specced 0.1.3

Interview-driven bootstrap for a reusable agentic coding setup: proof-loop engine + project rules + skills, installed into any repo.

specced

Install a reusable, interview-driven agentic coding setup into any repo — one command instead of copy-pasting .claude/, .codex/, CONSTITUTION.md, and the proof-loop scaffolding between projects.

specced is two things sharing one set of templates:

• a uv-installable CLI that does the deterministic, agent-agnostic scaffolding, and
• a Claude Code plugin whose specced-bootstrap skill interviews you — detects your stack, asks a few sharp questions, and writes the project-specific content.

Just want to get going? See QUICKSTART.md for the 2-minute path.

What you get

specced installs three layers into a repo:

1. The engine — the repo-task-proof-loop skill (spec-freeze → build → evidence → fresh-verify → fix, with durable .agent/tasks/<ID>/ artifacts). Vendored from OpenAI, Apache-2.0 — see NOTICE.
2. The structure — four project agents (.claude/agents/ + .codex/agents/), managed blocks in CLAUDE.md/AGENTS.md, a Stop-hook formatter, skeletons for .claude/rules/, .claude/code-review/, .mcp.json, and a Makefile verification vocabulary — plus an agent-experience layer: a pre-authorized permission allowlist, an orientation block, and a machine-readable checks map (.specced/).
3. The content (interview) — your real CONSTITUTION.md, per-track rules, review dimensions, MCP servers, and make targets — authored to fit this repo.

Install

uv tool install specced          # or: uvx --from git+https://github.com/NoroSaroyan/specced specced

In Claude Code, add the marketplace and install the plugin:

/plugin marketplace add NoroSaroyan/specced
/plugin install specced

Quickstart

From inside the target repo, in Claude Code:

/specced:init

This runs the interview: it detects your stack, asks what matters, runs specced init for the mechanics, then writes your constitution, rules, review dimensions, MCP servers, and Makefile targets. Add --minimal to author all content by hand.

Then start your first task with the installed engine:

init my-first-task     # via the repo-task-proof-loop skill

Documentation

Full docs in docs/: Getting started · Concepts · The proof loop · CLI reference · Skills · Presets · FAQ

CLI reference

specced detect                    Inspect the repo: languages, tracks, infra,
                                  suggested preset + MCP servers (JSON).
specced presets                   List stack presets.
specced init [--preset NAME|auto] [--minimal] [--force] [--format-cmd "…"]
                                  Install / refresh the setup (idempotent).
specced add-mcp <names…> [--force]  Add MCP servers to .mcp.json from the catalog.
specced add-skill <name> [--force]  Install a library skill into .claude/skills/.
specced list-skills               List available library skills.
specced sync                      Refresh engine + agents + managed blocks.
specced doctor                    Verify the setup is consistent.
specced status                    Show installed components, presets, mcp catalog, config.
specced version                   Print specced + engine versions.

13 presets (go, rust, python-fastapi, python-django, python, node-next, node-svelte, node-react, node-express, node, java-spring, ruby-rails, tauri — see docs/presets.md) and a 17-skill library (code-review, api-endpoint, db-migration, add-integration, background-worker, regen-client, write-tests, debug-issue, refactor, dependency-upgrade, perf-investigation, security-review, release, prepare-pr, new-domain-skill, decision-record, capture-rule — see docs/skills.md).

Every command prints JSON, so the interview agent can read exactly what happened. State is recorded in .specced/config.json.

How it works

The CLI is the mechanical half: it copies the vendored engine, installs the static agent + managed-block templates verbatim (the same files the engine itself would write), and lays down create-if-absent skeletons for the content layer. The plugin is the intelligent half: the specced-bootstrap skill detects, interviews, calls the CLI, then replaces the skeletons with real content. One template tree, two surfaces.

Develop

make install   # uv venv + editable install with dev extras
make verify    # ruff format --check + ruff check + pytest + build (the CI gate)

See CONTRIBUTING.md and docs/architecture.md.

Status

v0.1 — interview-first, with stack detection, 13 presets, a 7-server MCP catalog, a 17-skill library, an agent-experience layer, and GitHub repo-as-code (Terraform under infra/terraform/github/). Roadmap: a specced update that diffs managed content across versions, more presets/skills, and PyPI publication.

License

specced is MIT (see LICENSE). It bundles the Apache-2.0 repo-task-proof-loop engine unmodified; attribution in NOTICE.