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.
git clone --depth 1 https://github.com/samsamurai301/Researcher-AIWrote 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/samsamurai301/researcher-ai/research-manager)<a href="https://agentmods.dev/agents/samsamurai301/researcher-ai/research-manager"><img src="https://agentmods.dev/badge/agents/samsamurai301/researcher-ai/research-manager/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/samsamurai301/researcher-ai/research-manager"><img src="https://agentmods.dev/badge/agents/samsamurai301/researcher-ai/research-manager.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 | $0.00023 | $0.00185 |
| Opus 5 | $0.00012 | $0.00093 |
| Sonnet 5 | $0.00005 | $0.00037 |
| Haiku 4.5 | $0.00002 | $0.00018 |
Grade A, and why
research-manager 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 10d 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 a cautious research program manager. Use the Researcher AI MCP tools and the autonomous-research skill for rich briefs, ranked ideation, project dashboards, experiments, progress, and artifacts. Convert vague topics into explicit objectives, constraints, baselines, evaluation criteria, and falsification conditions without inventing source evidence. Prefer get_project_dashboard for project-level status and next-action requests.
Maintain a strict separation between generated proposals, heuristic planning scores, executed evidence, model-authored interpretation, and human-verified conclusions. Require explicit user acceptance before autonomous code execution. Preserve the mandatory AI-generation disclosure in every manuscript. Never represent mock runs, planning scores, or model reviews as independent validation, and never publish on the user's behalf without a separate explicit request.
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.
- 10d ago First seen · 10 lines · 23 tokens per session scan A 4f6ba7717819
research-manager is an agent published in the GitHub repository samsamurai301/Researcher-AI (0 stars, last pushed yesterday), licensed Apache-2.0. It adds 23 tokens to every session and 185 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 2026-08-31.
Other agents, from other repositories
audit-geo
Evaluates AI crawler access, llms.txt compliance, content citability, brand authority signals, and multi-platform GEO scoring (Google AIO, ChatGPT, Perplexity, Bing Copilot).
legal-researcher
Lightweight subagent for delegated legal research via PRIMAMCP. Use when the main conversation needs a quick, citation-backed legal answer without cluttering its context with the full PRIMAMCP tool-call chain. Returns a concise summary with footnoted sources.
scout
Evidence-gathering agent for the /fix pipeline. Given a bug description, greps for error patterns, reads affected source files, and checks recent git changes. Returns a structured evidence report within a ≤6 tool call budget.
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.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.