Agent Skills: component-extraction
Domain-neutral methodology for the third level of Adler-style reading - extracting structured components (terms, propositions, arguments, solutions) from a document section by section. Selects a reading strategy appropriate to document size and structure (section-based for documents under 50 pages with clear sections; windowing for long documents without breaks; targeted for hybrid content where only specific sections matter). Writes per-section extraction notes that downstream synthesis can consume. Reusable across any extraction workflow - skill creation from a methodology document, Pass-2 content grasp on a paper's full text, evidence-mining from a long-form report. Use when an agent has done structural analysis and now needs to extract the actual atomic content. Trigger keywords - component extraction, section-by-section extraction, extract terms, extract propositions, extract arguments, Adler Level 3, interpretive reading.
Install this agent skill to your local
Skill Files
The files that make up component-extraction.
More agent skills
- adr-architectureDocuments significant architectural and technical decisions with full context, alternatives considered, trade-offs analyzed, and consequences understood. Creates a decision trail that helps teams understand why decisions were made. Use when choosing between technology options, making infrastructure decisions, establishing standards, migrating systems, or when user mentions ADR, architecture decision, technical decision record, or decision documentation.
- fuzzing-dictionaryBuilds and applies fuzzing dictionaries so a fuzzer can produce the keywords, magic bytes, and tokens a target expects. Covers extracting tokens from source, headers, binaries, and specifications, dictionary syntax, and wiring one into libFuzzer or AFL++. Use when fuzzing a parser, protocol, or file format, when coverage stalls at input validation, or when a target compares against fixed strings.
- subagent-driven-developmentUse when executing implementation plans with independent tasks in the current session
- context-degradationThis skill should be used for diagnosing and mitigating context degradation: lost-in-middle failures, context poisoning, context clash, context confusion, attention-pattern issues, and agent performance degradation caused by accumulated or conflicting context.
- app-store-changelogCreate user-facing App Store release notes by collecting and summarizing all user-impacting changes since the last git tag (or a specified ref). Use when asked to generate a comprehensive release changelog, App Store "What's New" text, or release notes based on git history or tags.
- axiom-audit-core-dataUse when the user mentions Core Data review, schema migration, production crashes, or data safety checking.