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cccskills

「capture」の検索結果

1,236 件 ・ 関連度順

概要と使いどころ

form-cro

無料

When the user wants to optimize any form that is NOT signup/registration — including lead capture forms, contact forms, demo request forms, application forms, survey forms, or checkout forms. Also use when the user mentions "form optimization," "lead form conversions," "form friction," "form fields," "form completion rate," or "contact form." For signup/registration forms, see signup-flow-cro. For popups containing forms, see popup-cro.

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。

danstrem2/clawdbot-skill-master-pack22026年2月1日 更新

camsnap

無料

Capture frames or clips from RTSP/ONVIF cameras.

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。

danstrem2/clawdbot-skill-master-pack22026年2月1日 更新

Create product demo videos by automating browser interactions and capturing frames. Use when the user wants to record a demo, walkthrough, product showcase, or interactive video of a web application. Supports Playwright CDP screencast for high-quality capture and FFmpeg for video encoding.

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。

johnalbertini14-glitch/openclaw-skills22026年2月26日 更新

Human-in-the-loop CAPTCHA solving with two modes: screenshot (default, zero infrastructure) and token relay (requires network access). Screenshot mode captures the page with a grid overlay, sends it to the human, and injects clicks based on their reply. Token relay mode detects CAPTCHA type + sitekey, serves the real widget on a relay page for native solving, and injects the token via CDP.

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。

johnalbertini14-glitch/openclaw-skills22026年2月26日 更新

Deep bug analysis to break the fix-forget-repeat cycle. Analyzes root cause category, why fixes failed, prevention mechanisms, and captures knowledge into specs. Use after fixing a bug to prevent the same class of bugs.

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。

ofoxai/skills22026年9月22日 更新

Captures executable contracts and coding conventions into .trellis/spec/ documents. Use when learning something valuable from debugging, implementing, or discussion that should be preserved for future sessions.

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。

ofoxai/skills22026年9月22日 更新

Requires OFOX_API_KEY — create one at https://app.ofox.ai, plus two real screenshots of one interface in two states. Animates the transition between them as one video — both go into a single Ofox video job, and the model cross-fades the values that changed while the rest of the layout holds. Use when a user wants a short software demo animation out of captures they already have, e.g. "turn these two screenshots into a demo clip", "show the dashboard going from the free plan to the paid one", "animate this settings change for the docs", or "make a clip of the counter going from 3 to 25". Do not use for a pair that is not a user interface (see keyframe-animation), for a screen recording (record it instead), or when only one screenshot exists.

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。

ofoxai/skills22026年9月22日 更新

Threat-models protocols where authority, scarce resources, bonds, bounties, escrow, reputation, ordering, adjudication, or settlement create strategic incentives. Use to test attack utility, conservation, collusion, Sybil resistance, oracle capture, griefing, custody, liquidity, and residual risk. NOT for choosing payment or bond amounts without evidence, smart-contract code audit, legal or employment classification, DeFi trading, admitting workers, or settling claims.

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。

curiositech/port-daddy22026年10月12日 更新

Systematic methodology for eliciting, representing, and operationalizing expert cognitive skills—pattern recognition, situation assessment, mental simulation—from practitioners without requiring research training. Bridges academic rigor and practical usability.

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。

curiositech/port-daddy22026年10月12日 更新

Systematic methodology for eliciting, representing, and operationalizing expert cognitive skills—pattern recognition, situation assessment, mental simulation—from practitioners without requiring research training. Bridges academic rigor and practical usability.

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。

curiositech/port-daddy22026年10月12日 更新

Track the full Toulmin epistemic ancestry of every claim produced by a multi-agent swarm. Each agent output is tagged with an argument chain (claim / data / warrant / relationship) derived from SwarmTracer spans and LineageEdge records, so operators can zoom into any sub-claim and see precisely which agents asserted it, what triggered each assertion, and how contradictions propagated or were synthesised away. The SwarmTracer pattern — wrapping the SwarmAgentExecutor to capture spans, record messages, and build a lineage graph — is the concrete runtime substrate. Argumentative lineage lifts that graph into the Toulmin vocabulary so reasoning provenance is both machine-queryable and human-interpretable.

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。

curiositech/port-daddy22026年10月12日 更新

Apply cognitive task analysis to expert work that depends on perceptual cues, branching judgment, and recurring monitoring loops. Use when decomposing expert capability into agent structure, simulation design, or validation interviews. NOT for ordinary step-by-step SOP capture or simple pipelines with no tacit cue layer.

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。

curiositech/port-daddy22026年10月12日 更新