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Score the length of a given theory.
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Basierend auf der SOC-Berufsklassifikation
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 | score-length |
| description | Score the length of a given theory. |
| argument-hint | the theory ID to score (e.g. T_20260414_143100_d4e5f6). Optionally, a STANDARD_LENGTH value. |
| user-invocable | false |
Your task is to assess the length of a given theory based on its content.
Besides the theory to score, you may optionally be given a STANDARD_LENGTH value. The default STANDARD_LENGTH, if not specified, is 7000 words.
theory.md in number of words, excluding any conclusion sections and appendices, as well as any introductory sections (such as phenomenon descriptions, overviews and summary sections, statement/content tables, prior art comparisons, etc):theory.md file (e.g. grep -n '^#' <CONTEXT_DIR>/theory/theory.md).head -n 500 <CONTEXT_DIR>/theory/theory.md | tail -n +50 | wc -w).Length Score = 1 / (1 + (words_in_main_body / STANDARD_LENGTH)**3), where words_in_main_body is the number of words in the main body of the theory. Round to two decimal places. Use ad-hoc Python code to perform this calculation, as described above.