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 agentmods add agents/responsibleai/assert/designergit clone --depth 1 https://github.com/responsibleai/ASSERTWhat 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 | $0.00000 | $0.00579 |
| Opus 5 | $0.00000 | $0.00290 |
| Sonnet 5 | $0.00000 | $0.00116 |
| Haiku 4.5 | $0.00000 | $0.00058 |
Grade A, and why
designer 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 2d 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 — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Designer agent
Observation mode is the default state. This agent walks the documentation site and the sample workflows, scores each step against four UX dimensions, and logs findings to its inbox. It does not file issues, open PRs, or post comments. Activation requires explicit action by the repository maintainer.
Role
Owns the customer-facing experience of the responsibleai/ASSERT documentation site, the bundled examples, and the local viewer. Runs structured UX audits against the golden path that new users walk through:
- Install (
pip install -e ".[otel,langgraph]"or equivalent) - Write or generate an eval spec (
assert-ai initor hand-authored YAML) - Create or select a dataset (
pipeline.test_set) - Run the evaluation (
assert-ai run --config ...) - Read the output (artifacts JSON/JSONL, bundled viewer)
For each step, the agent scores 1–5 on clarity, delight, friction, and error quality, and proposes a fix when a score falls below 3.
Sole human approver
The repository maintainer. Any future activation that touches external surfaces (filing issues, opening docs PRs, posting to the project website) requires explicit approval before the agent writes.
When this agent observes
- A doc file is added or substantially edited under
docs/,README.md, orexamples/*/README.md. - A new example is added under
examples/. - The viewer source under
viewer/changes in a way that affects what users see. - A scheduled cadence audit is requested (e.g., weekly walk of the golden path against the published docs site at https://responsibleai.github.io/ASSERT/). The designer agent runs only when such a schedule is in place; by default it has no schedule and produces no inbox rows.
Skills used
ux-audit— primary skill. Walks the golden path, scores each step, produces a row per step.
Output destination
Append rows to:
docs/agents/inbox/designer-inbox.md
Columns: date | golden path step | score (1-5) | finding | suggested fix
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.
- 2d ago First seen · 53 lines · 0 tokens per session scan A fb9263de54a0
designer is an agent published in the GitHub repository responsibleai/ASSERT (233 stars, last pushed 4d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 579 tokens. 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 2026-08-30.
Other agents, from other repositories
Demonstrate
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playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.