danielrosehill

Sweep all (or a filtered subset of) email addresses in the workspace CRM and re-verify them via Hunter Email-Verifier. Use periodically — people change jobs, addresses go stale, accept-all status changes. Updates the `verified` and `last-verified` columns in `crm/contacts.md` and prints a summary of what flipped.

Scan the user's existing Claude Code plugins and MCP servers to detect capabilities the career plugin needs (email send, transcription, calendar/tasks, semantic store, CRM). For each capability, decide whether to reuse an already-installed plugin/MCP, install a recommended companion plugin, or add an MCP server. Writes the resolution map to ${CAREER_DATA_DIR}/config.json under a `capabilities` block. Invoked from /career:onboard before install-companion-plugins so we don't double up on capabilities the user already has.

Enrich an existing CRM contact with Hunter Combined-Enrichment — pulls role, seniority, department, social handles, and the contact's company facts in one call. Use to flesh out a thinly-populated CRM row before drafting outreach or prepping for a meeting. Operates on an email address from the CRM; updates the row in place.

Given a person's name and their company (name or domain), return Hunter's best guess at their email address with a confidence score. Use when the user already knows who they want to reach and just needs the address. Differs from find-contact (which lists candidates at a company) — this is targeted at a single named person.

Validate a single email address via Hunter Email-Verifier. Use when the user has an address (handed to them, scraped, guessed) and wants a deliverability + confidence read before sending outreach. Returns Hunter's verdict (deliverable / risky / undeliverable / unknown), score, and the disposable / role / accept-all flags. Does not write to the CRM unless asked.

For CONTEXT_STORE=pinecone — verify the index against the local workspace. Flags vectors whose source file was deleted, renamed, or content-changed (hash mismatch), and surfaces vectors whose content contradicts current ground-truth (stale claims, closed engagements, outdated targets). Proposes deletes/re-embeds; never silently mutates the index.

First-run scaffold of a vector-store namespace dedicated to application/outreach tracking. Creates the `applications` namespace in the configured index, sets the metadata schema (company, role, status, applied_date, last_touch, source_path, stage), seeds it from crm/outreach.md + crm/opportunities.md, and registers it in config. Idempotent — re-running detects existing namespace and offers reseed or skip.

Flat/local-mode workspace hygiene. Sort loose files into canonical folders (research/, domain-notes/, inbox/, crm/, resume/, snippets/, branding/, cache/), find near-duplicates by name+hash, flag stale inbox entries (>14d), and re-root mis-placed files. Proposes a plan, applies only on confirm. No-op when CONTEXT_STORE != markdown.

Extract a single track (audio, subtitle, video) from a Matroska container to its own file using mkvextract. Use when the user says "pull out this audio track", "extract the subtitles", "save this audio as a separate file", "get the SRT from this MKV". No re-encode.

Set which audio or subtitle track plays by default in a Matroska container using mkvpropedit. Use when the user says "set the default audio", "make this subtitle track default", "this audio language should play first", "change the default track". Idempotent, no re-encode.

Remove unwanted tracks (audio, subtitle, video) from a Matroska container and save a new, smaller file. Use mkvmerge syntax (-a, -s, -d to keep tracks; -A, -S, -D to drop all of a type). Use when the user says "remove this audio track", "drop all subtitles except English", "keep only this video and audio", "make this file smaller". No re-encode.

Inspect tracks in a Matroska (MKV) container and display a formatted table showing track number, type (video/audio/subs), codec, language, default flag, and track name. Use when the user asks "what's in this MKV", "list the tracks", "show audio/subtitle languages", "inspect this file before editing".

Install optional video-editing tools (moviepy, auto-editor, video-use, VideoAgent, vit, LosslessCut, editly) plus media-inspection helpers (exiftool, mediainfo). Lets the user pick which to install; Python tools share a single uv-managed venv recorded in preferences.json. Use when the user says "install video tools", "set up moviepy", "install auto-editor", "deps setup", "install lossless cut", "install mediainfo", "install exiftool".

Extract one or more time-range segments from a video. Use when the user says "cut from 1:30 to 3:45", "trim the first 30 seconds", "extract these segments", "split this clip at 5:00". Stream-copies losslessly by default; offers a frame-accurate re-encode mode when the cut must be exact. Multiple segments are written as separate files (or optionally stitched in one pass).

Run an agentic / LLM-driven cut-down on a long video — "make a 60-second highlight reel of this hour-long stream", "cut the boring parts from this lecture", "find the best moments in this footage". Wraps `video-use` (browser-use) by default; falls back to `VideoAgent` (HKU) for research-grade understanding. Both come from the shared uv venv set up by `deps-setup`. Outputs a cut-list (timestamps + reasons) and an optional rendered preview.

Render a video from a declarative editly JSON spec (clips, transitions, titles, audio mix). Use when the user says "render this editly spec", "compose this slideshow", "make a video from this JSON", "editly render". Validates the spec, runs editly headlessly, and reports the deliverable. Editly must be installed via `deps-setup` (npm-global).

Audit and standardise a dataset's header row against a naming convention (snake_case, camelCase, Title Case, kebab-case) and verify consistency with an existing or forthcoming data dictionary. Use when preparing a dataset for SQL loading, publishing, or when header inconsistency (mixed casing, spaces, punctuation, abbreviation drift) is blocking downstream work.

Produce localised versions of a dataset and/or its data dictionary with translated column headers (and optionally translated dictionary descriptions) so the same underlying data can be analysed by speakers of different languages. Use when the user wants frictionless multi-language packaging — e.g. English canonical plus Hebrew, Arabic, French, Spanish variants — without forking the underlying data.

Audit numeric columns for inconsistent decimal precision (e.g. some values at 4 dp, others at 2 dp) and round all values to a user-chosen precision. Use before SQL load or publishing when mixed precision would otherwise produce awkward `NUMERIC(x, y)` choices or misleading implied precision.

Generate a polished PDF document from a dataset using Typst, with layout chosen to match the data shape (wide tables → landscape multi-page reference, narrow tables → portrait report, per-record → one-record-per-page card/profile layout, grouped → sectioned report). Supports user-selected field subsets, custom column labels, optional filtering/sorting, cover page, summary stats, and branded templates. Use when the user wants the dataset (or a slice of it) rendered as a shareable/printable document rather than a spreadsheet export.

Reconcile a canonical upstream data file with a downstream project that has diverged — the downstream has added enrichments, renamed columns, changed types, or restructured the data, so fresh upstream rows can't be loaded incrementally without transformation. Builds a mapping between upstream and downstream representations and generates an idempotent incremental sync script that ingests only new/changed rows from upstream, applies the transformation, and appends/upserts them into the downstream dataset. Use when a project's working data has evolved beyond the source and new source data needs to flow in without clobbering the divergence.

Convert tabular geodata (CSV / Excel / Parquet) into GeoJSON (or GeoJSON Seq / newline-delimited GeoJSON) — inferring geometry from lat/lon columns, WKT/WKB columns, or address columns via geocoding. Handles CRS reprojection (default WGS84 / EPSG:4326), feature property selection, and large-file streaming. Use when the user has location data in flat form and needs it as GeoJSON for mapping, GIS, or geospatial analysis tools.

Add or update a CHANGELOG.md in a data repository, recording dataset versions, schema changes, row-count deltas, enrichments applied, and re-publications. Follows Keep-a-Changelog conventions adapted for datasets. Use when the user wants versioned documentation of how a dataset has evolved over time.

Prepare or refactor a dataset for upload into a REST API or MCP server — mapping dataset columns to API request fields, handling batching, pagination, rate limits, authentication, idempotency, and error retries. Works from an OpenAPI spec the user provides, a user-pointed MCP tool schema, or documentation for a well-known API (Salesforce, HubSpot, Airtable, Notion, Stripe, Shopify, Pipedrive, etc.). Generates a loader script plus a dry-run preview before executing.

Batch-stamp copyright, artist, and rights information on all images in a directory. Use when you need to quickly add copyright metadata to a photo library before distribution or archival — a convenience wrapper around exiftool.

Decode JPEG XL images (.jxl) to PNG or JPEG. Use when you need to convert JXL files back to standard formats for compatibility, display, or further editing.

Extract embedded JPEG and PNG images from a PDF at their native resolution, without rasterizing. Use when a PDF is primarily a wrapper around photos or images and you want to recover them at full quality without the page rendering overhead.

Rasterize PDF pages to numbered image files (JPEG, PNG, or TIFF) at a specified resolution (DPI). Use when you need to convert PDF content to standalone images — one image per page — with optional page range selection.

Read and display EXIF, IPTC, XMP, and other metadata from images as structured JSON. Use when you need to inspect image metadata without modifying it — opposite of scrub-metadata, which removes metadata.

Write EXIF, IPTC, and XMP metadata tags to image files. Use when you need to add or update metadata like artist name, copyright, description, keywords, or GPS coordinates on individual images.

Convert images to JPEG XL format (.jxl) with quality presets (lossless, visually lossless, or web). Use when you want optimal compression for photo archival or long-term storage, especially from JPEG originals where lossless transcoding preserves the original bitstream at smaller file size.

Losslessly transcode JPEG files to JPEG XL, preserving the original JPEG bitstream while achieving ~20% file size reduction. Use when archiving JPEG photo libraries where the goal is smaller files without re-compression artifacts.

Export a transcript (or any pipeline output) by emailing it, uploading to Google Drive, or copying to clipboard. Use when the user asks to send, email, upload, save to Drive, or copy a transcript.

Transcribe a podcast episode and produce two outputs in one pass — (1) the raw API transcript exactly as the provider returned it, and (2) a podcast-formatted reading version with filler words removed, section headers added, and speaker labels preserved. Use whenever the user provides a podcast audio file or says "transcribe this podcast".

Diagnose-and-treat workflow for very messy recordings where the standard preprocessor isn't enough. Generates a spectrogram, identifies problematic frequency bands (AC hum, rumble, narrow-band whines, broadband hiss, clipping), and proposes targeted ffmpeg filters. ONLY use when the user explicitly invokes it — the normal pipeline runs `preprocess-for-transcription` directly and skips diagnostic work. Trigger phrases the user might use — "this audio is messy", "transcription failed because of noise", "fix this rough recording", "the audio is bad and the transcript is garbage".

Remove background noise from an audio file. Cloud providers (Auphonic default, ElevenLabs, Dolby.io) or local (DeepFilterNet ML, ffmpeg afftdn non-ML). Use when the user asks to denoise, clean up noise, remove hum/hiss, or enhance speech audio before transcription.

Prepare audio for transcription — format normalise (mono/16kHz/opus), loudness normalise (EBU R128), and collapse long silences (silero-vad). Optional denoise pass. Use before sending to AssemblyAI or any ASR for cleaner results, smaller uploads, and lower cost. Use when the user asks to "preprocess audio", "prep for transcription", "clean up a recording before sending it", or just hands over a raw voice memo to be transcribed.

Apply a stylistic / formatting transformation to a transcript using a named prompt from the user's Text-Transformation-Prompt-Library (206 transformations covering blog outlines, briefs, business correspondence, analysis documents, meeting notes, and more). Use when the user asks to "convert this to <style>", "format like a <type>", or names a specific transformation. Fetches the catalog on demand and caches it; never commits the prompts into this plugin.

Mine a transcript for durable personal context — facts about the speaker (location, role, projects, preferences, relationships, ongoing work) — and write them to a context file for later reuse. De-duplicates against existing context so the same facts aren't re-extracted on every memo. Use when the user wants to build a knowledge base from voice memos, or asks to "pull out context from this".

Segment a mixed-intent transcript into separate files by category — prompts, context, action items, background, decisions. Useful when the user has dictated a dev brief, code review, or planning session that interleaves multiple kinds of content. Use when the user says "split this transcript", "separate the prompts from the context", or hands over a transcript that is clearly multi-purpose.

Orchestrator — analyze a decision through multiple frameworks in parallel. Reads a decision file, fans out to N framework subagents simultaneously (one per selected framework), each produces a structured analysis fragment, then synthesis aggregates the results. Use this when the user wants a multi-lens evaluation of a major decision rather than running individual frameworks.

Apply Kahneman's outside view — define the reference class, look up the historical base rate, and benchmark the inside-view prediction against it. Produces a 0-100 score.

List, create, edit, or delete named lens-bundles (saved framework groupings) used by /decision:analyze. Bundles let the user predefine "for career decisions, run these five frameworks" without typing the list each time.

Apply Cost-Benefit Analysis to a single decision — quantify costs and benefits per option over a stated time horizon, run sensitivity, and produce a 0-100 score. Use when the user wants just this one lens, or as a building block called by /decision:analyze.

Apply Snowden's Cynefin frame — classify the decision domain (Clear, Complicated, Complex, Chaotic, Confused) and prescribe domain-appropriate action. Produces a 0-100 score.

Build a decision tree with probabilities and payoffs, roll back expected values, and report EV and variance per option. Produces a 0-100 score.

Classify decision items by urgency and importance on the 2x2 matrix and prescribe quadrant-appropriate action. Produces a 0-100 score.

Export a rendered decision-analysis PDF — upload to Google Drive via the configured gws MCP server, copy to a chosen local path, or both. Run after /decision:render-pdf.

Use when the user points at a GitHub repo (an agent skill, MCP server, or "Claude plugin"-ish project) and wants to install or register it. Routes between native plugin install, MCP server registration, and adding to the user's third-party marketplace. Triggers on phrases like "install this from GitHub", "add this skill to my setup", "register this as a third-party plugin", "is this available as a Claude plugin".

Reference and worked example for the CONTEXT.md / CLAUDE.md two-file workflow. Use when the user asks "what is CONTEXT.md", how the human-context vs agent-briefing split works, or wants a copyable example pair to seed a new repo. Pairs with the operational skills (context-to-claude, claude-to-context, add-to-context, remove-from-context, manual-context-update, chunk-repo-context) — this skill explains the model; those skills do the work.

Use when the user wants to prune and chunk a bloated CLAUDE.md into a structured context/ store with pipeline folders and subagent templates. Triggers on phrases like "chunk claude", "prune CLAUDE.md", "set up context store", "split CLAUDE.md".

Use when the user wants to strip AI-generated style tics from documentation — emojis, excessive lists, all-caps filenames, fragmented structure. Triggers on phrases like "declaude the docs", "clean up documentation style", "remove emojis from docs", "apply style guide".

Use when the user wants to install a new user-level slash command at ~/.claude/commands/. Triggers on phrases like "install a slash command", "add a /command", "create a user-level slash command", "save this as a slash command".

Save a Claude Code plan (from ExitPlanMode, design discussion, or multi-step task) to persistent storage. ONLY invoke when the user explicitly asks to save/stash/store a plan (e.g. "save this plan", "stash the plan", "store the plan in the planning repo"). Do NOT auto-invoke after planning. Routes to the active project's `planning/` folder when one exists, else to the user's configured central planning repo.

Synthesize a new SKILL.md from the procedure that was just followed in this session, so the next session can replay it without being briefed from scratch. Use when the user says "extract this as a skill", "save this process", "make a skill from what we just did", "this should be a skill", "let's not have to explain this again next time", or after a long worked example whose procedure has clear reuse value.

Write a comprehensive point-in-time session log into `<repo>/planning/session-logs/YYYY-MM/YYYY-MM-DD-<slug>.md` for archival rather than immediate continuation. Captures everything achieved, the current overall state, decisions, surprises, and follow-ups for the distant future. Use when the user says "log this session", "wrap up with a record", "write today's session out", "record what we did", "we may not come back to this for a while — capture it", "session log", or otherwise signals they want a journal entry rather than a handover.

Manage meeting agendas as Google Docs — create, link to a calendar event description, share with attendees, or email. One skill, four sub-actions.

Assign due dates to Todoist tasks in batch. Walks the user through each undated task and applies their choice.

Assign priorities to Todoist tasks in batch. Walks the user through each unprioritised task and applies their choice.

Create multiple Google Calendar events from a structured list. Resolves attendees once across the batch, confirms the table, then writes.

Create multiple Todoist tasks from a structured list. Confirms the table, then writes serially.

Create a single Google Calendar event. Resolves attendees via the contacts MCP. Optionally links a Drive doc (agenda) into the description.

Create a single Todoist task. Sets project, due date, priority, labels per user input or sensible defaults.

Delete a Google Calendar event. Confirms before deleting; warns when attendees will receive cancellation notices.

Look up an Israeli medication on drug.co.il (the drug-information site of the Israeli Pharmacists Organization, ארגון הרוקחות בישראל). Returns structured JSON — Hebrew + English name, manufacturer, active ingredients, ATC code, dosage/usage form, prescription status, health-basket inclusion (סל הבריאות), approved indication, equivalent drugs (generics), and links to MOH-hosted patient leaflets in Hebrew/English/Arabic. Use when the user asks about an Israeli medication by Hebrew or English brand name, generic name, or active ingredient.

Look up an Israeli medication in the official Israeli Drug Registry (מאגר התרופות) maintained by the Ministry of Health at israeldrugs.health.gov.il. This is the authoritative regulatory source — registration number (דרגיסטר), license holder, manufacturer, active ingredients with strengths, ATC code, dosage form, route of administration, prescription/OTC status, health-basket inclusion, full approved indication, registration status (active / cancelled / suspended), and links to the official MOH-approved Hebrew/English/Arabic patient leaflet (עלון לצרכן) and prescribing information (עלון לרופא). Use when the user wants the regulatory record — registration number, license holder, official indication text, or whether a drug is currently registered.

Categorized map of every skill in the israel-agent-skills plugin, grouped by area (Healthcare & Medication, Emergency Preparedness, Travel & Transit, Government Services, Finance, Media, Connectivity, Meta/Tooling). Use when the user asks "what skills are in this plugin", "is there a skill for X in Israel", "which medication / shelter / municipality skill should I use", or when you (Claude) need a quick categorical map without reading every individual SKILL.md. Also lists which skills are orchestrators (chain other skills) vs. direct lookups, so you pick the right entry point.

Orchestrator for "is drug X available to me in Israel" questions. Chains the per-source lookup skills in the right order — start with the user's health fund (currently Maccabi via `maccabi-medicine-lookup`) for the practical answer (listed? in basket? copay? prior approval?), reach for the patient-facing pharma reference (`drug-co-il-lookup`) only if the user needs clinical context (active ingredient, leaflet, equivalents), and reach for the official Israeli Drug Registry (`israel-drugs-registry-lookup`) only if regulatory status is in question (is it currently registered, who holds the licence, is the registration cancelled). Use when the user asks something like "is X available", "can I get X on Maccabi", "is X covered", "is X still sold in Israel", or any open-ended availability/coverage question that doesn't already pin down which database to hit.

Use when Daniel wants to add a new skill to the Israel-Agent-Skills-Plugin repo based on rough / raw notes he pastes into the chat. Takes unstructured bullet points, URLs, field notes, Hebrew snippets and example pages, and turns them into a well-formed `skills/<skill-name>/SKILL.md` file that matches the conventions of existing skills in this repo (YAML frontmatter with `name` + rich `description` including trigger phrases, then a structured markdown body). Also syncs the new skill into the local plugin cache at `~/.claude/plugins/cache/danielrosehill/israel-agent-skills/<version>/skills/` so it is usable immediately, commits, and pushes. Trigger phrases: "add a skill to this plugin", "new skill for israel-agent-skills", "turn these notes into a skill", "scaffold a skill from my raw notes", "save this as a skill in the repo".

Use when another skill in this plugin reports a missing dependency (Python module, Playwright browser, CLI tool), or when the user wants to verify or set up the runtime environment for Israel-Agent-Skills. Checks for required tools and offers to install them. Trigger phrases - "set up environment for X skill", "playwright not installed", "install dependencies for israel skills", "fix missing module", "ModuleNotFoundError: playwright".

Use when the user wants to find upcoming conferences, professional events, summits, expos, or industry meetups happening in Israel — by topic (tech, AI, biomed, finance, marketing, HR, cyber, startup), by city (Tel Aviv, Jerusalem, Haifa), by date window, or in general ("what conferences are coming up in Israel", "any AI events in Tel Aviv next month", "כנסים בישראל", "אירועים מקצועיים", "tech conferences Israel"). Checks a curated whitelist of Israeli event aggregators FIRST (events.co.il, conferenceindex.org, IVC, ICX, dev.events) before falling back to general web search.

Use when the user wants the current Israel National Security Council (NSC) travel threat level / advisory for a specific country. Pulls the official rating, recommendation, area under threat, and background details from gov.il. Trigger phrases include "NSC threat level for X", "is it safe for Israelis to travel to X", "travel warning for X", "Israeli travel advisory for X", "what's the threat rating for X", "NSC recommendation on X".

Surface the load-bearing assumptions in a captured idea and the most likely objections an investor, customer, or skeptical advisor would raise. Produces an assumption-validation plan and an objection-handling brief. Use when the user wants to pressure-test an idea before committing time or capital.

Explore B2B vs B2C (and B2B2C, prosumer, marketplace, dev-tool) routings for a captured idea. Lays out pros and cons of each viable model and recommends the best fit given the idea, user context, and capital appetite. Use when the user is unsure which customer segment to target.

Brainstorm tweaks, additions, or pivots that could improve an idea's feasibility, market readiness, capital efficiency, defensibility, or speed-to-revenue. Produces a ranked list of variants with the trade-off each one buys. Use when an idea has been analysed and the user wants suggestions for how to make it stronger.

Capture a new business idea from text input into a structured workspace. Always preserves the raw input verbatim and offers optional formatted versions — executive summary, elevator pitch, technical deep-dive, and timeline/project plan. Use when the user wants to start a new idea workspace from a written description, brain-dump, or pasted text.

Capture a business idea from a voice memo / audio file. Transcribes the recording, preserves the raw transcript, then hands off to capture-idea so the user can optionally generate executive summary, elevator pitch, technical deep-dive, and timeline variants. Use when the user has an audio file or recording of an idea pitch.

Compare multiple captured ideas head-to-head across explicit dimensions — commercial prospect, speed to first revenue, capital intensity, fit-to-user, defensibility, social impact — and produce a ranked recommendation. Use when the user has 2+ ideas in the workspace and wants help choosing where to focus.

Run a multi-persona LLM-council review using Andrej Karpathy's original llm-council Python implementation. Clones the repo into a temp scratch dir, configures it for the user's idea, runs it, and copies outputs back into the idea workspace. Use when the user explicitly wants the canonical implementation rather than the native subagent variant.

Run a multi-persona LLM-council review of an idea using Claude Code subagents — six personas (Operator, Financier, Skeptic, Visionary, Customer Advocate, Strategist) each review the idea independently, then a chairman synthesizes. Runs entirely inside the Claude harness — no external code or repo clone. Faster path; use unless the user wants the original Karpathy implementation.

Add bleed margins to a PDF for commercial print shops that trim — extends the page size by the bleed amount on each side and shifts content to the new center. Most office digital printing does NOT need this; use only when sending to a print shop. Triggers on phrases like "add bleed", "add 3mm bleed", "prep for trim".

Generate a matching-size cover page with a title (and optional subtitle, author, date) and prepend it to a PDF. Triggers on phrases like "add a cover page", "prepend a title page", "make a cover for this PDF".

Overlay a diagonal text watermark (DRAFT, PRIVATE, CONFIDENTIAL, etc.) at 45° across every page in light red (or user-specified color), at low opacity so body text remains readable. Triggers on phrases like "add a DRAFT watermark", "stamp PRIVATE on every page", "watermark this PDF".

Burn a permanent footer label into every page of a PDF — CLIENT CONFIDENTIAL, PRIVATE, FAMILY DISTRIBUTION, DRAFT, EMBARGOED UNTIL ..., or custom text. User can choose font and size. Renders a PNG preview to verify layout before committing. Triggers on phrases like "add a CONFIDENTIAL footer", "burn in a footer", "stamp 'embargoed until' across the bottom".

Convert a color PDF to grayscale (black-and-white) for monochrome digital printing — saves toner and avoids color-mismatch issues. Triggers on phrases like "convert PDF to grayscale", "make it black and white", "remove color from PDF", "monochrome PDF".

Bundle one or more print-ready PDFs into a single "print job" folder with a manifest, ready to hand to a digital printer or share with collaborators. Triggers on phrases like "create a print job", "bundle these PDFs", "make a job folder for the printer".

Generate a formal print job order — a printer-facing document (PDF + JSON) that specifies files, copies, color instructions, paper, binding, finishing, special notes, and the customer's contact info. Drops it into a job folder so it's ready to hand to a digital printer or print shop. Triggers on phrases like "create a print order", "make a printer order sheet", "write up the job for the printer".

Downsample embedded images in a PDF to a target DPI (default 300 for print, 150 for proofs). Reduces file size and prevents printers from running out of memory on documents with huge embedded photos. Triggers on phrases like "downsample images", "shrink the PDF", "reduce image DPI", "the printer keeps choking on this PDF".

Inspect, pause, resume, and reset the Baloo file indexer. Use when search is missing files, indexing is hammering disk/CPU, or the user wants to add/remove indexed paths.

Pair, list, ping, find, and send files / SMS / clipboard via kdeconnect-cli to phones and other KDE Connect devices. Use for scripted phone↔desktop interactions.

Inspect and edit KGlobalAccel keyboard shortcuts (global hotkeys) on KDE Plasma. Use when the user wants to bind, unbind, or audit a Meta/Ctrl/Alt key combination, or troubleshoot a shortcut that stopped firing.

Read, clear, and push entries to the Klipper clipboard history via D-Bus. Use when the user wants to inspect what's been copied recently, clear sensitive history, or programmatically stage clipboard content.

List wallets, folders within a wallet, and entries within a folder. Use to enumerate what's stored in KWallet without revealing values.

Read a single password / map / binary entry from KWallet by wallet name, folder, and key. Triggers a user consent prompt the first time the calling app id is seen.

Check whether kwalletd is running, which wallets exist, whether the default wallet is open, and whether KWallet is enabled at all. Use as the first step before any other kwallet skill.

Write or update a password / map / binary entry in KWallet. Creates the folder if it doesn't exist. Use to seed credentials for KDE apps that don't have their own input flow.