القائمة
Streamline a theory down to its core essence, selecting a few different options.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Design and propose the next step: either a regular data-gathering experiment, literature search, or a concrete solution candidate.
Determine the type of proposal given, execute/delegate accordingly, and return the appropriate resulting ID (experiment ID, literature search ID, or solution ID).
Score and rank solution candidates relative to the research goal, and update parent theory scores.
Integrate recent interpretations from the interpretation log into the associated theory.
Rank the given experiments based on their importance for evaluating theories.
Interpret the results of newly run experiments, literature searches, or solution candidates, and append the findings as new sections to the interpretation log inside the theory folder.
| name | streamline-theory-variations |
| description | Streamline a theory down to its core essence, selecting a few different options. |
| argument-hint | theory ID (e.g. T_20260414_143100_d4e5f6) |
Arguments: $ARGUMENTS
The arguments contain a theory ID (like T_20260414_...).
You will run the streamline-theory skill multiple times, each in a separate parallel subagent, and each with a different instruction for which key story to focus on.
In particular:
streamline-theory with the instruction to focus on "the most novel aspect". Also pass it the input theory ID.streamline-theory with the instruction to focus on "the most insightful aspect". Also pass it the input theory ID.streamline-theory with the instruction to focus on "the most foundational aspect". Also pass it the input theory ID.streamline-theory with the instruction to focus on "the most universally applicable aspect". Also pass it the input theory ID.streamline-theory with the instruction to focus on "the most speculative and ambitious aspect". Also pass it the input theory ID.All subagents can run in parallel. Each one will report back a new theory ID (e.g. T_20260414_150000_x1y2z3). Wait for all subagents to finish and collect their final result messages containing the returned theory IDs. Report the list of returned theory IDs as the output of this skill.