Ferramentas

Extracts text and tables from PDFs; merges, splits and rotates pages, adds watermarks, fills forms and OCRs scanned documents. The official Anthropic skill behind Claude's document features; source-available, not open source.

166 research skills maintained by K-Dense (formerly Claude Scientific Skills), spanning bioinformatics, cheminformatics, clinical research, materials and physics, including unified access to 78 public databases such as PubChem and UniProt. Works with Claude Code, Codex and Cursor.

Turns the current folder into a teaching workspace you can resume across conversations: asks your learning goal, gathers reliable sources, builds short HTML lessons and cheat sheets, and tracks progress. Good for self-study and lesson prep; invoke manually (/teach), no API key.

After giving advice, a draft or a data analysis, adds 2-3 targeted follow-up questions that prompt the user to check key facts, test the reasoning and fill in missing context. Fires at most once per conversation. Official Anthropic skill.

Skill suite for the whole academic research workflow: deep research (including PRISMA systematic reviews), paper writing, multi-perspective peer review and revision, pausing for human approval at each stage, with citation and integrity checks. CC BY-NC, non-commercial only.

Drafts, revises and reviews research manuscripts, tying every fact and number to verified evidence and covering reporting guidelines, authorship, AI disclosure and confidentiality; explicitly forbids fabricated citations or data. Includes offline check scripts; no API key needed.

Unified database lookup skill from K-Dense's scientific collection: reproducibly queries about 80 public database APIs such as PubChem, UniProt, ChEMBL, ClinicalTrials.gov and FRED, returning traceable results with endpoints, parameters and count checks. Some need API keys.

Systematic literature reviews following PRISMA and similar standards: searches PubMed, arXiv, bioRxiv and other databases, verifies each citation's DOI, and outputs Markdown and PDF in APA, Nature or other styles. Main web search uses parallel-cli and needs a Parallel account.

Teaches agents standard single-cell RNA-seq analysis with Scanpy: QC, normalization, PCA/UMAP, clustering, differential expression and plots, with ready-to-run pipeline scripts and guidance on converting Seurat and other R objects to h5ad. Needs Python 3.12+; by K-Dense.

Guides agents to the right statistical method for research data: t-tests, ANOVA, chi-square, regression and Bayesian analysis, checking assumptions, computing effect sizes and power, and reporting results in APA format. Python-based (pingouin, statsmodels); by K-Dense.

Teaches agents to read and write Obsidian vaults: Obsidian-flavored Markdown, Bases data views, JSON Canvas and the Obsidian CLI, plus Defuddle web content extraction and Knap template rendering. Maintained by Obsidian CEO kepano.

Completes and populates three-statement financial model templates, linking the income statement, balance sheet and cash flow with formulas and checking that the balance sheet balances and cash ties out, with no hardcoded values. Part of Anthropic's official financial-analysis plugin.

Builds M&A accretion/dilution models: sources and uses, pro forma EPS and goodwill amortization impact, with sensitivities on synergies, premium and cash/stock mix, in an Excel workbook. You supply share prices, EPS and deal terms. From Anthropic's investment-banking plugin; needs expert review.

Anthropic's official financial services skills for investment banking, equity research, private equity, fund admin and wealth management: comps, DCF, LBO, three-statement models, CIMs, earnings reviews, IC memos, GL reconciliation and more. Outputs need expert review.

Official Anthropic earnings skill: for a covered company, reads the quarterly report and call, compares results with consensus for a beat or miss, breaks down key metrics, updates estimates and thesis, and writes an 8-12 page update with charts. Needs analyst review; not investment advice.

Official Anthropic private equity skill: turns company, industry, financials, deal terms, diligence findings and returns into a standard IC memo with executive summary, key risks and mitigants, base, upside and downside returns and a clear recommendation, as a Word doc by default.

Official Anthropic initiating coverage skill: works in five separate steps (company research, financial model, valuation, charts, final report) to produce an Excel model, 25-35 charts and a 30-50 page Word report styled after bulge-bracket sell-side research. Needs analyst review.

Official Anthropic finance skill that checks Excel for formula errors like #REF!, numbers hardcoded in formulas, sum ranges that miss rows and mixed units; on full models it also checks the balance sheet balances and cash ties. Lists issues and fixes and asks before changing anything.

Builds a DCF valuation in Excel: pulls figures from SEC filings and research, projects free cash flow, computes WACC and terminal value, and adds sensitivity tables. Derived values are formulas, inputs cite sources, and each step is confirmed with you. From Anthropic's financial-analysis plugin.

Official Anthropic LBO modeling skill: builds sources and uses, operating projections, debt schedule and IRR/MOIC returns in an Excel template, with every calculation as a formula and each section checked with you. Works in the Excel add-in or generates files with local Python; needs expert review.

Official Anthropic comparable company analysis skill: selects listed peers, compiles operating metrics and multiples like EV/EBITDA and P/E with percentiles, and outputs a comps table in Excel for valuation, IPO or financing pricing. Prefers paid sources like FactSet but can use SEC filings.

Official Anthropic fund admin skill: matches general ledger and subledger exports for a date or period line by line, lists mismatched amounts, quantities, posting dates and one-sided entries, suggests causes such as timing, FX or mapping, and writes a break report. Needs accountant review.

Distills technical books, doc folders or paper collections (PDF, EPUB, DOCX, Markdown and more) into an agent skill with a core framework, on-demand chapter files, glossary and cheat sheet for lookup while working. Extraction needs local Python; poppler or docling optional for PDFs.

Helps finance teams with ratio analysis, DCF valuation, budget variance analysis and rolling forecasts, using bundled Python scripts so the numbers can be recomputed. Needs Python locally and financial data prepared as JSON; have a professional review the results.