argumentative-zoning
Skill1 starsChanged 3 months agoApache-2.0View on GitHub
Tactic: Label every sentence of one paper with its rhetorical role using Argumentative Zoning. Use when fixed rhetorical labels and cross-paper alignment matter.
In this repository34 other files it gives its agents.
- acu-nugget-recallSkill
- atomic-unit-matchingSkill
- atomic-unit-recall-aggregateSkill
- atomic-unit-writingSkill
- claim-label-predictionSkill
- claim-writingSkill
- domain-level-judgmentSkill
- dual-column-self-checkSkill
- engineering-config-gradingSkill
- first-pass-skimSkill
- keshav-three-passSkill
- multi-stage-cascade-extractionSkill
- paper-fetchSkill
- qalmriSkill
- qalmri-worksheetSkill
- qasper-evidence-qaSkill
- quality-appraisal-checklistSkill
- question-framingSkill
- rationale-selectionSkill
- reforms-gradingSkill
- reporting-standard-checklistSkill
- reproducibility-third-party-verificationSkill
- research-question-appraisalSkill
- rhetorical-structure-qualitySkill
- second-pass-graspSkill
- signalling-question-answeringSkill
- star-awardingSkill
- study-design-tool-gateSkill
- sum-threshold-scoringSkill
- template-slot-fillingSkill
- third-pass-deep-readSkill
- unit-classificationSkill
- unit-segmentationSkill
- worst-case-lookupSkill
The file
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 32
Use exactly AIM, BACKGROUND, OWN, CONTRAST, BASIS, TEXTUAL, and OTHER.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Argumentative Zoning
Orchestration Pattern
- Fetch the paper; stop on
not_found. - Segment the requested scope with sentence granularity and preserve
{line, start, end}offsets. Write01-unit-segmentation.json. - Classify every unit with
label_set: argumentative-zoning,hierarchy_toggle: false, andoutput_type: single_label. Write02-unit-classification.json.
Use exactly AIM, BACKGROUND, OWN, CONTRAST, BASIS, TEXTUAL, and OTHER. Every sentence receives one label; use OTHER rather than skipping an uncertain unit. Narrow scopes are valid but not distributionally comparable to a full-text run.
Report scope, sentence count, zone counts, empty zones, and both paths.
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