How do I install the Think Research Framework skill?

Run npx skillmds@latest add product-on-purpose/think-research-framework in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Think Research Framework safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Think Research Framework?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Think Research Framework free to use?

Yes. Installing skills from SkillMD is free. This skill is licensed under Apache-2.

Who published Think Research Framework?

product-on-purpose (@product-on-purpose) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Think Research Framework by product-on-purpose

Name: Think Research Framework
Author: product-on-purpose

Think Research Framework

Researches a thinking framework end to end and produces a schema-valid proposed registry entry plus a learning dossier, grading the evidence on the seven-tier model and assessing overlap against the shipped catalog. Use when you need an honest evidence grade and a build-or-fold verdict for a candidate method before turning it into a skill, when reproducing the evidence-and-overlap vetting on a method the catalog already judged, or when you need a ranked shortlist of new candidate methods in a family.

product-on-purpose 80a122d 3 files · 9.5 KB Updated Sep 17, 2026

File contents

Research Framework

This meta-skill is the entry point to the framework-research engine. It is not a thinking method and ships no registry entry of its own; it delegates the bounded research role to the think-research-framework subagent so the work runs in its own context with web search.

When to use

You have a candidate thinking method and need an honest evidence grade, an overlap call against the shipped catalog, a learning dossier, and a proposed registry entry before deciding whether to build it.
You want to reproduce the evidence-and-overlap vetting on a method the catalog already judged.
You want a ranked shortlist of new candidate methods in a given family.

When NOT to use

You already know the verdict and just want to author the skill. Go straight to the skill-authoring flow.
The request is a product or domain question rather than a thinking-method evaluation. That belongs in the sibling pm-skills library.
You want a framework executed on your own problem. That is what the individual think- skills (and the advisor's plan) are for.

What it does

Dispatch the work to the think-research-framework subagent: invoke the Task tool with subagent_type think-research-framework, passing the framework name (or the "discover N in family X" brief) the user supplied. Do not run the research inline in this context; the subagent holds the honesty discipline and runs the web research in its own window.

In name mode the subagent researches the method, grades it on the seven-tier model (S, M, P, V, A, C, X) using the conservative governing grade when the evidence is split or transferred, assesses overlap (distinct only above the roughly 20 percent ceiling, else fold, recipe, reject, or out-of-scope), writes the dossier body to a staging path (frameworks/_proposed/<slug>/dossier.md for a not-yet-shipped method; a shipped method keeps its record at skills/think-<slug>/evidence/dossier.md), validates a proposed registry entry against the schema with scripts/check-proposed-entry.mjs, and prints that entry for human paste plus a one-screen verdict. It never writes frameworks/registry.mjs. In discovery mode it returns a ranked shortlist of real, named candidate methods, each with a distinctness hypothesis.

---name: think-research-frameworkdescription: Researches a thinking framework end to end and produces a schema-valid proposed registry entry plus a learning dossier, grading the evidence on the seven-tier model and assessing overlap against the shipped catalog. Use when you need an honest evidence grade and a build-or-fold verdict for a candidate method before turning it into a skill, when reproducing the evidence-and-overlap vetting on a method the catalog already judged, or when you need a ranked shortlist of new candidate methods in a family.license: Apache-2.0---# Research FrameworkThis meta-skill is the entry point to the framework-research engine. It is not a thinking method and ships no registry entry of its own; it delegates the bounded research role to the `think-research-framework` subagent so the work runs in its own context with web search.## When to use- You have a candidate thinking method and need an honest evidence grade, an overlap call against the shipped catalog, a learning dossier, and a proposed registry entry before deciding whether to build it.- You want to reproduce the evidence-and-overlap vetting on a method the catalog already judged.- You want a ranked shortlist of new candidate methods in a given family.## When NOT to use- You already know the verdict and just want to author the skill. Go straight to the skill-authoring flow.- The request is a product or domain question rather than a thinking-method evaluation. That belongs in the sibling pm-skills library.- You want a framework executed on your own problem. That is what the individual `think-` skills (and the advisor's plan) are for.## What it doesDispatch the work to the `think-research-framework` subagent: invoke the Task tool with subagent_type `think-research-framework`, passing the framework name (or the "discover N in family X" brief) the user supplied. Do not run the research inline in this context; the subagent holds the honesty discipline and runs the web research in its own window.In name mode the subagent researches the method, grades it on the seven-tier model (S, M, P, V, A, C, X) using the conservative governing grade when the evidence is split or transferred, assesses overlap (distinct only above the roughly 20 percent ceiling, else fold, recipe, reject, or out-of-scope), writes the dossier body to a staging path (`frameworks/_proposed/<slug>/dossier.md` for a not-yet-shipped method; a shipped method keeps its record at `skills/think-<slug>/evidence/dossier.md`), validates a proposed registry entry against the schema with `scripts/check-proposed-entry.mjs`, and prints that entry for human paste plus a one-screen verdict. It never writes `frameworks/registry.mjs`. In discovery mode it returns a ranked shortlist of real, named candidate methods, each with a distinctness hypothesis.

Frequently asked questions