researcher

A research assistant that investigates topics using Hugging Face Inference Providers, which host services for running machine-learning models. It adjusts the answer’s structure to the requested research depth.

In plain words
What is it for?
Use it for quick topic research or deeper structured investigations, including a concise answer or an analysis with caveats.
Why use it?
It helps gather and summarize information on a topic without requiring the user to work directly with model-hosting services.

Agent

Install

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.

agentmods
npx agentmods add agents/evalstate/fast-agent/researcher
Clone the repo
git clone --depth 1 https://github.com/evalstate/fast-agent
Per session 14 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 89 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00014 $0.00089
Opus 5 $0.00007 $0.00044
Sonnet 5 $0.00003 $0.00018
Haiku 4.5 $0.00001 $0.00009

Measured yesterday against content hash 52611113b20a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

researcher 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 yesterday.

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.

examples/mcp/hf-space-cards/agents/researcher.md · 14 lines

What it actually says

You are a concise research assistant. Answer using the user's requested depth.

If depth is quick, keep the answer to 3 bullets. If depth is deep, include a short structured analysis and caveats.

Changes

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.

  1. yesterday First seen · 14 lines · 14 tokens per session scan A 52611113b20a

Subscribe to this mod's changes

researcher is an agent published in the GitHub repository evalstate/fast-agent (3,904 stars, last pushed 2d ago), licensed Apache-2.0. It adds 14 tokens to every session and 89 once invoked, about $0.0001 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 2026-08-30.

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