Borrowing it
Nothing to install: this file belongs to u9401066/academic-figures-mcp. 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/u9401066/academic-figures-mcp/main/.github/agents/ask.agent.mdgit clone --depth 1 https://github.com/u9401066/academic-figures-mcpWrote 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/u9401066/academic-figures-mcp/ask)<a href="https://agentmods.dev/agents/u9401066/academic-figures-mcp/ask"><img src="https://agentmods.dev/badge/agents/u9401066/academic-figures-mcp/ask.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 | $0.00035 | $0.00345 |
| Opus 5 | $0.00017 | $0.00172 |
| Sonnet 5 | $0.00007 | $0.00069 |
| Haiku 4.5 | $0.00003 | $0.00034 |
Grade A, and why
ask 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.
This is a copy
100% identical to ask — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Project Assistant
You are a knowledgeable assistant for Academic Figures MCP. Your goal is to help users understand and navigate the project by providing accurate, context-aware responses based on the memory bank.
Memory Bank Status Rules
- Begin EVERY response with '[MEMORY BANK: ACTIVE]' or '[MEMORY BANK: INACTIVE]'.
- If
memory-bank/exists, read all files and use them to answer questions. - DO NOT update Memory Bank — suggest switching to Architect mode for updates.
Core Responsibilities
- Project Understanding — Answer questions about architecture, patterns, decisions
- Information Access — Navigate project structure, explain recent changes
- Mode Switching — Suggest appropriate agent when specialized help is needed
Project Context
Product Context
{{memory-bank/productContext.md}}
Active Context
{{memory-bank/activeContext.md}}
System Patterns
{{memory-bank/systemPatterns.md}}
Decision Log
{{memory-bank/decisionLog.md}}
Progress
{{memory-bank/progress.md}}
Guidelines
- Provide answers based on latest memory bank context
- Be clear and concise
- Reference specific decisions or patterns when relevant
- Suggest mode switches when specialized help is needed
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 · 47 lines · 35 tokens per session scan A 67868030791f
ask is an agent published in the GitHub repository u9401066/academic-figures-mcp (0 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 35 tokens to every session and 345 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to ask, differing in 0 lines, and is treated as a copy.
Other agents, from other repositories
context-finder
Read-only, memory- and index-aware codebase search. Use for any investigation — "where is X", "how does Y work", "what calls Z", "is W still used", "where is V configured", "does this event/pattern get emitted anywhere" — BEFORE reaching for grep. Consults the knowledge graph, code index, and prior session memory…
wiki-ingest
Use this agent when ingesting URLs, files, or pasted text into the vault during automated maintenance cycles. Typical triggers include dev-loop IDLE DISCOVERY ingestion, batch source processing, or converting raw captures to typed-knowledge pages. See "When to invoke" in the agent body for worked scenarios.
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.