Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add beyarkay/claude-skills --skill wandb-reportgit clone --depth 1 https://github.com/beyarkay/claude-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/beyarkay/claude-skills/wandb-report)<a href="https://agentmods.dev/skills/beyarkay/claude-skills/wandb-report"><img src="https://agentmods.dev/badge/skills/beyarkay/claude-skills/wandb-report/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/beyarkay/claude-skills/wandb-report"><img src="https://agentmods.dev/badge/skills/beyarkay/claude-skills/wandb-report.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00037 | $0.01407 |
| Opus 5 | $0.00018 | $0.00704 |
| Sonnet 5 | $0.00007 | $0.00281 |
| Haiku 4.5 | $0.00004 | $0.00141 |
Grade A, and why
wandb-report scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 230 lines — stays where its author put it; the contents beside it link to each section on GitHub.
W&B Report Generator
Create Weights & Biases reports for weekly mentor reviews and experiment updates.
Workflow
Follow these 3 phases in order. Never skip the outline phase.
Phase 1: Gather Context
Before drafting anything, gather this information:
-
Project/Entity: Ask or detect from context/environment
- Check for
WANDB_API_KEYin environment or.env - Look for wandb config in the project
- Check for
-
Runs to Include: Ask what experiments/runs to include
- Examples: "last 4 runs", specific run names, runs matching a pattern
- Query wandb API to get available run names and metrics
-
Story to Tell: Ask what the report should communicate
- What's the main finding or comparison?
- Example: "FooIntervention works better than BarIntervention"
Phase 2: Draft Outline (CRITICAL)
ALWAYS draft a markdown outline BEFORE writing any code.
Present the outline for user critique. Include [bracketed descriptions] of where plots will go.
Outline Template
# Report: [Title]
## Key Finding
- Main takeaway: [one sentence summary]
- [CalloutBlock: "quote the key result here"]
## Setup
- Brief bullet points describing what was compared
- [No plot - just text]
## Training Curves
- Show how loss evolved over training
- [Full-width LinePlot: train/loss for all runs, x=Step, y=Loss]
## Results Comparison
- Compare final metrics across runs
- [Half-width LinePlot: eval/metric_A] [Half-width LinePlot: eval/metric_B]
## Conclusion
- Brief interpretation
- Next steps (if any)
Wait for user approval. Iterate on the outline until the user is satisfied with:
- The story structure
- What plots are included
- Chart layouts (full-width vs side-by-side)
Phase 3: Create Report
Only after outline approval:
- Generate Python code using
wandb_workspacesAPI - Execute the code to create the actual report
- Return the report URL to the user
Layout Rules
| Layout | Width | Use Case |
|---|---|---|
| Full-width | w=24 |
Default for all charts |
| Half-width | w=12 |
Side-by-side comparisons only |
| Never use | w<12 |
Too small to read |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 230 lines · 37 tokens per session scan A 83aed4745432
wandb-report is a skill published in the GitHub repository beyarkay/claude-skills (2 stars, last pushed 1mo ago), licensed MIT. It adds 37 tokens to every session and 1,407 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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