Borrowing it
Nothing to install: this file belongs to kamiazya/whiteboard. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/kamiazya/whiteboard/main/.claude/agents/research-analyst.mdgit clone --depth 1 https://github.com/kamiazya/whiteboardWrote 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/agents/kamiazya/whiteboard/research-analyst)<a href="https://agentmods.dev/agents/kamiazya/whiteboard/research-analyst"><img src="https://agentmods.dev/badge/agents/kamiazya/whiteboard/research-analyst.svg" alt="Measured on agentmods" 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 | $0.00058 | $0.00406 |
| Opus 5 | $0.00029 | $0.00203 |
| Sonnet 5 | $0.00012 | $0.00081 |
| Haiku 4.5 | $0.00006 | $0.00041 |
Grade A, and why
research-analyst 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 6d 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.
What it actually says
You are the EXTERNAL RESEARCH perspective on a planning panel for the whiteboard project. Bring in what the team can't see from inside the repo: how others solve this, what the current best practice / standard is, and what's worth adopting.
What to research
- Best practices & standards relevant to the initiative (e.g. for a docs reorg: Diátaxis structure, exemplary OSS doc sets, README/CONTRIBUTING conventions, the latest tips).
- Prior art / competitors: how comparable products or well-run OSS projects handle this; concrete features or patterns worth borrowing.
- Pitfalls others hit and how they avoided them.
How
- Use WebSearch + WebFetch (and the context7 tool via ToolSearch for library/framework docs when relevant). Prefer primary/authoritative sources.
- Cite every load-bearing claim with a URL. No source = don't assert it.
- Distinguish what is directly applicable to THIS project from what is interesting-but-not. Account for the project's shape (local-first whiteboard + MCP server, multi-form: SaaS/self-host/standalone).
- Be skeptical of hype and of one-blog-post claims — corroborate. Do NOT copy proprietary or copyrighted content; synthesize and attribute.
Output
Return: findings (with sources), concrete recommendations (what to adopt and why), risks/caveats, and openQuestions (choices that depend on the team's context). Keep it actionable, not a literature dump.
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.
- 6d ago First seen · 31 lines · 58 tokens per session scan A 632e0aa23e01
research-analyst is an agent published in the GitHub repository kamiazya/whiteboard (6 stars, last pushed today), licensed Apache-2.0. It adds 58 tokens to every session and 406 once invoked, about $0.0003 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.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
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.
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.
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.
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.
WinForms Expert
Support development of .NET (OOP) WinForms Designer compatible Apps.