diff --git a/igneous/task_creation/common.py b/igneous/task_creation/common.py
index 5600fe5..17ed399 100644
--- a/igneous/task_creation/common.py
+++ b/igneous/task_creation/common.py
@@ -226,6 +226,8 @@ def set_encoding(cv, mip, encoding, encoding_level):
 
   if encoding == "jpeg":
     scale["jpeg_quality"] = encoding_level
+  elif encoding == "jpegxl":
+    scale["jpegxl_quality"] = encoding_level
   elif encoding == "png":
     scale["png_level"] = encoding_level
   elif encoding == "fpzip":
diff --git a/igneous/task_creation/image.py b/igneous/task_creation/image.py
index 9e06473..94ba786 100644
--- a/igneous/task_creation/image.py
+++ b/igneous/task_creation/image.py
@@ -406,14 +406,6 @@ def create_sharded_image_info(
   # maximum amount of information in the morton codes
   grid_size = np.ceil(Vec(*dataset_size) / Vec(*chunk_size)).astype(np.int64)
   max_bits = sum([ math.ceil(math.log2(size)) for size in grid_size ])
-  if max_bits > 64:
-    raise ValueError(
-      f"{max_bits}, more than a 64-bit integer, "
-      "would be required to describe the chunk positions "
-      "in this dataset. Try increasing the chunk size or "
-      "increasing dataset bounds."
-      f"Dataset Size: {dataset_size} Chunk Size: {chunk_size}"
-    )
 
   chunks_per_shard = math.ceil(uncompressed_shard_bytesize / (chunk_voxels * byte_width))
   chunks_per_shard = 2 ** int(math.log2(chunks_per_shard))
@@ -423,7 +415,7 @@ def create_sharded_image_info(
 
   # approximate, would need to account for rounding effects to be exact
   # rounding is corrected for via max_bits - pre - mini below.
-  num_shards = num_chunks / chunks_per_shard 
+  num_shards = num_chunks / chunks_per_shard
   
   def update_bits():
     shard_bits = int(math.ceil(math.log2(num_shards)))
@@ -465,7 +457,25 @@ def update_bits():
   # in the morton codes, so if there's any slack from rounding, the
   # remainder goes into shard bits.
   preshift_bits = preshift_bits - minishard_bits
-  shard_bits = max_bits - preshift_bits - minishard_bits
+  if dataset_size[2] == chunk_size[2]:
+    additional_bits = (preshift_bits // 3)
+    i = 0
+    while i < additional_bits:
+      max_bits += 1
+      preshift_bits += 1
+      if preshift_bits % 3 != 0:
+        i += 1
+
+  shard_bits = max(max_bits - preshift_bits - minishard_bits, 0)
+
+  if max_bits > 64:
+    raise ValueError(
+      f"{max_bits}, more than a 64-bit integer, "
+      "would be required to describe the chunk positions "
+      "in this dataset. Try increasing the chunk size or "
+      "increasing dataset bounds."
+      f"Dataset Size: {dataset_size} Chunk Size: {chunk_size}"
+    )
 
   if preshift_bits < 0:
     raise ValueError(f"Preshift bits cannot be negative. ({shard_bits}, {minishard_bits}, {preshift_bits}), total info: {max_bits} bits")
diff --git a/igneous/task_creation/skeleton.py b/igneous/task_creation/skeleton.py
index bb7d4a6..e99ab06 100644
--- a/igneous/task_creation/skeleton.py
+++ b/igneous/task_creation/skeleton.py
@@ -15,7 +15,7 @@
 from cloudvolume import CloudVolume
 from cloudvolume.lib import Vec, Bbox, max2, min2, xyzrange, find_closest_divisor, yellow, jsonify
 from cloudvolume.datasource.precomputed.sharding import ShardingSpecification
-from cloudfiles import CloudFiles
+from cloudfiles import CloudFiles, CloudFile
 
 from igneous.tasks import ( 
   SkeletonTask, UnshardedSkeletonMergeTask, 
@@ -58,6 +58,7 @@ def bounds_from_mesh(
     bbxes.append(bounds)
 
   bounds = Bbox.expand(*bbxes)
+  bounds = bounds.expand_to_chunk_size(shape, offset=vol.voxel_offset)
   return Bbox.clamp(bounds, vol.bounds)
 
 def create_skeletonizing_tasks(
@@ -71,9 +72,11 @@ def create_skeletonizing_tasks(
     parallel=1, fill_missing=False, 
     sharded=False, frag_path=None, spatial_index=True,
     synapses=None, num_synapses=None,
-    dust_global=False, 
+    dust_global=False, fix_autapses=False,
     cross_sectional_area=False,
     cross_sectional_area_smoothing_window=5,
+    timestamp=None,
+    root_ids_cloudpath=None,
   ):
   """
   Assign tasks with one voxel overlap in a regular grid 
@@ -121,6 +124,17 @@ def create_skeletonizing_tasks(
   fix_borders: Allows trivial merging of single overlap tasks. You'll only
     want to set this to false if you're working on single or non-overlapping
     volumes.
+  fix_autapses: Only possible for graphene volumes. Uses PyChunkGraph (PCG) information
+    to fix autapses (when a neuron synapses onto itself). This requires splitting
+    contacts between the edges of two touching voxels. The algorithm for doing this
+    requires much more memory.
+
+    This works by comparing the PYC L2 and root layers. L1 is watershed. L2 is the
+    connections only within an atomic chunk. The root layer provides the global
+    connectivity. Autapses can be distinguished at the L2 level, above that, they
+    may not be (and certainly not at the root level). We extract the voxel connectivity
+    graph from L2 and perform the overall trace at root connectivity.
+
   dust_threshold: don't skeletonize labels smaller than this number of voxels
     as seen by a single task.
   dust_global: Use global voxel counts for the dust threshold instead of from
@@ -155,10 +169,24 @@ def create_skeletonizing_tasks(
   to the total computation.)
   cross_sectional_area_smoothing_window: Perform a rolling average of the 
     normal vectors across these many vectors.
+  timestamp: for graphene volumes only, you can specify the timepoint to use
+  root_ids_cloudpath: for graphene volumes, if you have a materialized archive
+    if your desired timepoint, you can use this path for fetching root ID 
+    segmentation as it is far more efficient.
   """
   shape = Vec(*shape)
   vol = CloudVolume(cloudpath, mip=mip, info=info)
 
+  if fix_autapses:
+    if vol.meta.path.format != "graphene":
+      raise ValueError("fix_autapses can only be performed on graphene volumes.")
+
+    if not np.all(shape % vol.meta.graph_chunk_size == 0):
+      raise ValueError(
+        f"shape must be a multiple of the graph chunk size. Got: {shape}, "
+        f"{vol.meta.graph_chunk_size}"
+      )
+
   if dust_threshold > 0 and dust_global:
     cf = CloudFiles(cloudpath)
     vxctfile = cf.join(vol.key, 'stats', 'voxel_counts.mb')
@@ -201,6 +229,15 @@ def create_skeletonizing_tasks(
 
   vol.skeleton.meta.commit_info()
 
+  if frag_path:
+    frag_info_path = CloudFiles(frag_path).join(frag_path, "info")
+    frag_info = CloudFile(frag_info_path).get_json()
+    if not frag_info:
+      CloudFile(frag_info_path).put_json(vol.skeleton.meta.info)
+    elif 'scales' in frag_info:
+      frag_info_path = CloudFiles(frag_path).join(frag_path, vol.info["skeletons"], "info")
+      CloudFile(frag_info_path).put_json(vol.skeleton.meta.info)
+
   will_postprocess = bool(np.any(vol.bounds.size3() > shape))
   bounds = vol.bounds.clone()
 
@@ -247,8 +284,11 @@ def task(self, shape, offset):
         spatial_grid_shape=shape.clone(), # used for writing index filenames
         synapses=bbox_synapses,
         dust_global=dust_global,
+        fix_autapses=bool(fix_autapses),
+        timestamp=timestamp,
         cross_sectional_area=bool(cross_sectional_area),
         cross_sectional_area_smoothing_window=int(cross_sectional_area_smoothing_window),
+        root_ids_cloudpath=root_ids_cloudpath,
       )
 
     def synapses_for_bbox(self, shape, offset):
@@ -292,8 +332,11 @@ def on_finish(self):
           'spatial_index': bool(spatial_index),
           'synapses': bool(synapses),
           'dust_global': bool(dust_global),
+          'fix_autapses': bool(fix_autapses),
+          'timestamp': timestamp,
           'cross_sectional_area': bool(cross_sectional_area),
           'cross_sectional_area_smoothing_window': int(cross_sectional_area_smoothing_window),
+          'root_ids_cloudpath': root_ids_cloudpath,
         },
         'by': operator_contact(),
         'date': strftime('%Y-%m-%d %H:%M %Z'),
diff --git a/igneous/tasks/image/image.py b/igneous/tasks/image/image.py
index 2e72cd6..b093148 100755
--- a/igneous/tasks/image/image.py
+++ b/igneous/tasks/image/image.py
@@ -70,7 +70,7 @@ def downsample_and_upload(
     if max_mips is not None:
       factors = factors[:max_mips]
 
-    if len(factors) == 0:
+    if len(factors) == 0 and max_mips:
       print("No factors generated. Image Shape: {}, Downsample Shape: {}, Volume Shape: {}, Bounds: {}".format(
           image.shape, ds_shape, vol.volume_size, bounds)
       )
@@ -327,6 +327,9 @@ def execute(self):
       cts = np.bincount(img2d)
       levels[0:len(cts)] += cts.astype(np.uint64)
 
+    if len(bboxes) == 0:
+      return
+
     covered_area = sum([bbx.volume() for bbx in bboxes])
 
     bboxes = [(bbox.volume(), bbox.size3()) for bbox in bboxes]
@@ -376,7 +379,8 @@ def select_bounding_boxes(self, dataset_bounds):
       patch_start += self.offset
       bbox = Bbox(patch_start, patch_start + sample_shape.size3())
       bbox = Bbox.clamp(bbox, dataset_bounds)
-      bboxes.append(bbox)
+      if not bbox.subvoxel():
+        bboxes.append(bbox)
     return bboxes
 
 @queueable
diff --git a/igneous/tasks/skeleton.py b/igneous/tasks/skeleton.py
index cfe80f7..30fae46 100644
--- a/igneous/tasks/skeleton.py
+++ b/igneous/tasks/skeleton.py
@@ -1,4 +1,4 @@
-from typing import Optional,Sequence,Dict
+from typing import Optional, Sequence, Dict, List
 
 from functools import reduce
 import itertools
@@ -21,9 +21,10 @@
 
 import cloudvolume
 from cloudvolume import CloudVolume, Skeleton, paths
-from cloudvolume.lib import Vec, Bbox, sip
+from cloudvolume.lib import Vec, Bbox, sip, xyzrange
 from cloudvolume.datasource.precomputed.sharding import synthesize_shard_files
 
+import cc3d
 import fastremap
 import kimimaro
 
@@ -39,15 +40,6 @@ def filename_to_segid(filename):
   segid, = matches.groups()
   return int(segid)
 
-def skeldir(cloudpath):
-  cf = CloudFiles(cloudpath)
-  info = cf.get_json('info')
-
-  skel_dir = 'skeletons/'
-  if 'skeletons' in info:
-    skel_dir = info['skeletons']
-  return skel_dir
-
 def strip_integer_attributes(skeletons):
   for skel in skeletons:
     skel.extra_attributes = [ 
@@ -89,6 +81,9 @@ def __init__(
     cross_sectional_area_shape_delta:int = 150,
     dry_run:bool = False,
     strip_integer_attributes:bool = True,
+    fix_autapses:bool = False,
+    timestamp:Optional[int] = None,
+    root_ids_cloudpath:Optional[str] = None,
   ):
     super().__init__(
       cloudpath, shape, offset, mip, 
@@ -101,14 +96,25 @@ def __init__(
       spatial_grid_shape, synapses, bool(dust_global),
       bool(cross_sectional_area), int(cross_sectional_area_smoothing_window),
       int(cross_sectional_area_shape_delta),
-      bool(dry_run), bool(strip_integer_attributes)
+      bool(dry_run), bool(strip_integer_attributes),
+      bool(fix_autapses), timestamp,
+      root_ids_cloudpath,
     )
+    if isinstance(self.frag_path, str):
+      self.frag_path = cloudfiles.paths.normalize(self.frag_path)
     self.bounds = Bbox(offset, Vec(*shape) + Vec(*offset))
     self.index_bounds = Bbox(offset, Vec(*spatial_grid_shape) + Vec(*offset))
 
   def execute(self):
+    # For graphene volumes, if we've materialized the root IDs
+    # into a static archive, let's use that because it's way more
+    # efficient for fetching root IDs.
+    cloudpath = self.cloudpath
+    if self.root_ids_cloudpath:
+      cloudpath = self.root_ids_cloudpath
+
     vol = CloudVolume(
-      self.cloudpath, mip=self.mip, 
+      cloudpath, mip=self.mip, 
       info=self.info, cdn_cache=False,
       parallel=self.parallel, 
       fill_missing=self.fill_missing,
@@ -116,10 +122,24 @@ def execute(self):
     bbox = Bbox.clamp(self.bounds, vol.bounds)
     index_bbox = Bbox.clamp(self.index_bounds, vol.bounds)
 
-    path = skeldir(self.cloudpath)
-    path = os.path.join(self.cloudpath, path)
+    path = vol.info.get("skeletons", "skeletons")
+    if self.frag_path is None:
+      path = vol.meta.join(self.cloudpath, path)
+    else:
+      # if the path is to a volume root, follow the info instructions,
+      # otherwise place the files exactly where frag path says to
+      test_path = CloudFiles(self.frag_path).join(self.frag_path, "info")
+      test_info = CloudFile(test_path).get_json()
+      if test_info is not None and 'scales' in test_info:
+        path = CloudFiles(self.frag_path).join(self.frag_path, path)
+      else:
+        path = self.frag_path
 
-    all_labels = vol[ bbox.to_slices() ]
+    all_labels = vol.download(
+      bbox.to_slices(), 
+      agglomerate=True, 
+      timestamp=self.timestamp
+    )
     all_labels = all_labels[:,:,:,0]
 
     if self.mask_ids:
@@ -136,6 +156,10 @@ def execute(self):
       dust_threshold = 0
       all_labels = self.apply_global_dust_threshold(vol, all_labels)
 
+    voxel_graph = None
+    if self.fix_autapses:
+      voxel_graph = self.voxel_connectivity_graph(vol, bbox, all_labels)
+
     skeletons = kimimaro.skeletonize(
       all_labels, self.teasar_params, 
       object_ids=self.object_ids, 
@@ -148,6 +172,7 @@ def execute(self):
       fill_holes=self.fill_holes,
       parallel=self.parallel,
       extra_targets_after=extra_targets_after.keys(),
+      voxel_graph=voxel_graph,
     )
     del all_labels
 
@@ -180,17 +205,80 @@ def execute(self):
       return skeletons
 
     if self.sharded:
-      if self.frag_path:
-        self.upload_batch(vol, os.path.join(self.frag_path, skeldir(self.cloudpath)), index_bbox, skeletons)
-      else:
-        self.upload_batch(vol, path, index_bbox, skeletons)
+      self.upload_batch(vol, path, index_bbox, skeletons)
     else:
       self.upload_individuals(vol, path, bbox, skeletons)
 
     if self.spatial_index:
       self.upload_spatial_index(vol, path, index_bbox, skeletons)
-  
+
+  def voxel_connectivity_graph(
+    self, 
+    vol:CloudVolume, 
+    bbox:Bbox, 
+    root_labels:np.ndarray,
+  ) -> np.ndarray:
+
+    if vol.meta.path.format != "graphene":
+      vol = CloudVolume(
+        self.cloudpath, mip=self.mip, 
+        info=self.info, cdn_cache=False,
+        parallel=self.parallel, 
+        fill_missing=self.fill_missing,
+      )
+
+    if vol.meta.path.format != "graphene":
+      raise ValueError("Can't extract a voxel connectivity graph from non-graphene volumes.")
+
+    layer_2 = vol.download(
+      bbox, 
+      stop_layer=2,
+      agglomerate=True,
+      timestamp=self.timestamp,
+    )[...,0]
+
+    graph_chunk_size = np.array(vol.meta.graph_chunk_size) / vol.meta.downsample_ratio(vol.mip)
+    graph_chunk_size = graph_chunk_size.astype(int)
+
+    shape = bbox.size()[:3]
+    sgx, sgy, sgz = list(np.ceil(shape / graph_chunk_size).astype(int))
+
+    vcg = cc3d.voxel_connectivity_graph(layer_2, connectivity=26)
+    del layer_2
+
+    # the proper way to do this would be to get the lowest the L3..LN root
+    # as needed, but the lazy way to do this is to get the root labels
+    # which will retain a few errors, but overall the error rate should be
+    # over 100x less. We need to shade in the sides of the connectivity graph
+    # with edges that represent the connections between the adjacent boxes.
+
+    root_vcg = cc3d.voxel_connectivity_graph(root_labels, connectivity=26)
+    clamp_box = Bbox([0,0,0], shape)
+
+    for gx,gy,gz in xyzrange([sgx, sgy, sgz]):
+      bbx = Bbox((gx,gy,gz), (gx+1, gy+1, gz+1))
+      bbx *= graph_chunk_size
+      bbx = Bbox.clamp(bbx, clamp_box)
+
+      slicearr = []
+      for i in range(3):
+        bbx1 = bbx.clone()
+        bbx1.maxpt[i] = bbx1.minpt[i] + 1
+        slicearr.append(bbx1)
+
+        bbx1 = bbx.clone()
+        bbx1.minpt[i] = bbx1.maxpt[i] - 1
+        slicearr.append(bbx1)
+
+      for bbx1 in slicearr:
+        vcg[bbx1.to_slices()] = root_vcg[bbx1.to_slices()] 
+
+    return vcg
+
   def compute_cross_sectional_area(self, vol, bbox, skeletons):
+    if len(skeletons) == 0:
+      return skeletons
+
     # Why redownload a bigger image? In order to avoid clipping the
     # cross sectional areas on the edges.
     delta = int(self.cross_sectional_area_shape_delta)
@@ -203,9 +291,13 @@ def compute_cross_sectional_area(self, vol, bbox, skeletons):
     huge_bbox.grow(int(np.max(bbox.size()) / 2) + 1)
     huge_bbox = Bbox.clamp(huge_bbox, vol.bounds)
     
-    mem_vol = vol.image.memory_cutout(
-      huge_bbox, mip=vol.mip, 
-      encoding="crackle", compress=False
+    mem_vol = vol.memory_cutout(
+      huge_bbox, 
+      mip=vol.mip, 
+      encoding="crackle",
+      compress=False,
+      agglomerate=True,
+      timestamp=self.timestamp,
     )
 
     all_labels = mem_vol[big_bbox][...,0]
@@ -266,6 +358,11 @@ def reprocess_skel(pts, skel):
       diff = bbox.minpt - skel_bbx.minpt
       skel.vertices += diff * vol.resolution
 
+      # we binarized the label for memory's sake, 
+      # so need to harmonize that with the skeleton ID
+      segid = skel.id
+      skel.id = 1
+
       kimimaro.cross_sectional_area(
         binary_image, skel,
         anisotropy=vol.resolution,
@@ -275,7 +372,7 @@ def reprocess_skel(pts, skel):
         fill_holes=self.fill_holes,
         repair_contacts=True,
       )
-
+      skel.id = segid
       skel.vertices -= diff * vol.resolution
 
     for skel in repair_skels:
diff --git a/igneous_cli/cli.py b/igneous_cli/cli.py
index 4800575..77d1540 100644
--- a/igneous_cli/cli.py
+++ b/igneous_cli/cli.py
@@ -896,7 +896,7 @@ def meshgroup():
 @meshgroup.command("xfer")
 @click.argument("src", type=CloudPath())
 @click.argument("dest", type=CloudPath())
-@click.option('--queue', required=True, help="AWS SQS queue or directory to be used for a task queue. e.g. sqs://my-queue or ./my-queue. See https://github.com/seung-lab/python-task-queue", type=str)
+@click.option('--queue', help="AWS SQS queue or directory to be used for a task queue. e.g. sqs://my-queue or ./my-queue. See https://github.com/seung-lab/python-task-queue", type=str)
 @click.option("--sharded", is_flag=True, default=False, help="Generate shard fragments instead of outputing mesh fragments.", show_default=True)
 @click.option("--dir", "mesh_dir", type=str, default=None, help="Write meshes into this directory instead of the one indicated in the info file.")
 @click.option('--magnitude', default=2, help="Split up the work with 10^(magnitude) prefix based tasks.", show_default=True)
@@ -933,7 +933,7 @@ def mesh_xfer(
 
 @meshgroup.command("forge")
 @click.argument("path", type=CloudPath())
-@click.option('--queue', required=True, help="AWS SQS queue or directory to be used for a task queue. e.g. sqs://my-queue or ./my-queue. See https://github.com/seung-lab/python-task-queue", type=str)
+@click.option('--queue', help="AWS SQS queue or directory to be used for a task queue. e.g. sqs://my-queue or ./my-queue. See https://github.com/seung-lab/python-task-queue", type=str)
 @click.option('--mip', default=0, help="Perform meshing using this level of the image pyramid.", show_default=True)
 @click.option('--shape', type=Tuple3(), default=(448, 448, 448), help="Set the task shape in voxels.", show_default=True)
 @click.option('--simplify/--skip-simplify', is_flag=True, default=True, help="Enable mesh simplification.", show_default=True)
@@ -984,7 +984,7 @@ def mesh_forge(
 
 @meshgroup.command("merge")
 @click.argument("path", type=CloudPath())
-@click.option('--queue', required=True, help="AWS SQS queue or directory to be used for a task queue. e.g. sqs://my-queue or ./my-queue. See https://github.com/seung-lab/python-task-queue", type=str)
+@click.option('--queue', help="AWS SQS queue or directory to be used for a task queue. e.g. sqs://my-queue or ./my-queue. See https://github.com/seung-lab/python-task-queue", type=str)
 @click.option('--magnitude', default=2, help="Split up the work with 10^(magnitude) prefix based tasks. Default: 2 (100 tasks)")
 @click.option('--nlod', default=0, help="(multires) How many extra levels of detail to create.", show_default=True)
 @click.option('--vqb', default=16, help="(multires) Vertex quantization bits for stored model representation. 10 or 16 only.", show_default=True)
@@ -1016,7 +1016,7 @@ def mesh_merge(ctx, path, queue, magnitude, nlod, vqb, dir, min_chunk_size):
 
 @meshgroup.command("merge-sharded")
 @click.argument("path", type=CloudPath())
-@click.option('--queue', required=True, help="AWS SQS queue or directory to be used for a task queue. e.g. sqs://my-queue or ./my-queue. See https://github.com/seung-lab/python-task-queue", type=str)
+@click.option('--queue', help="AWS SQS queue or directory to be used for a task queue. e.g. sqs://my-queue or ./my-queue. See https://github.com/seung-lab/python-task-queue", type=str)
 @click.option('--nlod', default=1, help="Number of levels of detail to create.", type=int, show_default=True)
 @click.option('--vqb', default=16, help="Vertex quantization bits. Can be 10 or 16.", type=int, show_default=True)
 @click.option('--compress-level', default=7, help="Draco compression level.", type=int, show_default=True)
@@ -1065,7 +1065,7 @@ def mesh_sharded_merge(
 
 @meshgroup.command("rm")
 @click.argument("path", type=CloudPath())
-@click.option('--queue', required=True, help="AWS SQS queue or directory to be used for a task queue. e.g. sqs://my-queue or ./my-queue. See https://github.com/seung-lab/python-task-queue", type=str)
+@click.option('--queue', help="AWS SQS queue or directory to be used for a task queue. e.g. sqs://my-queue or ./my-queue. See https://github.com/seung-lab/python-task-queue", type=str)
 @click.option('--magnitude', default=2, help="Split up the work with 10^(magnitude) prefix based tasks. Default: 2 (100 tasks)")
 @click.option('--dir', 'mesh_dir', default=None, help="Target this directory instead of the one indicated in the info file.")
 @click.pass_context
@@ -1114,7 +1114,7 @@ def spatialindexgroup():
 
 @spatialindexgroup.command("create")
 @click.argument("path", type=CloudPath())
-@click.option('--queue', required=True, help="AWS SQS queue or directory to be used for a task queue. e.g. sqs://my-queue or ./my-queue. See https://github.com/seung-lab/python-task-queue", type=str)
+@click.option('--queue', help="AWS SQS queue or directory to be used for a task queue. e.g. sqs://my-queue or ./my-queue. See https://github.com/seung-lab/python-task-queue", type=str)
 @click.option('--shape', default="448,448,448", type=Tuple3(), help="Shape in voxels of each indexing task.", show_default=True)
 @click.option('--mip', default=0, help="Perform indexing using this level of the image pyramid.", show_default=True)
 @click.option('--fill-missing', is_flag=True, default=False, help="Interpret missing image files as background instead of failing.", show_default=True)
@@ -1181,6 +1181,7 @@ def skeletongroup():
 @click.option('--fix-branching', is_flag=True, default=True, help="Trades speed for quality of branching at forks.", show_default=True)
 @click.option('--fix-borders', is_flag=True, default=True, help="Allows trivial merging of single voxel overlap tasks. Only switch off for datasets that fit in a single task.", show_default=True)
 @click.option('--fix-avocados', is_flag=True, default=False, help="Fixes somata where nuclei and cytoplasm have separate segmentations.", show_default=True)
+@click.option('--fix-autapses', is_flag=True, default=False, help="(graphene only) Fixes autapses by using the PyChunkGraph.", show_default=True)
 @click.option('--fill-holes', is_flag=True, default=False, help="Preprocess each cutout to eliminate background holes and holes caused by entirely contained inclusions. Warning: May remove labels that are considered inclusions.", show_default=True)
 @click.option('--dust-threshold', default=1000, help="Skip skeletonizing objects smaller than this number of voxels within a cutout.", type=int, show_default=True)
 @click.option('--dust-global/--dust-local', is_flag=True, default=False, help="Use global voxel counts for the dust threshold (when >0). To use this feature you must first compute the global voxel counts using the 'igneous image voxels' command.", show_default=True)
@@ -1195,14 +1196,17 @@ def skeletongroup():
 @click.option('--sharded', is_flag=True, default=False, help="Generate shard fragments instead of outputing skeleton fragments.", show_default=True)
 @click.option('--labels', type=TupleN(), default=None, help="Skeletonize only this comma separated list of labels.", show_default=True)
 @click.option('--cross-section', type=int, default=0, help="Compute the cross sectional area for each skeleton vertex. May add substantial computation time. Integer value is the normal vector rolling average smoothing window over vertices. 0 means off.", show_default=True)
+@click.option('--output', '-o', type=CloudPath(), default=None, help="Output the results to a different place.", show_default=True)
+@click.option('--timestamp', type=int, default=None, help="(graphene) Use the proofreading state at this UNIX timestamp.", show_default=True)
+@click.option('--root-ids', type=CloudPath(), default=None, help="(graphene) If you have a materialization of graphene root ids for this timepoint, it's more efficient to use it than making requests to the graphene server.", show_default=True)
 @click.pass_context
 def skeleton_forge(
   ctx, path, queue, mip, shape, 
   fill_missing, dust_threshold, dust_global, spatial_index,
-  fix_branching, fix_borders, fix_avocados, 
+  fix_branching, fix_borders, fix_avocados, fix_autapses,
   fill_holes, scale, const, soma_detect, soma_accept,
   soma_scale, soma_const, max_paths, sharded, labels,
-  cross_section,
+  cross_section, output, timestamp, root_ids,
 ):
   """
   (1) Synthesize skeletons from segmentation cutouts.
@@ -1247,6 +1251,8 @@ def skeleton_forge(
     dust_global=dust_global, object_ids=labels,
     cross_sectional_area=(cross_section > 0),
     cross_sectional_area_smoothing_window=int(cross_section),
+    frag_path=output, fix_autapses=fix_autapses,
+    timestamp=timestamp, root_ids_cloudpath=root_ids,
   )
 
   enqueue_tasks(ctx, queue, tasks)
@@ -1283,7 +1289,7 @@ def skeleton_merge(
 
 @skeletongroup.command("merge-sharded")
 @click.argument("path", type=CloudPath())
-@click.option('--queue', required=True, help="AWS SQS queue or directory to be used for a task queue. e.g. sqs://my-queue or ./my-queue. See https://github.com/seung-lab/python-task-queue", type=str)
+@click.option('--queue', help="AWS SQS queue or directory to be used for a task queue. e.g. sqs://my-queue or ./my-queue. See https://github.com/seung-lab/python-task-queue", type=str)
 @click.option('--min-cable-length', default=1000, help="Skip objects smaller than this physical path length.", type=float, show_default=True)
 @click.option('--max-cable-length', default=None, help="Skip objects larger than this physical path length. Default: no limit", type=float)
 @click.option('--tick-threshold', default=0, help="Remove small \"ticks\", or branches from the main skeleton one at a time from smallest to largest. Branches larger than this are preserved. Default: no elimination", type=float)
@@ -1334,7 +1340,7 @@ def skeleton_sharded_merge(
 
 @imagegroup.command("rm")
 @click.argument("path", type=CloudPath())
-@click.option('--queue', required=True, help="AWS SQS queue or directory to be used for a task queue. e.g. sqs://my-queue or ./my-queue. See https://github.com/seung-lab/python-task-queue", type=str)
+@click.option('--queue', help="AWS SQS queue or directory to be used for a task queue. e.g. sqs://my-queue or ./my-queue. See https://github.com/seung-lab/python-task-queue", type=str)
 @click.option('--mip', default=0, help="Which mip level to start deleting from. Default: 0")
 @click.option('--num-mips', default=5, help="The number of mip levels to delete at once. Default: 5")
 @click.option('--shape', default=None, help="The size of each deletion task as a comma delimited list. Must be a multiple of the chunk size.", type=Tuple3())
@@ -1358,7 +1364,7 @@ def delete_images(
 
 @skeletongroup.command("rm")
 @click.argument("path", type=CloudPath())
-@click.option('--queue', required=True, help="AWS SQS queue or directory to be used for a task queue. e.g. sqs://my-queue or ./my-queue. See https://github.com/seung-lab/python-task-queue", type=str)
+@click.option('--queue', help="AWS SQS queue or directory to be used for a task queue. e.g. sqs://my-queue or ./my-queue. See https://github.com/seung-lab/python-task-queue", type=str)
 @click.option('--magnitude', default=2, help="Split up the work with 10^(magnitude) prefix based tasks. Default: 2 (100 tasks)")
 @click.option('--dir', 'skel_dir', default=None, help="Target this directory instead of the one indicated in the info file.")
 @click.pass_context
@@ -1376,7 +1382,7 @@ def skeleton_rm(ctx, path, queue, magnitude, skel_dir):
 @skeletongroup.command("xfer")
 @click.argument("src", type=CloudPath())
 @click.argument("dest", type=CloudPath())
-@click.option('--queue', required=True, help="AWS SQS queue or directory to be used for a task queue. e.g. sqs://my-queue or ./my-queue. See https://github.com/seung-lab/python-task-queue", type=str)
+@click.option('--queue', help="AWS SQS queue or directory to be used for a task queue. e.g. sqs://my-queue or ./my-queue. See https://github.com/seung-lab/python-task-queue", type=str)
 @click.option("--sharded", is_flag=True, default=False, help="Generate shard fragments instead of outputing mesh fragments.", show_default=True)
 @click.option("--dir", "skel_dir", type=str, default=None, help="Write skeletons into this directory instead of the one indicated in the info file.")
 @click.option('--magnitude', default=2, help="Split up the work with 10^(magnitude) prefix based tasks.", show_default=True)
@@ -1440,7 +1446,7 @@ def spatialindexgroupskel():
 
 @spatialindexgroupskel.command("create")
 @click.argument("path", type=CloudPath())
-@click.option('--queue', required=True, help="AWS SQS queue or directory to be used for a task queue. e.g. sqs://my-queue or ./my-queue. See https://github.com/seung-lab/python-task-queue", type=str)
+@click.option('--queue', help="AWS SQS queue or directory to be used for a task queue. e.g. sqs://my-queue or ./my-queue. See https://github.com/seung-lab/python-task-queue", type=str)
 @click.option('--shape', default="512,512,512", type=Tuple3(), help="Shape in voxels of each indexing task.", show_default=True)
 @click.option('--mip', default=0, help="Perform indexing using this level of the image pyramid.", show_default=True)
 @click.option('--fill-missing', is_flag=True, default=False, help="Interpret missing image files as background instead of failing.", show_default=True)