Browse reusable Agent Skills, each with a clear purpose and practical guidance.
File organization toolkit. Provides duplicate detection, file merging/splitting, pattern matching, text processing (like case conversion, word counting), and file classification by size or time.
Student database processing tools. Includes grade calculation, duplicate name detection, recommendation letter filtering, and TOEFL score filtering.
Documents 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.
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.
Parse a heterogeneous conference program (markdown, HTML, PDF-derived text, or JSON) into normalized event records with per-field confidence scores and independent classification axes (topic, depth, format, prerequisites, recorded, capacity). Detects the program's format before extracting, treats every inferred field as uncertain (present vs inferred vs missing), and flags thin or missing abstracts so downstream enrichment can target them. Conference-agnostic. Use when ingesting a conference or event schedule into a structured store, normalizing a talk/session list, or extracting per-session metadata with calibrated confidence. Trigger keywords - program ingestion, parse schedule, session extraction, event records, conference program, talk metadata, per-field confidence.
Cluster a conference's event records into a small set of coarse themes with finer sub-clusters, an explicit outlier bucket, and soft (multi-membership) affinities — using the hybrid embed-then-label pipeline (embed abstracts, reduce, density-cluster, then LLM-label the clusters) when embedding libraries are available, and an LLM-reasoned hierarchical fallback when they are not. Embeddings do the grouping; the LLM only names the groups. Conference-agnostic. Use when turning structured event records into a navigable theme map for preference elicitation and scheduling, when you need 6-8 reasonable themes rather than 20 muddy ones, or when overlapping talks must belong to more than one theme. Trigger keywords - theme clustering, cluster talks, embed then label, soft membership, outlier talks, conference themes, topic map.
Datasheet and reference manual reading skill for embedded engineers. Use when extracting pinouts, electrical limits, register maps, clock trees, or timing from MCU documentation. Activates on queries about reading STM32 RM, extracting register bits, finding errata, or navigating reference manual sections.
Domain-neutral methodology for the first level of Adler-style reading - systematic skimming to determine what kind of document this is, what it's about as a whole, and whether deeper engagement is worth the time investment. Read title, metadata, table of contents or section headings, abstract or introduction, conclusion, and end-material at a glance. Classify document type (methodology, framework, tool, theoretical, reference, or hybrid). Decide whether to escalate to deeper reading. Reusable across any artifact-from-document workflow - paper extraction, skill creation from a methodology document, literature triage, reading-list pruning. Use when an agent needs to convert "I have a document, what is it" into structured downstream-actionable input. Trigger keywords - inspectional reading, systematic skimming, document classification, Adler reading, skim before reading, skill-worthiness check, paper triage, reading triage.
Scores any resume or cover letter against LockedIn's calibrated rubric. No vault required. Three modes: score, refine, refine then score. Activate when the user says "audit my resume", "score my resume", "check my resume", or provides a resume file and asks for feedback. Also triggered after a completed `lockedin ingest`.
Parses a single financial statement PDF (checking, savings, credit card, brokerage, 401k, HSA, mortgage, tax form) and emits a normalized JSON record with institution, account mask, statement period, opening/closing balances, line-item transactions or holdings, and a confidence score. Use when extracting structured data from a bank, brokerage, retirement, or HSA PDF statement, when ingesting a drop of household finance documents, or when user mentions parsing a statement, extracting transactions from a PDF, or normalizing statement data.