「surface」の検索結果

Hunts for Windows persistence across autostart locations: Run keys, services, scheduled tasks, WMI event subscriptions, and startup folders, baselining them to surface anomalous or recently added entries. Activates for requests to hunt persistence, audit autostart extensibility points, or find malware autoruns on Windows.

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Builds Zeek-based network hunting analytics by writing scripts and analyzing Zeek logs (conn, dns, http, ssl, files) to surface long connections, rare JA3s, suspicious downloads, and beaconing. Activates for requests to build Zeek analytics, write a Zeek hunting script, or analyze Zeek logs for threats.

日本語の概要は準備中です。原文の説明を表示しています。

Compares two related malware samples to surface what changed between variants using section-level hashing, import-set differences, and fuzzy similarity scoring. Activates for requests to diff two samples, compare malware variants, or measure similarity between two binaries for variant tracking.

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Guide users through `pulp upgrade` — discover new CLI releases, interpret migration notes for the hop they're performing, and apply breaking-change fixes (CMake macro renames, API surface changes, config file moves). Handles "upgrade pulp", "what's new", "migrate my project", "show breaking changes", and the `/upgrade` slash command. Pairs with the embedded migration index shipped in the CLI binary.

日本語の概要は準備中です。原文の説明を表示しています。

Maintain Pulp's installed design-time agent capability manifest and public-surface ledger. Use when adding, removing, renaming, or materially changing public audio, MIDI, signal, timebase, or sequence APIs; registering a new algorithm for generators; changing capability support or deprecation state; or repairing agent-capabilities freshness, schema, fingerprint, tombstone, or installed-SDK tests.

日本語の概要は準備中です。原文の説明を表示しています。

Audio Unit v2 adapter work for Pulp — picking the right AU component type (aufx/aumf/aumi/aumu) and its matching entry macro, wiring MIDI input and output (including the aumi MIDI-processor adapter), sharing the base-class-free adapter surface, and avoiding the DAW-side component cache that silently masks repackaging.

日本語の概要は準備中です。原文の説明を表示しています。

Audio Unit v3 (AUAudioUnit) format adapter for Pulp — render-block wiring, parameter tree bridging, MIDI / sysex via AURenderEvent, sidechain pulls, state persistence, iOS extension surface, and the pitfalls discovered while wiring the adapter.

日本語の概要は準備中です。原文の説明を表示しています。

The measurement surface for ALL Pulp DSP and audio-pipeline work — read it BEFORE writing or gating DSP, not only when something already sounds wrong. Covers the C++ harness (signal generators, metrics, assertions, RenderScenario, contracts), the offline Audio Doctor (magnitude/frequency response, THD/THD+N, phase/group delay), and their Python sibling the Audio Quality Lab (tools/audio/quality-lab — null residual + alignment, LTAS log-spectral distance, spectral flux/centroid, HNR, Theil-Sen drift slope, Kaiser-sinc resampling, license-guarded corpus, regression-net ratchet). TRIGGER on AUTHORING work — "build/design an oscillator/filter/synth/effect", "add a DSP module", "what should the acceptance gate be", "how do I measure aliasing / anti-aliasing / alias floor", "null against a reference", "is this DSP correct", "choose a tolerance", "golden/regression corpus for audio", "measure drift or jitter", "A/B two renders" — AND on DEBUGGING work — "is there sound / no audio / I hear nothing", "does this filter/compressor/synth/delay produce the right signal", "prove the DSP / prove the contract", "measure the frequency response", "what's the THD / is it distorting", "what's the group delay / phase response / measured latency", "magnitude response curve", "render a test tone and assert", "audio regression", "64-frame works but 128 is silent", "sample-rate change pitch-shifted it", "describe what's in this buffer", "audio doctor", "compare before/after a DSP refactor". Reach for this BEFORE hand-rolling any FFT, null test, alias measurement, pitch tracker, or golden-render script — most of it already exists in one of the two lanes. Test/tool layer over HeadlessHost — deterministic, no audio device, no speakers. Off the realtime thread entirely.

日本語の概要は準備中です。原文の説明を表示しています。

Keep paperclip-docs in lockstep with the parent paperclipai/paperclip codebase. Detects code-surface changes (CLI, env vars, API routes, adapters, plugin SDK, schemas) and produces friendly-tutorial-voice doc updates. Two modes — `nightly` (tracks parent's default branch (currently `master`), targets the `nightly` branch, preview deploy) and `release` (on parent tag, merges nightly → main, tags, ships live). Trigger phrases: "sync docs", "update docs from paperclip", "/sync-docs", "check for paperclip changes", "is docs current".

日本語の概要は準備中です。原文の説明を表示しています。

Traces and documents signal paths, bus/aux architecture, and sidechain connections in audio systems. Surfaces hidden coupling between audio components. Use when the user asks to trace a signal chain, explain audio routing, understand an audio graph, locate sidechain sources, or describe how audio flows through a plugin or engine. Trigger on phrases like "trace this signal chain", "explain this audio routing", "what calls what in this audio graph", "where does the sidechain come from", "how does audio flow through this plugin".

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記憶システムからの切断。得られた知見を脳に書き戻し、表層の現実へと復帰する。

脳（記憶システム）から切断する。浮上。

End-of-story completion review. Reads the story file, verifies each acceptance criterion against the implementation, checks for GDD/ADR deviations, prompts code review, updates story status to Complete, and surfaces the next ready story from the sprint.

日本語の概要は準備中です。原文の説明を表示しています。

Generate a soak test protocol for extended play sessions. Defines what to observe, measure, and log during long play sessions to surface slow leaks, fatigue effects, and edge cases that only appear after sustained play. Primarily used in Polish and Release phases.

日本語の概要は準備中です。原文の説明を表示しています。

Read all open bugs in production/qa/bugs/, re-evaluate priority vs. severity, assign to sprints, surface systemic trends, and produce a triage report. Run at sprint start or when the bug count grows enough to need re-prioritization.

日本語の概要は準備中です。原文の説明を表示しています。

Unity 6 AI and navigation guide. Use when working with NavMesh, pathfinding, NavMeshAgent, NavMeshSurface, NavMeshObstacle, off-mesh links, or Unity Sentis (ML model inference). Covers AI navigation package, runtime NavMesh baking, and common AI patterns like state machines and behavior trees. Based on Unity 6.3 LTS documentation.

日本語の概要は準備中です。原文の説明を表示しています。

Ableton Live Object Model (LOM) API reference for Python Remote Scripts and control surface development.

日本語の概要は準備中です。原文の説明を表示しています。

Tend the Allium garden. Use when the user wants to write, edit, update, add to, improve, clarify, refine, restructure, fix or migrate Allium specs. Covers adding entities, rules, triggers, surfaces and contracts, fixing syntax or validation errors, renaming or refactoring within specs, migrating specs to a new language version, and translating requirements into well-formed specifications. Pushes back on vague requirements.

日本語の概要は準備中です。原文の説明を表示しています。

Full-funnel paid advertising operations for B2B SaaS. Use this skill for PPC strategy, Google Ads optimization, LinkedIn Ads, social media advertising, programmatic buying, creative strategy, attribution modeling, budget allocation, budget pacing and planned-vs-delivered reconciliation, audience overlap and campaign self-competition audits, suppression lists, ROAS improvement, media spend optimization, and the media no auction sells — newsletter and podcast sponsorships, community and industry-publication placements, paid review-site listings on G2 and Capterra, and pay-per-lead content syndication. It also covers buying on the AI answer surface — ads inside Google AI Overviews and AI Mode that existing Search, Shopping and Performance Max campaigns already serve into with no opt-out, no placement targeting and no segmented reporting, and ChatGPT Ads and Microsoft Copilot as separate opt-in platforms with their own plan-tier reach limits, no negative keywords, and a landing-page crawler gate. It also owns the conversion signal the bidding algorithms learn from — CRM pipeline stages (SQL, opportunity, closed-won) sent back to Google Ads, LinkedIn, Meta and Microsoft Ads through offline conversion import, enhanced conversions for leads, the Google Data Manager API and the LinkedIn Conversions API, with click-ID capture, stage values, dedupe, EEA consent signals and retractions. It also gates connected TV (CTV) and streaming video for B2B — whether a reach medium belongs in the plan, how a vendor ties a TV household to a target account (member data, IP-to-account graph or contextual), the server-side ad insertion (SSAI) fraud questions, Programmatic Guaranteed deals, and a holdout lift test because CTV has no click. It also runs person-led paid social — LinkedIn Thought Leader Ads and Meta partnership ads that put spend behind an employee's or creator's post — on a paid-usage term, an in-post disclosure check and an end-date register, because the platform approval carries no term. Also triggers on: CTV, connected TV, OTT, streaming TV ads, should we run CTV, LinkedIn CTV, B2B CTV, account-based CTV, SSAI fraud, thought leader ads, boost an employee's post, sponsor a creator's post, partnership ads, whitelisting, creator usage rights, PPC, Google Ads, LinkedIn Ads, social ads, programmatic, ad creative, attribution, media budget, paid campaigns, ROAS, CPA, ad spend, newsletter sponsorship, podcast sponsorship, community sponsorship, sponsor a newsletter, content syndication, pay-per-lead, cost per lead vendor, media kit, rate card, insertion order, direct buy, publisher partnership, make-good, G2 paid listing, Capterra ads, review site advertising, sponsorship ROI, budget pacing, we underspent our budget, are our campaigns competing with each other, audience overlap, self-competition, campaign cannibalization, suppression list, exclusion list, ad frequency across channels, how many ad accounts do we have, ads in AI Overviews, AI Mode ads, ChatGPT Ads, OpenAI Ads Manager, Copilot ads, conversational ads, should we advertise on ChatGPT, can we buy our way into the AI answer, our ads are showing in AI Overviews and we cannot report on it, context hints, OAI-AdsBot, our ad landing page fails review, robots.txt is blocking our ads, our paid leads are junk, Google Ads is optimizing for the wrong leads, offline conversion import, OCI, enhanced conversions for leads, send CRM stages back to Google Ads, upload SQLs to LinkedIn, LinkedIn Conversions API, LinkedIn CAPI, Meta conversion leads, CRM to ad platform, gclid, li_fat_id, msclkid, value-based bidding, optimize for pipeline not form fills, low match rate, conversion lag.

日本語の概要は準備中です。原文の説明を表示しています。

Developer marketing and developer relations for B2B SaaS with technical audiences. Use this skill when the buyer or user is a developer: documentation as a marketing surface, quickstarts and time-to-first-call, SDKs and sample apps, developer community and DevRel programs, open-source strategy, and technical content that survives engineer scrutiny. Also triggers on: developer marketing, DevRel, developer relations, developer experience, DX, docs, documentation, quickstart, SDK, API marketing, open source strategy, developer community, technical content, dev audience, hacker news, engineering blog.

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Use when a task needs the judgment of a Dragline and Excavating/Loading Machine Operator in surface mining — converting a rated bucket capacity into bank cubic yards moved per shift, deciding whether a swing angle or spoil-placement plan needs to be flagged to pit engineering, matching loading pass count and payload to a haul truck's rated capacity, checking ground bearing conditions before walking or tracking a machine onto fill or spoil, or reading a berm/highwall condition against MSHA thresholds.

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Use when a task needs the judgment of a Cooling/Freezing Equipment Operator — calculating freezing time for a new product thickness via the thickness-squared relationship rather than assuming linear scaling, verifying freezing completion by actual core/thermal-center temperature rather than surface temperature or elapsed time, recognizing a temperature plateau as expected latent-heat removal rather than a malfunction, or matching belt speed/residence time to the calculated freezing time requirement.

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Use when a task needs the judgment of a Computer Numerically Controlled (CNC) Tool Programmer — calculating stepover from a scallop-height/surface-finish spec instead of picking one by feel, deciding whether a toolpath needs a dry run before cutting material on an unfamiliar post-processor/machine pairing, verifying datum consistency across multiple part setups, or diagnosing why cycle time jumped after a "minor" parameter change.

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Use when a task needs the judgment of a Coating/Painting/Spraying Machine Operator — calculating wet film thickness from a target dry film thickness and the coating's percent volume solids, deciding whether flash-off time can be shortened to increase throughput, verifying cure by actual part temperature rather than oven setpoint, or tracing an adhesion failure back to surface prep rather than the coating application.

日本語の概要は準備中です。原文の説明を表示しています。