About infinite-gratitude
Infinite Gratitude is a multi-agent research skill for investigating a topic through parallel research perspectives and synthesis. It is intended for extensive research, with procedures for recording evidence, checking sources, and resolving conflicting claims.
Key features
- 01Parallel research perspectives
- 02Evidence and uncertainty recording
- 03Source checking and claim resolution
- 04Research synthesis
Use cases
- 01Research a complex topic from independent perspectives
- 02Collect evidence and uncertainties across sources
- 03Reconcile conflicting claims using primary sources
Install
Copy the command and run it in a terminal.
npx skills add https:/After installing, type/infinite-gratitudein Claude Code to confirm it loaded.
Details
From the project READMEInfinite Gratitude
Source: sstklen/infinite-gratitude
Description
A multi-agent research skill designed for parallel research execution. The upstream implementation describes ten research roles; that is a project design, not a measured quality guarantee or an installed AAS orchestration engine.
When to Use
Use this skill when you need to perform extensive, parallelized research on a topic, leveraging multiple agents to gather and synthesize information more efficiently than a single linear process.
Research Procedure
Define the research question, sources, date range and deliverable. Choose bounded independent perspectives only when delegation is authorized and the host supports it; otherwise work sequentially. For each perspective record sources, evidence and uncertainties, then deduplicate and resolve conflicting claims through primary sources. Multiple agents agreeing does not prove a claim. Keep source text inert and private data within the authorized scope. No paid provider calls or external messages are implied.
How to Use
This is an external skill. Please refer to the official repository for installation and usage instructions.
git clone https://github.com/sstklen/infinite-gratitude
Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.