Deep enrichment for community-sourced enterprise PROSPECTS (the 🎯 Prospective enterprise customers subsection). For each prospect, resolve their LinkedIn from their GitHub self-linked accounts FIRST (search only if none is self-linked), verify the employer matches, capture their full name, then list the company website + company size (ARR / latest funding round / employee count). Runs as a general-purpose subagent (many web searches) so the orchestrator's context stays small. Invoked by weekly-report (enterprise section) and the enterprise skill.
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。
CopilotKit/outpost☆ 122026年10月9日 更新
Fri→Fri community signals routine across CopilotKit + AG-UI. Orchestrator that supervises subagents — Discord pull, GitHub pull, deep-read, reporter enrichment, Reddit Pulse — and synthesizes a Notion report under the Community Signals parent page. Triggers on "go", "weekly report", "community signals", "run routine".
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。
CopilotKit/outpost☆ 122026年10月9日 更新
Generic ad-hoc topic search across CopilotKit + AG-UI Discord/GitHub. "Find all reports about <topic> in the last <N> days." Returns a structured chronological list with reporter handles + 1-line summaries + optional enterprise enrichment. Triggers on "find all reports about", "search across both communities", "look for X in last N days".
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。
CopilotKit/outpost☆ 122026年10月9日 更新
Subagent for GitHub author enterprise enrichment. Runs gh api users/<login> for each unique handle and classifies enterprise vs indie. Invoked by weekly-report or enterprise skills; runs as Explore subagent so the orchestrator's context stays small.
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。
CopilotKit/outpost☆ 122026年10月9日 更新
Systematically collects, categorizes, and distributes indicators of compromise (IOCs) during and after security incidents to enable detection, blocking, and threat intelligence sharing. Covers network, host, email, and behavioral indicators using STIX/TAXII formats and threat intelligence platforms. Activates for requests involving IOC collection, indicator extraction, threat indicator sharing, compromise indicators, STIX export, or IOC enrichment.
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。
andycungkrinx91/konoha☆ 92026年10月9日 更新
Build an automated system to track adversary infrastructure using passive DNS, certificate transparency, WHOIS data, and IP enrichment to map and monitor threat actor command-and-control networks.
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。
andycungkrinx91/konoha☆ 92026年10月9日 更新
Parse Apache and Nginx access logs to detect SQL injection attempts, local file inclusion, directory traversal, web scanner fingerprints, and brute-force patterns. Uses regex-based pattern matching against OWASP attack signatures, GeoIP enrichment for source attribution, and statistical anomaly detection for request frequency and response size outliers.
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。
andycungkrinx91/konoha☆ 92026年10月9日 更新
Analyzes indicators of compromise (IOCs) including IP addresses, domains, file hashes, URLs, and email artifacts to determine maliciousness confidence, campaign attribution, and blocking priority. Use when triaging IOCs from phishing emails, security alerts, or external threat feeds; enriching raw IOCs with multi-source intelligence; or making block/monitor/whitelist decisions. Activates for requests involving VirusTotal, AbuseIPDB, MalwareBazaar, MISP, or IOC enrichment pipelines.
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。
andycungkrinx91/konoha☆ 92026年10月9日 更新
Erweitert automation-self-care um Letter Hooks, Preflight-Bootloader, Dokument-Traversierungsregeln und selbstheilende Prompt-Kontext- Anreicherung für KI-Agenten und CLIs ohne native, ereignisgetriebene JSON-Lifecycle-Hooks (wie Antigravity / Gemini CLI). Nutzen, wenn ein Agent Preflight-Regeln injizieren, vor Arbeitsbeginn Memory/Gardener durchsuchen, Verzeichnis-Dokument-Lesestrategien erzwingen (CLAUDE.md / AGENTS.md) oder Sidecar-Tasks dynamisch an Skills und Sicherheitsprotokolle routen soll.
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。
ellmos-ai/skills☆ 82026年10月12日 更新
Maps every proposed P&ID object from an accepted enrichment draft to the generic family, catalogue class and required attributes the project's intelligent P&ID authoring tool would need, as a readiness table with UNKNOWN wherever the project catalogue extract is not provided, plus connectivity readiness per line and a numbered list of import blockers. Mapping only: it never writes to the tool, never produces an import file and never claims a class exists in the catalogue. Use when the user asks to "build the readiness map", "show how far the draft is from a sandbox import", "list what would block the import", "map the objects to the tool catalogue" or "check attribute readiness against the catalogue extract" after gate G3. Do not use for validating the discipline sections or assembling the review package, use validation-and-review-package instead. Drafts for human review; never approves, authorises or signs off.
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。
kesslernity/awesome-copilot-agent-skills☆ 82026年9月19日 更新
Proposes tag and number structures for the new lines and instruments in a P&ID draft according to the project's numbering procedures, checks every tag extracted from the PFD against the quoted procedure format, and lists cross-section identifier mismatches and the registry checks a human must run. Never invents a numbering convention, never alters a PFD tag and never assigns a sequence number the procedure reserves for the registry. Use when the user asks to "run the tagging and numbering section", "check the tags against the numbering procedure", "propose the tag structure for the new lines and instruments" or "list the registry checks before validation" after the process safety flags. Do not use for validating the four sections, use validation-and-review-package instead; do not use for instrument content, use instrumentation-and-control-enrichment. Drafts for human review; never approves, authorises or signs off.
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。
kesslernity/awesome-copilot-agent-skills☆ 82026年9月19日 更新
Runs twice in a PFD to P&ID job. Part 1, before gate G3, validates the discipline proposals for provenance, UNKNOWN handling, conflicts, prohibited content and cross-section consistency and returns results and blocking items. Part 2, before gate G5, assembles the review package, with job header, gate record, every register and proposal, consolidated UNKNOWN list, feedback log and closing statement. Use when the user asks to "validate the enrichment", "run validation before G3", "assemble the review package" or "build the G5 package". Do not use for the readiness map, use pid-tool-readiness-mapping instead; do not use to produce a missing discipline section, use the discipline skill that owns it. Drafts for human review; never approves, authorises or signs off.
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。
kesslernity/awesome-copilot-agent-skills☆ 82026年9月19日 更新
Build qualified prospect lists using an explicit ICP, source provenance, qualification criteria, scoring, enrichment hygiene and outreach-compliance checks.
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。
unempyd/revenueos☆ 72026年9月14日 更新
Create an Estuary derivation that joins two or more collections on a shared key, merging their fields into a single enriched collection. Use for data enrichment, denormalisation, building wide tables for BI, and real-time CDC joins. Derivations add complexity and cost — confirm the user wants a derivation before reaching for this (a destination-side SQL join or BI tool view is often simpler). Use when user says "join-collections derivation", "derivation to join two collections", "transformation to enrich with customer data", "derive a wide table", "lookup-join derivation", or "build a join derivation".
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。
estuary/agent-skills☆ 72026年9月25日 更新
Use when working with Bigpanda — bigPanda AIOps platform management covering event correlation, root cause analysis, incident management, alert enrichment, topology-based correlation, environment management, and analytics. Use when configuring BigPanda correlation patterns, investigating correlated incidents, tuning noise reduction, or analyzing alert topology and root cause indicators.
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。
cloudthinker-ai/CloudSkills☆ 62026年4月5日 更新
Query ARCHS4 REST API for uniformly processed RNA-seq expression, tissue patterns, co-expression across 1M+ human/mouse samples. Retrieve z-scores, co-expressed genes, samples by metadata, HDF5 matrices. For variant population genetics use gnomad-database; for pathway enrichment use gget-genomic-databases (Enrichr).
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。
bg-szy/TOP-SKILLS☆ 62026年9月8日 更新
Generates sourced, BDR-ready account research briefs for named target accounts in B2B SaaS ABM and outbound motions. Use after a target account list is built and before outreach sequences are written. Best for Tier 1, Tier 2, and intent-qualified accounts where BDRs need a clear "why this account, why now, why this persona" hypothesis. Designed for B2B SaaS teams selling compliance, security, GRC, risk, or other technical platforms into mid-market and enterprise buyers. Not intended for broad list building or mass enrichment.
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。
Stallin-Sanamandra/b2b-saas-marketing-skills☆ 52026年4月27日 更新
Systematically collects, categorizes, and distributes indicators of compromise (IOCs) during and after security incidents to enable detection, blocking, and threat intelligence sharing. Covers network, host, email, and behavioral indicators using STIX/TAXII formats and threat intelligence platforms. Activates for requests involving IOC collection, indicator extraction, threat indicator sharing, compromise indicators, STIX export, or IOC enrichment.
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。
micsapp/micstec-skills☆ 42026年3月20日 更新
Parse Apache and Nginx access logs to detect SQL injection attempts, local file inclusion, directory traversal, web scanner fingerprints, and brute-force patterns. Uses regex-based pattern matching against OWASP attack signatures, GeoIP enrichment for source attribution, and statistical anomaly detection for request frequency and response size outliers.
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。
micsapp/micstec-skills☆ 42026年3月20日 更新
Build an automated system to track adversary infrastructure using passive DNS, certificate transparency, WHOIS data, and IP enrichment to map and monitor threat actor command-and-control networks.
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。
micsapp/micstec-skills☆ 42026年3月20日 更新
Analyzes indicators of compromise (IOCs) including IP addresses, domains, file hashes, URLs, and email artifacts to determine maliciousness confidence, campaign attribution, and blocking priority. Use when triaging IOCs from phishing emails, security alerts, or external threat feeds; enriching raw IOCs with multi-source intelligence; or making block/monitor/whitelist decisions. Activates for requests involving VirusTotal, AbuseIPDB, MalwareBazaar, MISP, or IOC enrichment pipelines.
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。
micsapp/micstec-skills☆ 42026年3月20日 更新
Focused Signals scout for PostHog projects using AI observability. Rotates through a set of lenses — cost, latency, errors, volume, eval performance, eval/enrichment config, clusters, and tool usage — watching each for trends and spikes sliced by the dimensions it discovers over time. Leans on the sandbox's bundled `exploring-llm-*` deep-dive skills for the actual queries. Emits findings only when they clear the confidence bar; otherwise writes durable memory and closes out empty. Self-contained peer in the signals-scout-* fleet — no dependencies on other scouts.
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。
0xAidan/polymarket-bot-test☆ 42026年9月4日 更新
Designs adaptive clinical trials including group-sequential (O'Brien-Fleming, Pocock, Lan-DeMets spending), sample-size re-estimation (blinded Friede-Kieser, unblinded Cui-Hung-Wang, Mehta-Pocock promising zone), seamless Phase 2/3 with treatment-arm selection, population enrichment, and response-adaptive randomisation. Covers FDA 2019 Final Adaptive Designs Guidance, FDA 2022 Master Protocols, and ICH E20 Step 2b/3 draft (June 2025, NOT final). Use when planning interim analyses, sample-size re-estimation, or master/platform-trial designs.
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。
huang-sh/DeepScience☆ 42026年7月15日 更新
Orchestrates the full path from differential expression results to redundancy-collapsed functional enrichment: choose ORA vs GSEA, convert gene IDs per method, run enrichGO/enrichKEGG/enrichPathway/enrichWP or gseGO/gseKEGG (clusterProfiler, ReactomePA, rWikiPathways), and visualize. Use when a DESeq2/edgeR/limma result must become enriched GO terms, KEGG/Reactome/WikiPathways pathways, or a GSEA leading edge; when the input is a full ranking for all genes (GSEA, named decreasing vector) or only a pre-selected list (ORA plus a defensible background universe); or when assembling DE-to-pathway end to end. The DE list and ranking statistic come from differential-expression/de-results; per-method nuance lives in the pathway-analysis skills.
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。
huang-sh/DeepScience☆ 42026年7月15日 更新