Total 57,464 skills
Showing 12 of 57464 skills
The idea-system craft — never run out of content ideas by running a system instead of waiting for inspiration. Use when someone is out of ideas, stares at a blank calendar, asks where good ideas come from, wants an idea bank/backlog, feels their AI-generated ideas sound like everyone else's, or thinks their niche is "boring." Uses the SPARK framework. Reads brand-profile + social-strategy + content-pillars + audience-research first. The audience is the idea engine (comments/DMs/FAQs clustered into themes); AI expands real signals, it doesn't discover them; systems beat muses; trends are a timing filter, not a source. The agent clusters/expands/scores; the HUMAN supplies proprietary signals and decides; WoopSocial publishes the content, not ideas. Never rewords competitor posts, invents audience questions, or fabricates probe results. Distinct from social-strategy/content-pillars, audience-research, cross-platform-repurposing/ content-recycling, and the format skills.
Use when the user asks to "analyze competitors" or "竞品分析"; benchmarks competitor keywords, content, backlinks, AI citations, and traffic share into strengths, weaknesses, and an action plan. Not for a pairwise topic-coverage gap map — use content-gap-analysis. 竞品分析/竞争对手
A skill for writing and revising Japanese business documents to make them easy to read and understand. It can be used for creating and proofreading business documents such as meeting minutes (including transcribing to minutes), research/analysis reports, internal guides/manuals, research notes, discussion papers, proposals, reports, emails, and slide outlines, as well as following instructions like 'write from the conclusion', 'clarify the argument', 'keep headings concise', and 'explain technical terms in an easy-to-understand way'. It also supports removing AI-like tones (direct, indirect, or colloquial feedback such as 'AI-like', 'unnatural', 'make it more natural Japanese', 'mechanical', 'make it sound human', 'monotonous', or phrasing like 'it would be possible to...', as well as cases where the document was said to be written by AI or suspected of being so), improving hard-to-read or unclear sentences (such as incorrect word order, long sentences, unclear meaning, incorrect comma placement, etc.), writing new note articles, blog posts, and essays (including requests to write from scratch on any topic), rewriting and polishing existing sentences, diagnosing and scoring AI-like tones (requests without rewriting, such as 'Did AI write this?', 'Score the AI-like tone', 'Judge how AI-like this is'), and requests to learn and profile one's own writing style (including requests to write in one's own style by reading past sentences). It also addresses readability principles such as removing forbidden words, avoiding monotonous rhythm, homogeneous paragraph structure, literal translation of English syntax, as well as word order, commas, one meaning per sentence, and the distance between subject and predicate. The structuring of technical documents or formatting of Markdown itself (such as one sentence per line, quote blocks, footnote notation, etc.) is not covered—this falls under another skill, and this skill specializes in the naturalness, readability, and comprehensibility of text.
Calculate accurate sales tax and VAT at checkout using TaxJar or Avalara, with nexus management for multi-state and international compliance
Analyze survey results into actionable PM insights. Produces persona segmentation, hypothesis validation status, thematic clustering of open-text responses, statistical confidence labels, prioritized recommendations, and what-NOT-to-conclude warnings. Refuses to overstate statistical significance from weak samples or biased instruments.
Compute and report task-correct held-out metrics for a trained medical-imaging model — segmentation (Dice plus a boundary metric such as HD95 or NSD, per structure), classification (AUROC plus AUPRC and sensitivity/specificity with bootstrap CIs at the deployment prevalence), detection (FROC or mAP with a stated IoU criterion), interactive/promptable segmentation (the interaction-count, convergence, and per-case-time axes a static Dice omits), or generative/synthesis image evaluation (similarity plus the downstream-task efficacy similarity alone cannot establish) — plus calibration and subgroup slices. Emits a per-case results table that analyze-stats turns into publication tables, and gates the metric choice against Metrics Reloaded, CLAIM 2024, and Park et al. 2024 (no pixel accuracy for segmentation, no bare accuracy under imbalance, no static Dice for an interactive method, no similarity-only claim for a generative model). Numbers come only from executed code, never hand-typed.
Build a reference system that returns the right reference in under 60 seconds. Use when setting up a design reference library, reorganizing existing collections, or helping teams build shared reference systems.
Renders a Structurizr workspace as a Claude artifact or a static site, using the Renderizr CLI. Use when the user wants to see, share, publish or hand over a C4 architecture model — "show me the architecture", "turn this workspace into an artifact", "publish these diagrams" — or mentions Renderizr, workspace.json or artifact.html.
Brand Registry enrollment guide — eligibility, application, benefits, A+ Content access, brand protection tools
Filter an existing audience or lead list against your ICP and split it into ready-to-sequence segments. Use when someone already has a list of people — an audience in their sales tool, a CSV or CRM export, event or webinar attendees, registrants, a Sales Navigator import, a newsletter or community export — and wants to know who is worth contacting. Triggers on: 'filter this audience against my ICP', 'who in this list matches my ICP', 'clean up this lead list', 'score these leads', 'qualify my signups', 'segment this audience', 'is my audience on-ICP', 'filter my webinar attendees', 'split this audience by ICP fit', 'remove the bad leads'. For SDRs, BDRs, RevOps, growth, demand gen and founders doing list qualification, ICP refinement, post-event follow-up or audience cleanup. Checks whether the data can support the ICP before filtering, sorts every lead into ICP match / needs review / no match, strips out your own team and competitors, and never silently drops anyone. Maintained by La Growth Machine.
Generate your Weekly Performance Advisor dashboard from your La Growth Machine data: a two-tab cockpit (To do + Weekly performance) that flags campaigns to fix, sorts replies by urgency, and tracks reply volume week over week. It pulls only YOUR live LGM data, scores each running campaign against baked 3-zone benchmarks, classifies your untagged replies, and renders a live artifact you can re-open every Monday. Use when the user wants a weekly outbound performance dashboard, a Monday cockpit, campaign health at a glance, "how are my campaigns doing this week", "who do I need to reply to", or a reply-triage + campaign-health view. Triggers on: 'weekly performance dashboard', 'my outbound cockpit', 'weekly performance advisor', 'campaign health this week', 'how are my campaigns doing this week', 'my Monday cockpit'. First run does a short setup (detect + connect LGM, pick the identity, optional deal layer); every run after that just rebuilds the dashboard. Maintained by La Growth Machine.
Example-first AI development guide for Hile @hile/* packages. Use when building or editing Node.js/TypeScript services with @hile/core, @hile/http, @hile/http-next, @hile/rsc, @hile/model, @hile/context, @hile/typeorm, @hile/ioredis, @hile/cache, @hile/message-*, @hile/micro, @hile/reloader, Redis reliability packages, @hile/schedule, or create-hile.