Results for “finding-classification”

基于 anchor 论文、topic 关键词或当前 wiki 状态，产出一份排好序的候选论文 shortlist，供用户或上游 skill 决定是否进一步 `/ingest`。当用户问 "接下来该读什么"、"找和这篇相似的论文"、"推荐相关工作"、"这个方向周围有什么" 时触发；`/ingest --discover` 也会内部调用本 skill。本身不 ingest，只提出候选。

Finds, inspects, and compares .NET project templates by resolving natural-language descriptions to ranked template matches with pre-filled parameters.

Rank an existing set of context chunks by relevance, diversity, freshness, and utility. Use when retrieval has already produced candidates that must be scored or reranked; use context-retrieval when the source corpus still needs to be searched.

Classifies HTML pages, forms, and fields using machine learning to detect page types, form types, and field types from HTML content or URLs.

Triage and categorize findings for the CLI todo system

Research-before-coding workflow. Search for existing tools, libraries, and patterns before writing custom code. Invokes the researcher agent.

research-synthesis

Multi-dimensional lead qualification scoring. Evaluates leads against BANT criteria, firmographic fit, behavioral signals, and intent indicators. Outputs qualified/disqualified verdict with detailed reasoning.

Research-before-coding workflow. Search for existing tools, libraries, and patterns before writing custom code. Invokes the researcher agent.

Discovers and evaluates community skills from skills.sh and awesome-openclaw-skills when local skills don't cover a need, scoring credibility and installing top recommendations with permission.

Guides selection of Qdrant search strategies including hybrid search, reranking, relevance feedback, MMR, and discovery APIs to improve retrieval quality.

Plan, debug, tune, evaluate, export, or deploy public Nemotron embedding and reranking retrieval recipes using the current checkout.

Define product positioning by mapping competitive alternatives, unique attributes, and best-fit customers to the right market category using a structured canvas and 5-step process.

Guides database index selection, creation, and maintenance with SQL examples for PostgreSQL and MySQL.

Classify, triage, and manage declared security incidents from initial triage through forensic evidence collection and escalation routing.

Mine proof-heavy papers, notes, PDFs, Markdown, or LaTeX sources into source-indexed proof-material files. Use when the user wants to extract technically nontrivial lemmas, estimates, definitions, dependencies, reductions, constructions, or proof strategies, preserve paper locations and stable material IDs, run DeepSeek screening/backtests, and update the proof-material index rather than writing directly to proof-usage.

Research companies, industries, or competitor sets using web search and seven analytical lenses to produce structured intelligence for downstream product management tasks.

Merges multiple research, analysis, or brainstorming inputs into a single coherent synthesis with key insights and a recommended action.

Defines ideal customer profile filters, scores inbound and outbound leads, and builds a lightweight qualification rubric to sharpen pipeline focus for founder-led sales.

研究优先于编码的工作流程。在编写自定义代码之前，搜索现有的工具、库和模式。调用研究员代理。

選択肢(A/B/C)の深掘り比較→淘汰→推奨で判断負担を下げ判断の質を上げるスキル。5段階（L1固定3点/L1.5案拡張Diverge・自動/L2評価軸マトリクス/L3複数LLM弁証論/L4過去判断照合）。 「比較して」「深掘りして」「メリデメ教えて」「お勧めは？」「徹底的に」「過去の判断と照合」「前にどう決めたっけ」「/sentaku」等で発火。teian(浅)の深掘り要求を受け取り、brainstorming(深:設計全体)と棲み分け。

Find adjacent vendors and subs (not top market primes) who fill a capability gap against a displacement target using USASpending flows and SAM entity signals. Use when user defines a teaming gap and wants vault-ready partner shortlist with citations.

Generate new feature ideas for an existing product using multi-perspective ideation from PM, Designer, and Engineer viewpoints, then prioritize the best five.

Research the open web for enhancement opportunities (Layer 3 — Opus subagent with WebSearch + WebFetch). Topic-driven. Returns structured findings with hype tags + source URLs. Does NOT auto-implement.

Analyzes type design for encapsulation, invariant expression, usefulness, and enforcement, providing scores and improvement suggestions.

Perform semantic search, find similar content, and conduct structured research using the Exa API.

Investigates hard, flaky, or performance failures through a six-phase feedback-loop-first debugging process; use when quick targeted debugging is insufficient.

融合分类系统与潜能蒸馏能力，从复杂现象中提取本质并进行结构化分类，促进跨领域知识整合与创新。

Scores competitors across nine weighted dimensions with explicit 1–5 rubrics and a tension plot, producing comparable profile cards for competitive analysis.

Research existing tools, libraries, and patterns before writing custom code by invoking a researcher agent.

Semantic search, similar content discovery, and structured research using Exa API

Search and analyze research papers, find related work, summarize key ideas. Use when user says "find papers", "related work", "literature review", "what does this paper say", or needs to understand academic papers.

Ingests case studies, past proposals, and boilerplate from library/inbox into structured indexes. Use when the user requests to 'index proposal library', 're-index case studies', 'ingest inbox docs', or 'validate library'.

Orchestrate a full theory-first idea discovery pipeline. Use when the user wants the analysis counterpart of idea-discovery: literature context, proof-oriented idea generation, novelty checking, DeepSeek critique, and an analysis plan instead of an experiment-first workflow.