Diagnose and fix common FiftyOne issues automatically. Use when a dataset disappeared, the App won't open, changes aren't saving, MongoDB errors occur, video codecs fail, notebook connectivity breaks, operators are missing, or any recurring FiftyOne pain point needs solving.
Diagnoses and fixes common FiftyOne issues like dataset persistence, App connection failures, and MongoDB errors.
npx claudepluginhub voxel51/fiftyone-skillsThis skill inherits all available tools. When active, it can use any tool Claude has access to.
Diagnose and fix common FiftyOne pain points. Match the user's symptom to the Issue Index, explain the root cause and proposed fix, get approval, then apply.
Shell commands in this skill are written for macOS/Linux. On Windows (non-WSL), adapt using PowerShell equivalents or use WSL.
Designed to grow: add new issues at the bottom as they are encountered.
pip install fiftyoneNEVER run a fix without first:
Wait for explicit user confirmation before executing anything that modifies files, config, or data.
fo.delete_dataset()fo.list_datasets(), fo.load_dataset(), len(dataset), dataset.get_field_schema() — these are safepymongo, db.drop_collection(), or raw MongoDB shell commandsdatabase_uri, database_name, or any config file without showing what will change and getting approval.zshrc, .bash_profile, virtualenv activate) without showing the exact line change and getting explicit user confirmation to applyAny fix that sets an environment variable or modifies a config file only takes effect for new processes. Already-running App servers, service managers, and Python scripts will NOT pick up the change.
FIFTYONE_DATABASE_NAME or similar env vars, identify and restart any running FiftyOne processesps aux | grep fiftyonepkill -f "fiftyone" (confirm with user first)Run the Health Check after every fix to confirm the environment is operational.
Handles connection failures gracefully — always produce useful output:
import sys
print(f"Python: {sys.executable}")
print(f"Version: {sys.version.split()[0]}")
try:
import fiftyone as fo
print(f"FiftyOne: {fo.__version__}")
print(f"Database: {fo.config.database_name}")
print(f"DB URI: {fo.config.database_uri or '(internal MongoDB)'}")
except ImportError:
print("ERROR: fiftyone not installed — check Python environment, if needed run: pip install fiftyone")
sys.exit(1)
try:
print(f"Datasets: {fo.list_datasets()}")
print("Connection: OK")
except Exception as e:
print(f"Connection ERROR: {e}")
print("→ Match this error to the Issue Index below")
Run after any fix to confirm the environment is fully operational.
This script creates and destroys a temporary test dataset (
_fo_health_check). It does not touch any user datasets. Do not manually create a dataset with the name "_fo_health_check".
import fiftyone as fo
import tempfile, os
TEST_NAME = "_fo_health_check"
try:
# Clean up any debris from a previous failed check
if TEST_NAME in fo.list_datasets():
fo.delete_dataset(TEST_NAME)
# Non-persistent: auto-removed if Python exits before cleanup
dataset = fo.Dataset(TEST_NAME, persistent=False)
dataset.add_sample(fo.Sample(
filepath=os.path.join(tempfile.gettempdir(), "health_check.jpg")
))
assert len(dataset) == 1, "Sample write failed"
# Verify connection round-trip
assert TEST_NAME in fo.list_datasets(), "Dataset not listed"
print(f"OK — FiftyOne {fo.__version__} on database '{fo.config.database_name}'")
finally:
# Always clean up, even on failure
if TEST_NAME in fo.list_datasets():
fo.delete_dataset(TEST_NAME)
| Symptom | Section |
|---|---|
| Dataset disappeared after restart | Dataset Persistence |
| App won't open / not connected | App Connection |
| Changes not saved | Unsaved Changes |
| Video not playing / codec error | Video Codec |
| Too many open files (macOS) | Open Files Limit |
| App not loading in notebook / remote | Notebook / Remote |
| Plots not showing in notebook | Notebook Plots |
| MongoDB connection failure | MongoDB |
| Operator not found / plugin missing | Missing Plugin |
| "No executor available" | Delegated Operators |
| Dataset is read-only | Read-Only Dataset |
| Slow performance on large datasets | Performance |
| App showing stale / wrong data | Stale Data |
| Downgrading FiftyOne | Downgrading |
| Database version mismatch | DB Version Mismatch |
| Teams / OSS client type mismatch | Teams vs OSS |
Cause: Datasets are non-persistent by default and are deleted when Python exits.
Fix:
import fiftyone as fo
# Make an existing dataset persistent
dataset = fo.load_dataset("my-dataset")
dataset.persistent = True
# Prevention: always create persistent datasets
dataset = fo.Dataset("my-dataset", persistent=True)
If the dataset is already gone from
fo.list_datasets(), it cannot be recovered through FiftyOne — re-import from source files.
Cause A — Script exits before the App loads. Fix: add session.wait().
session = fo.launch_app(dataset)
session.wait() # keeps the process alive
Cause B — Windows multiprocessing. Fix: add the __main__ guard.
if __name__ == "__main__":
session = fo.launch_app(dataset)
session.wait()
Cause C — Port already in use.
session = fo.launch_app(dataset, port=<alternative-port>) # e.g. 5152, 5153
Cause D — Stale process.
pkill -f "fiftyone"
Fix — sample edits:
sample["my_field"] = "new_value"
sample.save() # required
Fix — dataset-level properties:
dataset.info["description"] = "Updated"
dataset.save() # required
Fix — bulk updates (no .save() needed):
dataset.set_values("my_field", [v1, v2, ...])
Cause: Video codec not supported by the browser's HTML5 player (requires MP4/H.264, WebM, or Ogg).
⚠️ Re-encoding overwrites files on disk. Show the user the exact paths that will be modified and get explicit confirmation before running.
import fiftyone.utils.video as fouv
# Re-encode all videos in a dataset
fouv.reencode_videos(fo.load_dataset("my-dataset"))
# Or a single file
fouv.reencode_video("/path/to/input.avi", "/path/to/output.mp4")
# Temporary (current session only)
ulimit -n 65536
# Permanent — add to your shell profile and reload it
# bash: ~/.bash_profile or ~/.bashrc
# zsh: ~/.zshrc
echo "ulimit -n 65536" >> <your-shell-profile> && source <your-shell-profile>
Cause A — Remote Jupyter: localhost URL not reachable from browser.
fo.app_config.proxy_url = "http://your-server:<app-port>/proxy/<app-port>"
session = fo.launch_app(dataset)
Cause B — Google Colab / Databricks: works out of the box, no proxy needed.
Cause C — SSH remote: forward the port locally.
# Use the same port FiftyOne is listening on (default: 5151)
ssh -L <app-port>:localhost:<app-port> user@remote-server
pip install plotly
jupyter labextension install jupyterlab-plotly
import plotly.offline as pyo
pyo.init_notebook_mode(connected=True)
Symptoms: ConnectionFailure, ServerSelectionTimeoutError, hangs on import, port 27017 errors.
Diagnose:
ps aux | grep mongod # is MongoDB running?
df -h # is disk full?
Fix A — Restart FiftyOne's MongoDB:
pkill -f "fiftyone.*mongod" # kill stale process, then re-import fiftyone
Fix B — Free disk space. MongoDB will not start on a full disk.
Fix C — Use an external MongoDB instance (requires user confirmation):
// ~/.fiftyone/config.json
{ "database_uri": "mongodb://localhost:27017" }
Fix D — Reset internal MongoDB (last resort, destroys all datasets):
⚠️ Requires explicit user confirmation.
ls -la ~/.fiftyone/ # show what will be deleted
rm -rf ~/.fiftyone/var/ # only after user confirms
Diagnose:
fo.list_plugins()
# Via MCP:
list_plugins(enabled=True)
list_operators(builtin_only=False)
Fix:
fo.download_plugin("voxel51/fiftyone-plugins", plugin_names=["@voxel51/brain"])
fo.enable_plugin("@voxel51/brain")
# Via MCP:
download_plugin(url_or_repo="voxel51/fiftyone-plugins", plugin_names=["@voxel51/brain"])
enable_plugin(plugin_name="@voxel51/brain")
| Operator prefix | Plugin |
|---|---|
@voxel51/brain/* | @voxel51/brain |
@voxel51/io/* | @voxel51/io |
@voxel51/utils/* | @voxel51/utils |
@voxel51/evaluation/* | @voxel51/evaluation |
@voxel51/zoo/* | @voxel51/zoo |
Cause: Brain, evaluation, and annotation operators require the FiftyOne App running as executor.
launch_app() # 1. launch app first
# wait 5-10 seconds
execute_operator(...) # 2. then run the operator
writable = fo.load_dataset("read-only-dataset").clone("my-writable-dataset")
writable.persistent = True
# Use views, not full dataset iteration
view = dataset.match({"label": "cat"}).take(1000)
# Bulk updates over per-sample saves
dataset.set_values("my_score", values_list) # fast
# vs: sample["my_score"] = v; sample.save() # slow
# Add indexes for frequently filtered fields
dataset.create_index("ground_truth.detections.label")
dataset.reload()
# or
session.dataset = fo.load_dataset("my-dataset")
session.refresh()
Browser: Cmd+Shift+R (macOS) / Ctrl+Shift+R (Windows/Linux).
pip install fiftyone==X.Y.Z
python -c "import fiftyone as fo; fo.migrate_database_if_necessary()"
⚠️ Export important datasets before downgrading.
Symptom:
OSError: You must have fiftyone>=X.Y.Z to migrate from vX.Y.Z to vA.B.C
Cause: All FiftyOne installs on a machine share the same MongoDB database (fiftyone by default). A newer version writes a forward-only version marker that older installs cannot read. Common when a dev virtualenv runs an older version than the system pip install.
Diagnose:
# Current env
python -c "import fiftyone as fo; print(fo.__version__, fo.config.database_name)"
# Check if the database is accessible at all
python -c "
import fiftyone as fo
try:
print('datasets:', fo.list_datasets())
except Exception as e:
print('inaccessible:', e)
"
# All Python installs on this machine
which -a python python3 | xargs -I{} sh -c '{} -c "import fiftyone as fo; print(\"{}: \", fo.__version__)" 2>/dev/null'
Fix A — Isolate the environment (recommended, no data loss):
Give the affected env its own database so it never conflicts with other installs.
# Find the virtualenv activate script
ACTIVATE=$(python -c "import sys; print(sys.prefix)")/bin/activate
echo $ACTIVATE # confirm before editing
# Append isolation — pick a name that reflects your project
echo '
# Isolate FiftyOne database from other installations
export FIFTYONE_DATABASE_NAME=fiftyone-<your-project>' >> $ACTIVATE
source $ACTIVATE
python -c "import fiftyone as fo; print(fo.config.database_name)"
Then run the Health Check.
⚠️ After applying this fix, restart any running FiftyOne App or Python processes — env var changes only affect new processes. Check for stale processes:
ps aux | grep fiftyone. Confirm with user before killing them.
Fix B — Per-session (no file changes):
FIFTYONE_DATABASE_NAME=fiftyone-<your-project> python your_script.py
Fix C — Upgrade to match the database version:
pip install "fiftyone>=X.Y.Z"
Fix D — Global config (affects all installs, confirm with user):
// ~/.fiftyone/config.json
{ "database_name": "fiftyone-<your-project>" }
Symptom:
ConnectionError: Cannot connect to database type 'fiftyone' with client type 'fiftyone-teams'
(or the inverse)
Cause: Teams and OSS clients use incompatible database types and cannot share a database.
Diagnose:
import fiftyone as fo
print(fo.__version__)
print(fo.config.database_name)
print(fo.config.database_uri or "(internal MongoDB)")
try:
fo.list_datasets()
except Exception as e:
print(e)
Fix — Isolate the OSS environment:
ACTIVATE=$(python -c "import sys; print(sys.prefix)")/bin/activate
echo $ACTIVATE # confirm before editing
echo '
# Isolate FiftyOne database from Teams installation
export FIFTYONE_DATABASE_NAME=fiftyone-<your-project>' >> $ACTIVATE
source $ACTIVATE
Fix — Inspect Teams config if the error is unexpected:
cat ~/.fiftyone/config.json 2>/dev/null || echo "(no config)"
python -c "import fiftyone as fo; import json; print(json.dumps(fo.config.serialize(), indent=2))"
## Issue: <Name> section with: Symptom → Cause → FixActivates when the user asks about AI prompts, needs prompt templates, wants to search for prompts, or mentions prompts.chat. Use for discovering, retrieving, and improving prompts.
Search, retrieve, and install Agent Skills from the prompts.chat registry using MCP tools. Use when the user asks to find skills, browse skill catalogs, install a skill for Claude, or extend Claude's capabilities with reusable AI agent components.
This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.