Build AI lead scoring systems. TRIGGERS - Use when user needs help with ai-lead-scorer related tasks.
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。
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概要と使いどころ
Build AI lead scoring systems. TRIGGERS - Use when user needs help with ai-lead-scorer related tasks.
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。
Create evaluation frameworks for AI outputs with rubrics and scoring. TRIGGERS - Use when user needs help with ai-evaluation-framework related tasks.
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。
Use when building durable AI agents or agentic workflows with Inngest and AgentKit, including model calls, tool calls, multi-agent networks, human approval, realtime progress, provider rate limits, crash-safe execution, and Agent Evals handoff. Covers AgentKit, `step.ai`, `step.run`, `step.waitForEvent`, native realtime, and when to use lower-level Inngest primitives instead of an in-memory agent loop. Use `inngest-agent-evals` with this skill when the user wants scoring, sessions, experiments, deferred scorers, or outcome-based evaluation for the agent.
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。
Core knowledge for migrating integrations from other platforms (Boomi, Cyclr) to Prismatic Code Native Integrations. Provides the standard integration schema, schema-to-spec mapping, confidence scoring, and migration-aware code generation patterns. Use when the user says "migrate", "convert from Boomi/Cyclr", "parse this export".
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。
Indicator pivoting methodology — how to use one known indicator to discover related infrastructure across the IOC graph. Decision tree by indicator type with concrete `/lookup-*` commands per pivot, a worked multi-hop example, pivot-quality scoring, and routing into the rigor pipeline. Use when the user asks "what else is connected to this IP / domain / hash / cert / actor?", needs to expand a single seed IOC into a campaign cluster, or wants the canonical reference for graph-walking IOCs.
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。
Use when validating, benchmarking, or monitoring LLM application performance. Keywords: RAG evaluation, LLM-as-a-judge, CI/CD gating, trajectory scoring, test suites, prompt quality.
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。
Provide proven marketing strategies and growth ideas for SaaS and software products, prioritized using a marketing feasibility scoring system.
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。
Apply behavioral science and mental models to revenue (cuan) decisions, prioritized using a psychological leverage and feasibility scoring system.
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。
"Measure social media influence using engagement-weighted metrics beyond follower count. Use this skill when the user needs to evaluate influencer effectiveness, compare influence across accounts, or build an influence scoring system — even if they say 'who is more influential', 'influencer ranking', or 'measure social impact'.".
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。
"Implement TF-IDF scoring to measure term importance relative to a document corpus. Use this skill when the user needs to rank documents by keyword relevance, extract important terms from text, or build a basic search relevance engine — even if they say 'find relevant documents', 'keyword extraction', or 'term importance'.".
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。
"Implement VADER sentiment analysis for social media text scoring. Use this skill when the user needs to analyze sentiment in tweets, reviews, or social posts, compute compound sentiment scores, or classify text polarity — even if they say 'is this positive or negative', 'sentiment of these comments', or 'social media mood analysis'.".
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。
"Implement Elo rating system to rank items or players from pairwise comparison outcomes. Use this skill when the user needs to rank items from head-to-head matchups, build a competitive rating system, or evaluate relative quality from comparison data — even if they say 'player rating', 'ranking from comparisons', or 'competitive scoring system'.".
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。
"Build CTR prediction models for estimating ad click-through rates from features. Use this skill when the user needs to predict click probability, build an ad ranking model, or evaluate ad creative performance — even if they say 'predict click rate', 'ad relevance scoring', or 'which ad will get more clicks'.".
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。
"Implement BM25 ranking function for e-commerce product search relevance scoring. Use this skill when the user needs to build a text-based product search engine, improve search result relevance, or replace basic TF-IDF with a more robust ranking function — even if they say 'product search ranking', 'search relevance', or 'BM25 implementation'.".
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。
Assess identified vulnerabilities for exploitability, impact, and risk. Provide CVSS scoring and remediation strategies. Use when analyzing security findings.
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。
Validate user stories — INVEST scoring, story-to-test coverage mapping, PRP completeness, and development-readiness assessment. Use after writing stories and before starting implementation. Trigger on "validate the stories", "are these stories ready", "INVEST check", "story coverage", "is this ready to build".
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。
Build structured vendor/tool evaluation matrices with weighted scoring, TCO analysis, and recommendation memos. Covers criteria definition, deal-breaker identification, and negotiation points. Use when selecting SaaS tools, evaluating technology vendors, or making build-vs-buy decisions.
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。
Build structured behavioral interview guides using the STAR method. Map job competencies to interview questions, provide scoring rubrics (1–5), and include follow-up probes and red/green flag indicators. Use when preparing for hiring interviews or standardizing interview practices.
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。
Writes professional bug bounty reports for HackerOne, Bugcrowd, and Intigriti with CVSS 4.0 scoring, business impact, working exploits, and remediation. Runs 5-check Pre-Report Verification first: hallucination detection, AI writing patterns, PoC reproducibility, duplicate detection, and impact plausibility. Use when user describes a vulnerability, shares HTTP logs, HAR files, recon output, or screenshots; says 'write a bug report', 'format my finding', 'draft a vuln report', 'is this valid', 'rate my vulnerability', 'verify my report', or any variant. Trigger for partial or messy input — raw notes, one-liners, or full writeups all work. Do not wait for perfect input.
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。
Use when curating, refreshing, expiring, calibrating, or equivalence-testing evidence and publication inputs for the active Safety Score model. Not for unrelated scoring models or copy-only changes.
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。
Write or refresh evidence-grounded editorial summaries for stablecoin detail pages, including draining the AI-summary candidate queue after scoring changes.
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。
Discovery-only Gaia curation for one manually selected source page. Fetches and normalizes up to five real SKILL.md candidates, deduplicates and maps them for human L4 review, then stops without evidence scoring or registry mutation.
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。
Skippable Phase 0 of the Gaia evidence verification pipeline. Use only on declared need for higher-quality Stage-2 evidence: a promotion candidate, or a skill that gaia-meta-sweep flagged as under-evidenced. Given a skill id, source repo/context, and needed evidence types (benchmark-result, arxiv, peer-review, social-signal), it runs Firecrawl searches, scrapes top hits to markdown, and appends discovered sources into Phase 1 inputs. Missing benchmark evidence is recorded as benchmark-source candidates first, not direct scoring rows. Trigger phrases: "discover evidence", "find new evidence", "Phase 0", "run ev-discovery", "search for benchmarks/papers", "under-evidenced", "promotion candidate needs stronger proof". This is the ONLY ev-* skill that searches the web for NEW evidence; other ev-* skills aggregate or verify known sources. Requires Firecrawl to be usable (`firecrawl --status` authenticated OR FIRECRAWL_API_KEY set); skips gracefully when neither holds.
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。
Enriches indicators with context from threat-intel sources: planning lookups against reputation, passive DNS, WHOIS, and sandbox/sample databases, scoring confidence, and avoiding operational-security mistakes that tip off adversaries. Activates for requests to enrich IOCs, add threat context, or plan indicator lookups safely.
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。