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 skills add MuduiClaw/ClawKing --skill gpt-researchergit clone --depth 1 https://github.com/MuduiClaw/ClawKingWrote 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/skills/muduiclaw/clawking/gpt-researcher)<a href="https://agentmods.dev/skills/muduiclaw/clawking/gpt-researcher"><img src="https://agentmods.dev/badge/skills/muduiclaw/clawking/gpt-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/skills/muduiclaw/clawking/gpt-researcher"><img src="https://agentmods.dev/badge/skills/muduiclaw/clawking/gpt-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 | $0.00079 | $0.01780 |
| Opus 5 | $0.00039 | $0.00890 |
| Sonnet 5 | $0.00016 | $0.00356 |
| Haiku 4.5 | $0.00008 | $0.00178 |
Grade A, and why
gpt-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 11d 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
95% identical to gpt-researcher — 1 line 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.
How it starts
The opening of the file, as written. The whole thing — 228 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GPT Researcher Development Skill
GPT Researcher is an LLM-based autonomous agent using a planner-executor-publisher pattern with parallelized agent work for speed and reliability.
Quick Start
Basic Python Usage
from gpt_researcher import GPTResearcher
import asyncio
async def main():
researcher = GPTResearcher(
query="What are the latest AI developments?",
report_type="research_report", # or detailed_report, deep, outline_report
report_source="web", # or local, hybrid
)
await researcher.conduct_research()
report = await researcher.write_report()
print(report)
asyncio.run(main())
Run Servers
# Backend
python -m uvicorn backend.server.server:app --reload --port 8000
# Frontend
cd frontend/nextjs && npm install && npm run dev
Key File Locations
| Need | Primary File | Key Classes |
|---|---|---|
| Main orchestrator | gpt_researcher/agent.py |
GPTResearcher |
| Research logic | gpt_researcher/skills/researcher.py |
ResearchConductor |
| Report writing | gpt_researcher/skills/writer.py |
ReportGenerator |
| All prompts | gpt_researcher/prompts.py |
PromptFamily |
| Configuration | gpt_researcher/config/config.py |
Config |
| Config defaults | gpt_researcher/config/variables/default.py |
DEFAULT_CONFIG |
| API server | backend/server/app.py |
FastAPI app |
| Search engines | gpt_researcher/retrievers/ |
Various retrievers |
Architecture Overview
User Query → GPTResearcher.__init__()
│
▼
choose_agent() → (agent_type, role_prompt)
│
▼
ResearchConductor.conduct_research()
├── plan_research() → sub_queries
├── For each sub_query:
│ └── _process_sub_query() → context
└── Aggregate contexts
│
▼
[Optional] ImageGenerator.plan_and_generate_images()
│
▼
ReportGenerator.write_report() → Markdown report
What ships with it
12 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/adding-features.md 11 KB
- references/advanced-patterns.md 3.0 KB
- references/api-reference.md 5.7 KB
- references/architecture.md 12 KB
- references/components.md 6.5 KB
- references/config-reference.md 3.1 KB
- references/deep-research.md 2.2 KB
- references/flows.md 13 KB
- references/mcp.md 2.4 KB
- references/multi-agents.md 1.8 KB
- references/prompts.md 3.6 KB
- references/retrievers.md 2.9 KB
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.
- 11d ago First seen · 228 lines · 79 tokens per session scan A e371d541acd6
gpt-researcher is a skill published in the GitHub repository MuduiClaw/ClawKing (11 stars, last pushed 4mo ago), licensed MIT. It adds 79 tokens to every session and 1,780 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to gpt-researcher, differing in 1 line, and is treated as a copy.
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