops a child ignoring it. Recursion depth is enforced by the host — the default permits children but not grandchildren.

Development

From this package directory:

npm test
npm pack --dry-run

License

MIT