Results for “process”

Comprehensive PDF manipulation toolkit for extracting text and tables, creating new PDFs, merging/splitting documents, and handling forms. When Claude needs to fill in a PDF form or programmatically process, generate, or analyze PDF documents at scale.

Comprehensive PDF manipulation toolkit for extracting text and tables, creating new PDFs, merging/splitting documents, and handling forms. When Claude needs to fill in a PDF form or programmatically process, generate, or analyze PDF documents at scale.

Comprehensive PDF manipulation toolkit for extracting text and tables, creating new PDFs, merging/splitting documents, and handling forms. When Claude needs to fill in a PDF form or programmatically process, generate, or analyze PDF documents at scale.

Comprehensive PDF manipulation toolkit for extracting text and tables, creating new PDFs, merging/splitting documents, and handling forms. When Claude needs to fill in a PDF form or programmatically process, generate, or analyze PDF documents at scale.

Integrate Iteration Layer APIs for document, website, image, and sheet processing. Composable APIs — Document Extraction, Website Extraction, Document to Markdown, Image Transformation, Image Generation, Document Generation, and Sheet Generation — share one credit pool and chain together into workflows.

Writes documents in a plain, human voice and removes phrasing that reads as machine-generated, applying a two-pass write-and-audit process to any written artifact meant to be read by a person.

This guide covers essential PDF processing operations using Python libraries and command-line tools. For advanced features, JavaScript libraries, and detailed examples, see reference.md. If you need to fill out a PDF form, read forms.md and follow its instructions.

Processes documents through case.dev OCR for text and table extraction. Supports PDF and image files up to 500MB with page-level and word-level output. Use when the user mentions "OCR", "text extraction", "scan document", "digitize", "extract text from PDF", or needs word-level positional data from documents.

Unified content extraction and action planning. Use when user says `tapestry [URL]`, `weave [URL]`, `help me plan [URL]`, `extract and plan [URL]`, `make this actionable [URL]`, or similar phrases indicating they want to extract content and create an action plan. Automatically detects content type (YouTube video, article, PDF) and processes accordingly.

Write WeChat public account long-form articles in the distinctive style of Khazix, a known AI content creator. Handles various input formats (PDF, links, notes) and guides the user through a structured writing process from material understanding to final polish.

Run condition-based vault health diagnostics. 8 categories — schema compliance, orphan detection, link health, description quality, three-space boundaries, processing throughput, stale notes, MOC coherence. 3 modes — quick (schema+orphans+links), full (all 8), three-space (boundary violations only). Returns actionable FAIL/WARN/PASS report with specific fixes ranked by impact. Triggers on "/health", "check vault health", "maintenance report", "what needs fixing".

Record observable skill test runs for debugging. Use when the user wants to test, dry-run, debug, inspect, or compare how a Codex skill behaves on a concrete request; creates a local non-overwriting Markdown report with the visible process, files read, commands run, changed artifacts, errors, and a brief behavior summary. Does not certify skill quality or replace user judgment.

Inspect, extract, OCR, create, merge, split, reorder, rotate, annotate, fill, redact, compress, secure, and verify PDF documents while preserving source files and visual fidelity. Use when working with one or more .pdf files; converting documents to or from PDF; extracting text, tables, images, metadata, forms, or page ranges; applying true redactions or signatures; diagnosing malformed, encrypted, scanned, or inaccessible PDFs; or validating that a PDF transformation preserved the intended content and layout.

Guide users through writing a systematic literature review (SLR) following the PRISMA 2020 framework. Use this skill whenever the user mentions 'systematic review', 'systematic literature review', 'SLR', 'PRISMA', 'PRISMA 2020', 'PRISMA flow diagram', 'PRISMA checklist', or asks for help writing, structuring, or auditing a literature review that follows reporting guidelines. Also trigger when the user asks about inclusion/exclusion criteria for a review, search strategies for databases like Scopus/WoS/PubMed, study selection processes, risk of bias assessment, or narrative synthesis for a review paper. This skill covers the full PRISMA 2020 checklist (27 items), produces a Word document manuscript in strict journal article format, generates an annotated PRISMA flow diagram, and enforces APA 7th Edition referencing throughout. It does NOT cover meta-analysis or statistical pooling. By Chuah Kee Man.

Use this skill whenever a user wants to create a presentation outline, slide deck structure, storyboard slides, or plan a deck for any context (talk, boardroom, email report). Also use when the user mentions "help me structure my presentation", "slide outline", "storyboard my deck", "presentation flow", "plan my slides", "key message for my deck", "pyramid principle for slides", "what slides should I include", or "help me tell a story with slides". This skill walks through a complete, interactive process in two phases: Phase 1 (setup → key message → storyboard) saves a slide-outline.md; Phase 2 (interactive per-slide copy drafting → polish) saves a slide-copy.md that is linked from slide-outline.md. Trigger even when the user only mentions a vague intent like "I need to present X to my team" or "help me put together a board deck".

Mechanics for building and managing pollers — subprocess scripts that check external services on a schedule and emit events when something has changed. Use when authoring a new poller (a `pollers.json` manifest plus a script in any language), debugging why a poller isn't firing, or extending an existing one. Pollers run on cron, emit JSONL events when there's something to report, and stay silent otherwise (silence-as-filter). The framework discovers `<home>/skills/<name>/pollers.json` files at startup and via `reload_pollers`; each emitted event becomes a fresh turn on a `poller:<name>` synthetic channel. Companion to the `world-scanning` skill, which catalogs *what's worth polling*. Distinct from `async-tasks` (one-shot wake-up via bash_async, not recurring) and from in-process scheduler callables (saga-consolidate, oauth-usage-poll — those mutate mimir-internal state and aren't subprocess-isolated).