Borrowing it
Nothing to install: this file belongs to tusharagg1/aifolimizer. 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/tusharagg1/aifolimizer/master/.claude/agents/researcher.mdgit clone --depth 1 https://github.com/tusharagg1/aifolimizerWrote 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/tusharagg1/aifolimizer/researcher)<a href="https://agentmods.dev/agents/tusharagg1/aifolimizer/researcher"><img src="https://agentmods.dev/badge/agents/tusharagg1/aifolimizer/researcher/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/agents/tusharagg1/aifolimizer/researcher"><img src="https://agentmods.dev/badge/agents/tusharagg1/aifolimizer/researcher.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 | $0.00051 | $0.00250 |
| Opus 5 | $0.00026 | $0.00125 |
| Sonnet 5 | $0.00010 | $0.00050 |
| Haiku 4.5 | $0.00005 | $0.00025 |
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 8d 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
researcher - Market Data + News Fetch Subagent
Use to gather market data, news, sentiment for portfolio tickers.
Context to provide
- Ticker symbols (PII-free)
- Data type needed: price history, news, fundamentals, macro indicators
Responsibilities
- Fetch from yfinance for price/fundamentals
- Search recent news (last 7 days) per ticker
- Fetch macro data (rates, inflation, GDP) from FRED or similar
- Return structured data ready to inject into analysis prompts
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.
- 8d ago First seen · 21 lines · 51 tokens per session scan A ce1991f95d1f
researcher is an agent published in the GitHub repository tusharagg1/aifolimizer (2 stars, last pushed 7d ago), licensed MIT. It adds 51 tokens to every session and 250 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
data-researcher
Data research agent. Finds, downloads, and prepares public reference datasets to enrich user data. Use when analysis needs external context like benchmarks, demographics, economic indicators, or geographic boundaries.
data-scientist
Senior data scientist agent. Designs and orchestrates multi-step analytical pipelines by composing tools across domains. Use when the analysis requires chaining multiple techniques or when the best approach is unclear.
operations-analyst
Operations and process analysis agent. Handles statistical process control, optimization, capacity planning, and efficiency analysis. Use when analyzing operational performance, quality control, or resource allocation.
bi-analyst
Business intelligence agent. Handles A/B testing, cohort analysis, CLV, attribution, and funnel analysis. Translates statistical results into business recommendations. Use for business metric analysis and experiment evaluation.
forecaster
Time series forecasting agent. Handles decomposition, stationarity testing, ARIMA/ETS model choice, and uncertainty quantification. Use when predicting future values from historical data.
graph-data-analyst
Graph data and network analysis agent. Explores graph structures, computes centrality, detects communities, finds paths, and exports visualizations. Use when working with network, dependency, or relationship data.