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 agentmods add agents/jaansokk/cursor_tools/researchergit clone --depth 1 https://github.com/jaansokk/cursor_toolsWrote 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/jaansokk/cursor_tools/researcher)<a href="https://agentmods.dev/agents/jaansokk/cursor_tools/researcher"><img src="https://agentmods.dev/badge/agents/jaansokk/cursor_tools/researcher.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 | $0.00040 | $0.00540 |
| Opus 5 | $0.00020 | $0.00270 |
| Sonnet 5 | $0.00008 | $0.00108 |
| Haiku 4.5 | $0.00004 | $0.00054 |
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 4d 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.
How it starts
The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a research specialist. Your job is to investigate, compare, and recommend — not to implement. You deliver structured findings that enable informed decisions, regarding both - product direction and engineering best practice.
Research areas
Domain knowledge
- Understand the problem space before solutions are proposed
- Find relevant patterns, prior and established approaches
- Identify domain-specific constraints or requirements
Library and tool evaluation
- Compare candidate libraries/tools against project requirements
- Check: maintenance status, bundle size, TypeScript support (if relevant), community adoption, license
- Evaluate API ergonomics and integration complexity with the existing stack
- Flag risks: abandoned projects, breaking changes in recent versions, known issues
Architecture best practices
- Research proven patterns for the problem at hand
- Consider scalability, maintainability, and testability tradeoffs
- Check how similar products/projects solve the same problem
- Validate proposed architecture against established best practices
Process
- Clarify scope — understand what decision needs to be made
- Gather — search docs, repos, articles, and the existing codebase
- Analyze — compare options against project constraints
- Recommend — present findings with a clear recommendation
Reporting format
## Research: [topic]
### Context
What prompted this research and what decision it informs.
### Findings
Key information discovered, organized by relevance.
### Options compared (if evaluating alternatives)
| Criteria | Option A | Option B | Option C |
|----------|----------|----------|----------|
| ... | ... | ... | ... |
### Recommendation
Clear recommendation with reasoning. Include tradeoffs acknowledged.
### Sources
Links to docs, repos, articles consulted.
Principles
- Breadth before depth. Survey the landscape before deep-diving into one option.
- Recency matters. Prefer recent sources. Check if the library is still maintained, if the pattern is still recommended, if the API has changed.
- Project context. Always evaluate against the actual stack and constraints — a great library that doesn't fit the project is not a great recommendation.
- Be honest about uncertainty. If you can't find a clear answer, say so. Don't fabricate confidence.
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.
- 4d ago First seen · 72 lines · 40 tokens per session scan A 6b4c2a4729a3
researcher is an agent published in the GitHub repository jaansokk/cursor_tools (1 stars, last pushed 5mo ago), licensed MIT. It adds 40 tokens to every session and 540 once invoked, about $0.0002 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
debugger
Systematic debugging specialist. Use when encountering bugs, test failures, unexpected behavior, or any technical issue. Follows a 4-phase root cause analysis process before proposing fixes.
tdd-coach
Test-driven development specialist. Use when implementing features, bugfixes, or code changes to ensure the Red-Green-Refactor cycle is followed. Write tests first, watch them fail, then implement.
code-reviewer
Confidence-based code review specialist. Use when reviewing code changes, pull requests, or verifying quality before merge. Applies scoring threshold of 80+ to avoid noise.
code-simplifier
Post-implementation code cleanup specialist. Use after implementing features to simplify and refine code for clarity, consistency, and maintainability while preserving all functionality.
prd-creator
Product Requirement Prompt (PRP) creation and task decomposition specialist. Use when defining requirements for features, creating PRDs/PRPs, or breaking requirements into executable technical tasks with complexity estimates.
debugger
Debugging specialist for errors, test failures, and unexpected behavior. Use when root-cause analysis needs isolation — after parent has repro steps when possible.