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Claude Skills by gtynnn060110-hash
github.com/gtynnn060110-hash13 skills0 installs48 views
- File OperationsGuidance on reading, parsing, and processing various file formats (CSV, JSON, YAML) commonly used in legal and compliance tasksVotes: 0GitHub stars: 8
- SecurityGuidance on security analysis, compliance auditing, and vulnerability assessment techniques relevant to legal and regulatory compliance tasksVotes: 0GitHub stars: 8
- Web BrowsingGuidance on web content analysis, data extraction, and online research techniques for legal and regulatory information gatheringVotes: 0GitHub stars: 8
- Create SkillCreate a new reusable skill file to capture a calculation method, formula, or tool pattern you've discovered during a task.Votes: 0GitHub stars: 8
- Modify SkillUpdate or correct an existing skill file based on judge feedback or improved understanding.Votes: 0GitHub stars: 8
- Web Search FinanceFetch public financial data using Python requests from SEC EDGAR, Yahoo Finance, and other free sources. Use when tasks require online lookup of financial statements, stock data, or market figures.Votes: 0GitHub stars: 8
- File OperationsGuidance on reading, parsing, and processing various file formats (CSV, JSON, YAML) commonly used in legal and compliance tasksVotes: 0GitHub stars: 8
- PymatgenMaterials science toolkit. Crystal structures (CIF, POSCAR), phase diagrams, band structure, DOS, Materials Project integration, format conversion, for computational materials science.Votes: 0GitHub stars: 8
- Bio Lab QaUse this skill for LAB-Bench and biomedical question answering. 1. Treat candidate answers as controlled options. 2. Compare each option against the wording of the question and any source metadata. 3. Avoid adding synonyms in exact-answer tasks; return the exact option string. 4. If evidence is incomplete, state the uncertainty in `reasoning` while keeping `answer` concise.Votes: 0GitHub stars: 8
- Math Physics SolvingUse this skill for SciBench physics and quantitative science calculation tasks. 1. Extract variables, constants, units, and target quantity. 2. Choose the governing equation or theorem before substituting numbers. 3. Use `sympy`, `scipy`, or a small Python script for algebra or numerical checks when useful. 4. Keep unit conversions visible. If the verifier expects a numeric answer, put only the numeric value in `answer`. 5. Include the derivation summary in `reasoning`.Votes: 0GitHub stars: 8
- Science Common ReasoningUse this skill before solving any science task. 1. Restate the scientific question, quantities, units, and requested output. 2. Identify whether the task is numeric, multiple choice, data analysis, or open-ended workflow design. 3. Read `/root/data/task-XXX/task_payload.json` before making assumptions. 4. Track assumptions explicitly and prefer dimensional checks for quantitative answers. 5. Write a compact final JSON file to the exact `/app/task_XXX_output.json` path.Votes: 0GitHub stars: 8
- Scientific Data AnalysisUse this skill for tasks that mention datasets, previews, CSV files, models, or generated artifacts. 1. Inspect the payload, folder tree, preview rows, and requested output paths. 2. Propose a reproducible script layout before modeling. 3. Choose baselines and metrics appropriate to the domain. 4. Validate by checking file existence, schema, row counts, value ranges, and leakage risks. 5. Save generated artifacts under `/app` unless the task explicitly asks for another path.Votes: 0GitHub stars: 8
- Scientific Source CheckingUse this skill when a task points to external scientific sources or benchmark pages. 1. Prefer primary benchmark URLs and cited dataset/project pages. 2. Record accessed URLs and version assumptions in the output JSON. 3. Distinguish source facts from derived calculations. 4. Do not claim unavailable files were inspected; describe fallback reasoning instead.Votes: 0GitHub stars: 8