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Turn messy repo intent into scoped AI Work Orders

Project description

Sembl

Turn messy repo intent into scoped AI Work Orders.

Sembl is not an AI coding agent. It is the layer that runs before one:

repo + task -> Work Order -> agent executes with tighter scope

A Work Order is an execution contract. It tells an agent:

  • what the goal is, and what it is not
  • which files it can touch
  • which files it should inspect but not modify
  • what must be true when it finishes
  • how to prove it succeeded
  • when to stop and ask a human

Website: https://sembl.vercel.app

Current Status

Sembl is early but usable for testing. The current CLI supports:

  • repo probing for language/framework/branch/dirty state
  • optional Graphify context
  • optional code-review-graph context
  • graph diagnostics via sembl doctor, and --graph-mode auto|required|off
  • LLM graph-impact synthesis over code-review-graph output (--no-graph-enrichment to skip)
  • OpenAI, Anthropic, Gemini, and NVIDIA NIM providers
  • work-order output as Markdown, JSON, executor prompt, validation plan, and graph-impact analysis

The best test path is graph-first:

pip install "sembl[graph-pipeline]"
sembl generate --repo C:\path\to\repo --task "fix the failing login redirect test" --provider nvidia --require-graph-context

Install

Sembl is published on PyPI: https://pypi.org/project/sembl/

# Core CLI
pip install sembl

# With the graph pipeline (Graphify + code-review-graph)
pip install "sembl[graph-pipeline]"

# As an isolated tool
uv tool install sembl

Pre-release channels

For the latest unreleased commits, install from GitHub:

uv pip install "sembl[graph-pipeline] @ git+https://github.com/speedvibecode/sembl.git"

TestPyPI mirrors each release (the --extra-index-url lets dependencies resolve from the real PyPI):

pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/ sembl

Install From Source

git clone https://github.com/speedvibecode/sembl
cd sembl
uv pip install -e ".[graph-pipeline]"

Plain pip also works:

pip install -e ".[graph-pipeline]"

Provider Keys

Set one provider key before generation:

$env:OPENAI_API_KEY="..."
$env:ANTHROPIC_API_KEY="..."
$env:GEMINI_API_KEY="..."
$env:NVIDIA_API_KEY="..."

Then choose the provider:

sembl generate --repo C:\path\to\repo --task "replace starter screen text" --provider nvidia

Optional Graph Context

Sembl can run without graph tools, but the strongest results come from Graphify plus code-review-graph.

graphify update C:\path\to\repo --no-cluster
code-review-graph build --repo C:\path\to\repo --data-dir C:\path\to\repo-specific-crg-data --skip-flows

$env:CRG_DATA_DIR="C:\path\to\repo-specific-crg-data"
sembl generate --repo C:\path\to\repo --task "fix the failing login redirect test" --provider nvidia --graph-mode required

Sembl guards against stale generic CRG_DATA_DIR values by deriving a repo-specific graph data directory when the env var does not look like it belongs to the target repo.

Diagnose and control graph context

Run sembl doctor first to see exactly what is installed, what is built, and the copy-paste command to fix each gap (add --fix to install missing graph tools, or --json for machine-readable output):

sembl doctor --repo C:\path\to\repo

Then choose how generation treats graph context with --graph-mode:

  • auto (default): use graph context if available, otherwise explain what is missing and fall back to direct repo probing.
  • required: fail before any LLM call if graph context is unavailable, so no tokens are wasted. (--require-graph-context is a backward-compatible alias.)
  • off: skip Graphify and code-review-graph entirely.

Add --refresh-graph to rebuild the graphs (Graphify update + code-review-graph build) before generating.

Usage

# Generate a Work Order for the current repo
sembl generate --task "add recurring expenses to this tracker" --provider nvidia

# Generate for an explicit repo
sembl generate --repo C:\path\to\repo --task "fix the login redirect bug" --provider nvidia

# Check the graph subsystem (tools, graphs, keys) and how to fix gaps
sembl doctor --repo C:\path\to\repo

# Require graph context (fails before any LLM call if it is unavailable)
sembl generate --repo C:\path\to\repo --task "fix the login redirect bug" --provider nvidia --graph-mode required

# Rebuild the graphs first, then generate on fresh context
sembl generate --repo C:\path\to\repo --task "fix the login redirect bug" --provider nvidia --refresh-graph

# List Work Orders
sembl list

# Show latest Work Order
sembl show

# Show the executor prompt
sembl show --file executor-prompt

# Show the graph-impact analysis (when graph context was available)
sembl show --file graph-impact

Output

.sembl/work-orders/wo-myproject-{timestamp}-{slug}/
  work-order.md       - read this
  executor-prompt.md  - paste into your agent
  validation-plan.md  - run this after
  work-order.json     - machine-readable
  graph-impact.md     - LLM synthesis of code-review-graph blast radius (graph context only)

Graph Impact Synthesis

When code-review-graph context is available, Sembl runs a focused LLM pre-pass that turns the graph's terse structural output (blast radius, node/edge counts) into a concise, grounded impact analysis: likely edit targets, hidden coupling, and files to keep read-only. That synthesis grounds the main Work Order and is also written to graph-impact.md. It is best-effort - if the provider call fails it is skipped silently. Disable it with --no-graph-enrichment.

The 8 Locks

Lock Purpose
Intent Goal, outcome, task type
Boundary Non-goals, forbidden areas
Scope Editable paths, read-only context
Context Files to inspect, architecture notes
Success Acceptance criteria, regressions
Proof Validation commands, tests to add
Safety Stop conditions, risk level
Executor Agent-ready prompt, patch expectations

Local Test

python -m unittest discover -s tests -v
python -m compileall -q sembl tests

Testing Notes

If you test Sembl on a real repo, the best feedback is:

  • the exact command you ran
  • whether graph context was available
  • the generated work-order.md
  • whether the executor agent could complete the task without scope confusion
  • any hallucinated files, missing validation commands, or false stop conditions

Releasing

Both channels publish automatically via GitHub Actions and Trusted Publishing (OIDC). No API tokens are stored.

Stable releases -> PyPI

.github/workflows/release.yml publishes to PyPI when you publish a GitHub Release.

  1. Bump the version in pyproject.toml, sembl/__init__.py, and the --version option in sembl/cli.py (all three must match).
  2. Commit and push.
  3. On GitHub: Releases -> Draft a new release -> Create a new tag named v<version> (e.g. v0.1.2, matching the bumped version) -> Publish.

The workflow builds, runs twine check, and publishes to PyPI. The tag must equal the pyproject.toml version or the build fails with a clear error.

Dev builds -> TestPyPI

.github/workflows/testpypi.yml publishes a uniquely-versioned dev build (<version>.devN) to TestPyPI on every push to master that touches code. Nothing is committed; the .devN suffix is stamped in CI only.

Testers install the latest dev build with pip:

pip install --pre --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/ sembl

Or with uv (needs --prerelease allow and a best-match index strategy so the dev build is preferred over the last stable release):

uv pip install --prerelease allow --index-strategy unsafe-best-match --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/ sembl

Keep master on the next in-development version (e.g. after releasing 0.1.1, bump to 0.1.2) so dev builds sort above the last stable release.

Models write code. Sembl makes the work governable.

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