Results for “pas”

Creates, analyzes, and visualizes complex networks and graphs in Python with NetworkX. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks, or visualizing topologies — applicable to social, biological, transportation, citation, and any pairwise-relationship networks. This is classical graph analytics, not deep learning — for training graph neural networks (GCN/message passing, node/edge/graph classification on Cora-style data) use alterlab-torch-geometric instead. Part of the AlterLab Academic Skills suite.

Composite skill — one-pass cleanup of stale local branches, dead worktrees, merged branches, and abandoned remote PR branches. Chains `git fetch --prune` → `clean_gone` (kill [gone] branches) → worktree prune + offer-to-remove dead worktrees → list-and-delete branches merged to main and release → delete remote PR branches whose PRs merged >7 days ago. Use instead of running `clean_gone` alone — that only catches half the rot. Daily-friction composite; fires on "clean up branches", "branch hygiene", "stale worktrees", and on session start when local branch count > 30.

This skill should be used when a SKILL.md file needs compression, deduplication, or token reduction. It provides an embedding-based compression pipeline that detects and removes redundant chunks within SKILL.md files using local embeddings (all-MiniLM-L6-v2). Two-pass approach: (1) free intra-skill deduplication via cosine similarity clustering, (2) optional LLM-judged graded eval to detect pretraining overlap. Typical result: 25-46% token reduction with zero quality loss. This skill is not intended for editing skill content, creating new skills, routing optimization, or cross-skill deduplication.

Opens a conversational planning session for a feature, bug, or ticket. Investigates the repo, discusses the approach with the user until a solution is agreed, and only then writes the plan to docs/plans/. Use whenever the user invokes it, describes a problem to solve, pastes a ticket, mentions an incident, or asks to plan a non-trivial change. Also on "plan this", "analyze this first", "what would we need to touch", "let's start with this" — or in Spanish "planeá", "analizá esto antes", "qué habría que tocar", "arranquemos con esto".

Turn a generic product tour into a buyer-specific demo that only shows what they told you hurts. Maps every feature you plan to show to a problem the buyer actually stated, writes the "so what" for each moment, and flags the trap of feature-dumping before you fall into it. Built for B2B sales teams, customizable to your product and your discovery. Trigger on "build a demo script", "prep for the demo", "what should I show", "map features to pain", "stop me from feature dumping", or any pre-demo planning pass.

Generate text-to-video with HappyHorse 1.0 on RunComfy. Documents HappyHorse 1.0's strengths (#1 on Artificial Analysis Video Arena, native 1080p with in-pass synchronized audio, multi-shot character consistency, 6-language prompt support), the duration / aspect-ratio / resolution schema, and when to route to Wan 2.7 / Seedance 2 / LTX 2 instead. Calls `runcomfy run happyhorse/happyhorse-1-0/text-to-video` through the local RunComfy CLI. Triggers on "happyhorse", "happy horse", "happyhorse 1.0", "happyhorse video", or any explicit ask to generate video with this model.

Generate text-to-video with HappyHorse 1.0 on RunComfy. Documents HappyHorse 1.0's strengths (#1 on Artificial Analysis Video Arena, native 1080p with in-pass synchronized audio, multi-shot character consistency, 6-language prompt support), the duration / aspect-ratio / resolution schema, and when to route to Wan 2.7 / Seedance 2 / LTX 2 instead. Calls `runcomfy run happyhorse/happyhorse-1-0/text-to-video` through the local RunComfy CLI. Triggers on "happyhorse", "happy horse", "happyhorse 1.0", "happyhorse video", or any explicit ask to generate video with this model.

Generate text-to-video with HappyHorse 1.0 on RunComfy. Documents HappyHorse 1.0's strengths (#1 on Artificial Analysis Video Arena, native 1080p with in-pass synchronized audio, multi-shot character consistency, 6-language prompt support), the duration / aspect-ratio / resolution schema, and when to route to Wan 2.7 / Seedance 2 / LTX 2 instead. Calls `runcomfy run happyhorse/happyhorse-1-0/text-to-video` through the local RunComfy CLI. Triggers on "happyhorse", "happy horse", "happyhorse 1.0", "happyhorse video", or any explicit ask to generate video with this model.

Generate cinematic short-form video with ByteDance Seedance 2.0 Pro on RunComfy. Documents Seedance 2.0 Pro's strengths (multi-modal references — up to 9 images, 3 videos, 3 audio — synchronized in-pass audio with natural lip-sync, cinematic motion refinement), the 4–15s duration schema, and when to route to HappyHorse 1.0 / Wan 2.7 / Kling instead. Calls `runcomfy run bytedance/seedance-v2/pro` through the local RunComfy CLI. Triggers on "seedance", "seedance 2", "seedance v2", "seedance pro", "bytedance video", or any explicit ask to generate video with this model.

Generate cinematic short-form video with ByteDance Seedance 2.0 Pro on RunComfy. Documents Seedance 2.0 Pro's strengths (multi-modal references — up to 9 images, 3 videos, 3 audio — synchronized in-pass audio with natural lip-sync, cinematic motion refinement), the 4–15s duration schema, and when to route to HappyHorse 1.0 / Wan 2.7 / Kling instead. Calls `runcomfy run bytedance/seedance-v2/pro` through the local RunComfy CLI. Triggers on "seedance", "seedance 2", "seedance v2", "seedance pro", "bytedance video", or any explicit ask to generate video with this model.

Generate cinematic short-form video with ByteDance Seedance 2.0 Pro on RunComfy. Documents Seedance 2.0 Pro's strengths (multi-modal references — up to 9 images, 3 videos, 3 audio — synchronized in-pass audio with natural lip-sync, cinematic motion refinement), the 4–15s duration schema, and when to route to HappyHorse 1.0 / Wan 2.7 / Kling instead. Calls `runcomfy run bytedance/seedance-v2/pro` through the local RunComfy CLI. Triggers on "seedance", "seedance 2", "seedance v2", "seedance pro", "bytedance video", or any explicit ask to generate video with this model.

Submit one or more wandb-logged training/finetuning runs to the HPC scheduler. `WANDB_PROJECT` is fixed per repo (snake_case basename); `WANDB_RUN_GROUP` is picked per invocation. The training script must take the experiment/group name as a config key (e.g. Hydra `meta.experiment_name=<group>`); the skill passes it on the command line. The working tree is committed first so each run pins to a real SHA. Delegates SLURM/PBS templating to `cluster-instructions`. Use when the user asks to submit, queue, launch, or kick off a wandb training/finetuning job.

Audit, improve, and compress every skill in the repo using live research. Load when the user asks to improve skills, audit the skill library, upgrade existing skills, refresh with new research, do a skill health check, or says "improve all skills", "update the skill library", "skill audit", or "run an improvement pass". Applies live domain research, fixes structural gaps, checks for skill linking opportunities, then rewrites and resizes each skill. Supports TARGETED mode (`TARGET=<skill> [SKIP_RESEARCH=true]`) for single-skill fixes, including learn-from-chat restructure escalations. All skills are in scope including meta skills.

Self-contained code review checklist — formatting, type safety, duplication, readable conditions, logic-out-of-UI, test coverage, comment quality. Adapts to whatever tooling the project actually has (skips Prettier/TypeScript/test-runner checks if unconfigured). Use before merging, after completing a feature, or any time you want a second pass on code quality. In Claude Code, prefer the official `code-review` skill or `pr-review-toolkit`/`feature-dev` code-reviewer agents instead — both are real, installed, and go deeper than this checklist. This copy exists for Codex/Cursor portability, where those agents aren't available.

Composite skill — configure a fresh or under-configured repo for the release-branch workflow in one pass. Creates the `release` branch on origin, seeds `CHANGELOG.md` (Keep-a-Changelog format), drops in `.claude/dep-sweep-config.json` + `.claude/branch-hygiene-config.json` + a `release-cadence.md` standard stub, opens a `chore/repo-bootstrap` PR to main. Use instead of manually setting these up before the first `/pr-to-release` — without this, none of the release-branch composites can fire. Idempotent: skips any artifact that already exists. Replaces ad-hoc "set up the new repo" scripts.

Use when the user wants to clone or adapt a UI pattern from any website into gotcontext.ai, or asks to "build something like X", "make our nav look like Y", or "clone that component". Prefer aura.build Pro when available; without a Pro subscription, skip Aura and go straight to Phase 2.5 direct rebuild. Aura's clone is now NATIVE — paste a URL or drag a screenshot into aura.build and it generates React/Tailwind directly; the Anima/Chrome-extension flow is only a fallback for login-gated pages Aura can't fetch server-side.

Agent Media OS, the single skill for every media need in a HyperFrames project. Resolve BGM, SFX, image, icon, brand logo, voice, color grade, or LUT into a frozen local file or paste-ready block + ledger record (one verb, `resolve`); generate via TTS / music / image models when the catalog misses; produce voiceover, transcription, captions, and background removal through one shared audio engine; operate on media (cut / reframe / transform); and reuse assets across projects. Also use for vague feedback that real footage looks dark, flat, boring, should feel retro/camcorder/print/ASCII, needs privacy, or needs a media reveal.

Use this skill when the user asks about Hours of Service (HOS) rules under 49 CFR 395 — the 11-hour driving limit, 14-hour on-duty window, 60/70 hour rule, 30-minute break, 10-hour off-duty reset, 34-hour restart, sleeper berth provisions, split sleeper berth, short-haul exemption (150-air-mile), agricultural exemption, adverse driving conditions, ELD malfunction handling, personal conveyance, yard moves, or anything related to driver duty status. Cite specific 49 CFR 395 subsection. If the question involves a non-standard operation (passenger carrier, oilfield, agricultural, military), confirm which set of rules applies.

Use this skill when the user asks anything that touches US Department of Transportation (DOT) or Federal Motor Carrier Safety Administration (FMCSA) regulation for commercial motor vehicles (CMVs) — including who's regulated, MC vs DOT number differences, operating authority, BOC-3 process agents, MCS-150 biennial updates, intrastate vs interstate distinctions, exemptions, or pointing to the right CFR section. Cite the actual regulation when answering. Don't guess; if you're not sure which Part applies, ask the user to clarify the operation type (for-hire vs private, passenger vs property, intra vs interstate, hazmat, gross weight rating).

Requires python3, and AISA_API_KEY. Uses the supplied AISA_API_KEY to send requests to https://api.aisa.one/apis/v1/twitter. Native-first ClawHub plugin for `twitter`. Ships the packaged AIsa skill with an `openclaw.plugin.json` manifest and a Claude-compatible bundle fallback. Searches and reads X (Twitter): profiles, timelines, mentions, followers, tweet search, trends, lists, communities, and Spaces. Publishes posts, likes/unlikes tweets, and follows/unfollows users after the user completes OAuth in the browser. Use when the user asks about Twitter/X data, social listening, posting, or interacting with tweets/users without sharing account passwords.

Talk to customers without leading them using Mom Test rules: discuss their life not your idea, ask about specifics in the past, and talk less. Use when the user mentions "customer interviews", "validate my idea", "users say they want it but dont buy", "leading questions", "The Mom Test", "customer feedback bias", or "interview script". Also trigger when preparing user research questions, interpreting ambiguous customer feedback, or designing customer discovery processes that avoid false positives. Covers commitment and advancement, avoiding compliments, and extracting signal from noise. For product-market fit, see jobs-to-be-done. For rapid prototype testing, see design-sprint.

Audits and repairs Markdown link health across a skills repo via a four-tier pipeline (config hardening, intra-repo file-ref fixes, external URL substitutions, residual exclusions) and enforces a Tier 3 substitution guardrail that prevents regressions of previously-passing links; designed for lychee-based GitHub Actions link checkers but generalizes to markdown-link-check and similar tools. Use when the request mentions link audit, dead links, link health, lychee, broken links, link checker, markdown link audit, link-health audit, 404 audit, check-links failing, CI link-check, or 連結健檢, 死鏈, 失效連結, 斷鏈檢查. Part of the AlterLab Academic Skills suite.

Turn a target account list into a real account-based play, not a spray. It tiers the accounts, sets the research angle per tier, builds the multi-thread across marketing and sales, and orchestrates the touches so the account feels one coordinated motion instead of a rep and a marketer working past each other. Built for B2B revenue teams, customizable to your CRM and your channels. Trigger on "build an ABM play", "account-based plan for this list", "how do I run ABM on these accounts", "tier my target list", "coordinate marketing and sales on these accounts", or any account-based planning request.

Review a built frontend against its chosen direction, catch drift back to generic AI defaults, enforce state coverage, ethical patterns, UX heuristics, and polish, and check contrast with APCA (not the legacy WCAG ratio). Produces specific, prioritized fixes — never vibes-based feedback. Works with pasted screenshots or Playwright MCP automated capture. Load when the user asks to review a UI, audit a design, check if a frontend looks generic or vibecoded, evaluate visual quality or polish, says "review this UI", "is this design good", "audit my frontend", "does this feel like [product]", "design QA", or when frontend-design routes here. Sub-skill of frontend-design.

Analyze raw prompts, identify intent and gaps, match ECC components (skills/commands/agents/hooks), and output a ready-to-paste optimized prompt. Advisory role only — never executes the task itself. TRIGGER when: user says "optimize prompt", "improve my prompt", "how to write a prompt for", "help me prompt", "rewrite this prompt", or explicitly asks to enhance prompt quality. Also triggers on Chinese equivalents: "优化prompt", "改进prompt", "怎么写prompt", "帮我优化这个指令". DO NOT TRIGGER when: user wants the task executed directly, or says "just do it" / "直接做". DO NOT TRIGGER when user says "优化代码", "优化性能", "optimize performance", "optimize this code" — those are refactoring/performance tasks, not prompt optimization.

Co-fold biomolecular complexes with Boltz-2, an open AlphaFold3-style model — predict protein + ligand (SMILES/CCD), protein + nucleic-acid, and multi-chain structures in one pass, with binding-affinity prediction. Use when folding a protein together with a small-molecule ligand, predicting a holo (ligand-bound) complex or its binding affinity, or co-folding protein–DNA/RNA assemblies. For protein-only or protein–protein folding without ligands prefer alterlab-alphafold; for antibody–antigen complexes prefer alterlab-chai; to dock a ligand into a FIXED receptor structure prefer alterlab-diffdock; to look up an existing structure prefer alterlab-pdb. Part of the AlterLab Academic Skills suite.

Sharpens and stress-tests an existing plan file through multiple codebase-grounded review passes, editing it in place and recording every finding and iteration in cross-referenced companion files. Use this skill whenever the user wants to iterate on, refine, tighten, or improve a plan. Also use it when the user asks to verify, validate, or confirm feasibility of an approach. Does not implement plan steps, write test plans, review code, or investigate bugs, and does not generate new plans from scratch — use plan-a-feature for a new plan. Runs its review rounds to completion without pausing between them; to review each round as it lands, use pairing.

Run Mom Test–style customer-discovery interviews to validate or kill an unbuilt idea — generate a non-leading interview guide, conduct or coach the conversations, and synthesize signal vs compliments. Load when the user asks to do customer discovery, run problem interviews, validate an idea with users, run a Mom Test, design an interview guide, or says "talk to customers", "validate the problem", "interview users", "Mom Test this", "did real users want it", "synthesize my interviews", "I just talked to N people". Sub-skill of `venture-exploration`. Hard-bans "would you use this?", solution-pitching, friend/family-only ICP, and treating compliments as validation. Calls `secure-*` before synthesizing any pasted external transcripts.

>- Run automatic SPICE simulations on subcircuits detected from KiCad schematic analysis — validates filter frequencies, divider ratios, opamp gains, LC resonance, and crystal load capacitance. Supports ngspice, LTspice, and Xyce (auto-detected). Generates testbenches, runs batch mode, produces structured pass/warn/fail report. Use when the user asks to simulate, verify, or validate any analog subcircuit — RC filters, LC filters, voltage dividers, opamp circuits, crystal oscillators. Also for "simulate my circuit", "run spice", "verify with simulation", "check my filter cutoff", "does this divider give the right voltage", "what's the bandwidth of this opamp stage". Consider suggesting simulation during design reviews when the schematic analyzer reports simulatable subcircuits and a SPICE simulator is available.

Never show the user a first draft. Run every writing task through a self-critique loop — draft, attack the draft as the harshest reviewer in the room, rewrite, and repeat until a full review pass finds zero flags — then return only the final plus a change log. Use for any writing the user actually cares about: emails, LinkedIn posts, newsletters, docs, announcements, client messages. Trigger whenever the user says 'run the loop', 'self-critique this', 'make it bulletproof', 'don't give me a first draft', 'be brutal', or hands over a task where quality matters more than speed. This is a single-agent loop; for the three-agent version use the-team.

Reverse engineering de diseños Figma para generar especificaciones técnicas completas listas para implementar en código. Usar cuando el usuario comparte capturas, exports o descripciones de un diseño en Figma y quiere documentarlo técnicamente, extraer tokens de diseño, entender la estructura de layouts, o preparar una spec para que un desarrollador o Claude Code lo implemente. También usar cuando el usuario dice "reverse engineering del diseño", "documenta este Figma", "quiero implementar este diseño", "dame las propiedades CSS de este diseño", "convierte este diseño a código", o cuando comparte pantallazos de Figma (layers, propiedades, canvas). Activar también cuando el usuario quiere crear documentación técnica de un diseño existente antes de pasarlo a Claude Code.

Auto-audit any website end-to-end — technical health, SEO basics, broken links, mobile rendering, design quality, copy clarity, and conversion readiness — producing a scored, evidence-backed report. Two modes: PROSPECT mode (fast audit of a lead's site to generate evidence for outreach; emits a portable audit_packet JSON other tools can consume) and QA mode (deep pre-launch / post-launch gate on a site you built, with pass/fail checklist). Use whenever the user asks to "audit this site", "run a website audit", "what's broken on this site", "check this prospect's website", "QA this build", "is this site ready to launch", or provides a URL asking what works and what doesn't.

Wydruki i raporty w Soneta (enova365, Triva) — pliki .repx (DevExpress XtraReports, serializowany XML). Sięgaj przy KAŻDYM zadaniu z wydrukiem/raportem: faktura, dokument, deklaracja, lista, zestawienie; utworzenie, przeróbka lub poprawa .repx (też z załącznika); pytanie „jak w wydruku zrobić X”. Typowe X: podpięcie danych (lista, dokument z pozycjami, master-detail, podraport), podział stron, kolumna Lp, tabele, grupowanie i sumy, formatowanie warunkowe, kwoty, nakładanie wartości na skan formularza, nagłówek/stopka/podpisy, arkusz stylów (.repss), rejestracja wydruku. Wyzwalają też pojęcia: XtraReportsLayoutSerializer, StyleSheetSerializer, pasma (DetailBand/DetailReportBand/GroupHeaderBand/SubBand), kontrolki (XRLabel/XRTable/AmountLabel), BusinessDataSource/DataKind, ReportContext, ExpressionBindings/Summary/CalculatedFields/FilterString, [assembly: DxReport], ReportSnippet/[DxBind]. Wystarczy „wydruk”, „raport” lub „.repx” w kontekście Soneta. NIE dla: business.xml, form.xml, SQL, Excel, Word .dotx.

Discover OPC UA servers and create client connections in MATLAB using opcuaserverinfo, opcua, connect, setSecurityModel, and certificate trust functions. Use when discovering OPC UA servers on the network, connecting to OPC UA servers, authenticating with username/password or certificates, configuring security modes, handling certificate trust errors, fixing hostname mismatch warnings, troubleshooting connection failures or empty discovery results, or inspecting an OPC UA certificate (.der or .pem) for compliance issues. Trigger on: opcuaserverinfo, OPC UA discovery, find OPC UA servers, LDS setup, opcua, opc.ua.Client, connect OPC UA, OPC UA client, OPC UA security, OPC UA certificate trust, OPC UA certificate inspection, setSecurityModel, opc.ua.trustServerCertificate, opc.ua.exportClientCertificate, Industrial Communication Toolbox, OPC UA server connection, OPC UA server discovery.

Update Han plugin documentation so every skill, agent, guidance doc, index, and cross-reference is current and accurate. On a non-default branch, scopes the pass to entities the branch actually touched. On the default branch, performs a full documentation sweep across the whole plugin. Use when updating, refreshing, syncing, auditing, or verifying Han's docs after changing skills, agents, references, or top-level guidance — including "update the docs", "doc sweep", "refresh documentation", "audit the docs", "make sure the docs are current". This is a repository-maintenance skill for the Han repo itself, not a general documentation skill — use /project-documentation to document features in arbitrary projects, /han-release to cut a release (and update CHANGELOG), and /update-pr-description for PR bodies.

Run the Ouroboros specification-first development loop: reduce ambiguity with a Socratic interview grounded in live git data (commits, churn, contributors), freeze an immutable seed/spec, render the execution plan through spec-kit (/speckit.plan → /speckit.tasks), execute against that contract through cli-anything agent-native CLI harnesses (cli-hub, --json evidence), verify before claiming success, and keep looping until completion is actually verified. Use when the user wants spec-first clarification, git-aware interviews, immutable requirements, drift-aware implementation, harness-driven execution, or a persistent completion loop that should keep going until tests / checks / acceptance criteria pass. Triggers on: ooo, ouroboros, interview, seed, run workflow, evaluate, evolve, ooo ralph, specification first, socratic interview, git-aware interview, ambiguity reduction, execution plan, cli harness execute, persistent completion.