tensorboard SKILL.md skillA
tensorboard from orchestra-research/ai-research-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add orchestra-research/ai-research-skills/tensorboard@v1.0.0Pins v1.0.0 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- orchestra-research/ai-research-skills
- Path
13-mlops/tensorboard/SKILL.md- Versions recorded
- 5
- Latest version
- v1.0.0, committed Nov 20, 2025
- First version recorded
- Nov 16, 2025
- Size
- 15,276 bytes
- Repository stars
- 13,718
- License
- MIT
Visualize training metrics, debug models with histograms, compare experiments, visualize model graphs, and profile performance with TensorBoard - Google's ML visualization toolkit.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# TensorBoard: Visualization Toolkit for ML
## When to Use This Skill
Use TensorBoard when you need to:
- **Visualize training metrics** like loss and accuracy over time
- **Debug models** with histograms and distributions
- **Compare experiments** across multiple runs
- **Visualize model graphs** and architecture
- **Project embeddings** to lower dimensions (t-SNE, PCA)
- **Track hyperparameter** experiments
- **Profile performance** and identify bottlenecks
- **Visualize images and text** during training
**Users**: 20M+ downloads/year | **GitHub Stars**: 27k+ | **License**: Apache 2.0
## Installation
```bash
# Install TensorBoard
pip install tensorboard
# PyTorch integration
pip install torch torchvision tensorboard
# TensorFlow integration (TensorBoard included)
pip install tensorflow
# Launch TensorBoard
tensorboard --logdir=runs
# Access at http://localhost:6006
```
## Quick Start
### PyTorch
```python
from torch.utils.tensorboard import SummaryWriter
# Create writer
writer = SummaryWriter('runs/experiment_1')
# Training loop
for epoch in range(10):
train_loss = train_epoch()
val_acc = validate()
# Log metrics
…Read the whole file at its exact version.
How to install
mdr add orchestra-research/ai-research-skills/tensorboard@sha256:717c4b05f88bbc88The line at the top of this page pins the label v1.0.0, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_b5ghmu5pse6pkz3j)
1 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 5 versions of this file, between Nov 16, 2025 and Nov 20, 2025, about one every day. Its first recorded version is graded C and its latest A.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| v1.0.0 latest | 2025-11-20 | 0a9ded4 | 15,276 B | A | view · diff |
| v1.0.0 | 2025-11-20 | 51fc3a3 | 15,289 B | A | view · diff |
| v1.0.0 | 2025-11-20 | 81c38fe | 15,288 B | A | view · diff |
| v1.0.0 | 2025-11-19 | bd4461f | 15,287 B | A | view · diff |
| git:20251116.d38cd91 | 2025-11-16 | d38cd91 | 14,810 B | C | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (15276 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
orchestra-research/ai-research-skills · 13,718 stars · license MIT · pushed 2026-10-11 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_b5ghmu5pse6pkz3j GET https://markdownregistry.com/api/v1/resolve?ref=orchestra-research/ai-research-skills/tensorboard GET https://markdownregistry.com/api/v1/blob/717c4b05f88bbc888d54cc51fa390ae225d687b3b86fb616e36cc7fc26108020
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.