Execution plans often pass review while still missing acceptance criteria, deltas, or verification steps, which causes rework during implementation. This skill routes each plan to the correct review lane and checklist, then returns graded blockers so a plan is only marked implementation-ready when it is truly executable.

代码改动后，README 与版本记录常被遗漏，文档容易与实现脱节。本技能读取真实代码与现有文档，按固定清单更新 README 和版本条目，并如实标注验证状态。

Large coding plans often fail when an agent edits too much at once. This skill implements one approved plan step at a time, keeps edits scoped, and reports a clear status when the step is done.

ai-gates documentation can be difficult to apply when project files, plugin files, and hooks have separate roles. This skill explains the workflow boundaries so users can start work, upgrade safely, and avoid duplicate setup.

A single still image is rarely enough to produce a convincing short video, because appearance problems cannot be fixed by motion. This skill solves appearance in the start frame first, then animates the approved frame with Magic Hour and inspects the finished clip before delivery.

Video generation APIs require model selection, asynchronous polling, and careful download handling. This skill guides RouteMux submissions and returns completed video files with status details.

AI client setup often fails because tools expect different base URL and protocol formats. This skill selects the correct RouteMux endpoint and verifies access.

Choosing a model without current availability, pricing, or capability data can cause failed requests and poor tradeoffs. This skill queries the live RouteMux catalogue for the models your key can call.

Coding agents can lose built-in image tools when routed through a custom API gateway. This skill uses RouteMux endpoints to generate or edit images.

Investors often have data but lack a consistent framework for comparing business quality, valuation, growth, and risk. This skill routes the question to a suitable investor lens and grounds the analysis in dated LLMQuant Data.

Financial research requests can become inconsistent when filing, ownership, and macro questions use different evidence standards. This skill routes each request to a focused workflow that uses dated LLMQuant Data and clearly separates retrieved facts from interpretation.

Macro research often mixes indicators, market pricing, and portfolio exposures without consistent dates or assumptions. This skill structures the analysis through focused LLMQuant workflows.

Market uncertainty makes risk signals and hedge choices difficult to compare. This skill routes requests into structured fear, volatility, hedging, and research-quality workflows.

Portfolio research can become fragmented across profiles, theses, themes, watchlists, and alerts. This skill routes each request into a structured workflow powered by LLMQuant Data.

Engineering teams need a direct path to their Context Mode analytics. This skill opens the hosted Insight dashboard and reports its address.

Equity derivative analysis requires reliable contract terms, market data, and clear risk framing. This skill routes each request through a focused, evidence-based workflow.

Market research can become fragmented across macro indicators, sentiment measures, and event markets. This skill routes each question to a focused workflow with dates, data windows, caveats, and portfolio context.

Portfolio requests often lack a consistent framework for evidence, sizing, catalysts, and risk. This skill routes each request to a focused institutional strategy workflow.

React contributions require several checks that are easy to miss or run in the wrong order. This skill coordinates formatting, linting, typing, and tests.

Brands struggle to measure how AI systems mention them and their competitors. BotSee manages research inputs, runs analyses, and turns results into actionable reports.