「tracking」の検索結果

Analyze meeting transcripts, recordings, and notes to extract action items, key decisions, topics, sentiment, and generate summaries using NLP and AI. Use when processing meeting transcripts, extracting action items, summarizing discussions, identifying key decisions, tracking topics and themes, analyzing sentiment, generating meeting notes, or building collaboration and productivity tools.

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。

Generate comprehensive changelogs from Git history, commit messages, pull requests, and issue tracking for release documentation. Use when preparing releases, documenting changes, creating release notes, categorizing commits, generating version summaries, maintaining project history, or automating changelog updates.

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 planning a Humans sprint — grooming the backlog into work batches and publishing the Peter-approved subset as a cloud sprint tracking issue. Runs locally with gh access to both repos.

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 a sprint tracking issue (label `sprint`) on peterdrier/Humans needs working — routine-fired cloud runs, or any unattended session told to execute the sprint queue.

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。

Weekly engineering retrospective. Analyzes commit history, work patterns, and code quality metrics with persistent history and trend tracking. Team-aware with per-person contributions, praise, and growth areas. Use when asked for weekly retro, what shipped this week, or engineering retrospective.

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。

Chief Security Officer mode. Infrastructure-first security audit: secrets archaeology, dependency supply chain, CI/CD pipeline security, LLM/AI security, skill supply chain scanning, plus OWASP Top 10, STRIDE threat modeling, and active verification. Two modes: daily (zero-noise, 8/10 confidence gate) and comprehensive (monthly deep scan, 2/10 bar). Trend tracking across audit runs. Use when: "security audit", "threat model", "pentest review", "OWASP", "CSO review". (gstack) Voice triggers (speech-to-text aliases): "see-so", "see so", "security review", "security check", "vulnerability scan", "run security".

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。

Weekly engineering retrospective. Analyzes commit history, work patterns, and code quality metrics with persistent history and trend tracking. Team-aware: breaks down per-person contributions with praise and growth areas. Use when asked to "weekly retro", "what did we ship", or "engineering retrospective". Proactively suggest at the end of a work week or sprint. (gstack)

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。

Monitor and react to content distribution events using Sling Distribution API (org.apache.sling.distribution). Covers distribution event handling, queue monitoring, and distribution lifecycle tracking.

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。

Compare two versions of an AEM Edge Delivery Services page to identify what changed. Fetches preview vs live, or two different URLs, and produces a detailed content diff showing added, removed, and modified content, metadata, and blocks. Use when reviewing changes before publishing, auditing content modifications, or tracking content evolution.

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。

Apple's approach to interface design and fluid, physical motion, translated for the web. Use when building or reviewing gesture-driven UI, spring animations, drag/swipe/sheet interactions, momentum and interruptible transitions, translucent materials and depth, typography (optical sizing, tracking, leading), reduced-motion, or the design foundations (feedback, spatial consistency, restraint) behind Apple-style interfaces.

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。

Runtime security for agent skills — prevents state corruption, skill overwrite attacks, denial of service, and enforces provenance tracking and no-go repo management. Load as part of the secure-* skill sequence whenever an agent processes external content or writes to the skill store. Also load when the user asks to check for state corruption, prevent skill overwrite, manage no-go repos, check provenance, audit runtime security, detect DoS patterns, or protect the skill store. Covers Issues 6, 9, 10 from the agent security threat model: instruction hierarchy enforcement, state corruption and skill overwrite, and denial of service prevention.

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。

Apple's approach to interface design and fluid, physical motion, translated for the web. Use when building or reviewing gesture-driven UI, spring animations, drag/swipe/sheet interactions, momentum and interruptible transitions, translucent materials and depth, typography (optical sizing, tracking, leading), reduced-motion, or the design foundations (feedback, spatial consistency, restraint) behind Apple-style interfaces.

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。

Automate customer engagement workflows including broadcast triggers, message analytics, segment management, and newsletter tracking through Customer.io via Composio

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。

Automate time tracking workflows in Clockify -- create and manage time entries, workspaces, and users through natural language commands.

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。

Run large codebase migrations and multi-file refactors. Uses the Composio CLI to coordinate issue tracking, batched PRs, and CI verification while the agent executes the transforms locally across hundreds of files.

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。

Turn Notion specs into implementation plans, tasks, and progress tracking; use when implementing PRDs/feature specs and creating Notion plans + tasks from them.

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。

Automate Calendly scheduling, event management, invitee tracking, availability checks, and organization administration via Rube MCP (Composio). Always search tools first for current schemas.

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。

Codified expertise for managing carrier portfolios, negotiating freight rates, tracking carrier performance, allocating freight, and maintaining strategic carrier relationships.

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。

Azure Weights & Biases SDK for .NET. ML experiment tracking and model management via Azure Marketplace. Use for creating W&B instances, managing SSO, marketplace integration, and ML observability.

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。

Complete App Store Optimization (ASO) toolkit for researching, optimizing, and tracking mobile app performance on Apple App Store and Google Play Store

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。

Assigns pathogen lineages (SARS-CoV-2 Pangolin via UShER mode; Nextclade clade + QC; pango-designation alias_key.json resolution) and tracks variant frequencies over time using Nextstrain (Augur + Auspice), wastewater deconvolution (Freyja, COJAC, alcov, lineagespot), lineage fitness modelling (Wenseleers / Bedford-Figgins multinomial logistic), and recombinant detection (3SEQ, RDP4, Bolotie). Covers Pangolin pangolin-data version pinning (mandatory for reproducibility), Nextclade dataset versioning (lineage-defining mutations change with dataset), Freyja barcode forward-only date constraint, ARTIC primer scheme version churn (V3 / V4 / V4.1 / V5.3.2 / Midnight 1200) with documented dropout regions, recombinant X-prefix Pango designation lag, GISAID vs INSDC dual-deposition tensions, and the Karthikeyan 2022 wastewater early-detection signal with explicit reproducibility caveats. Use when assigning Pango lineages and Nextclade clades to viral consensus sequences, building Nextstrain Augur surveillance pipelines, deconvolving wastewater pooled samples into lineage frequencies with Freyja, tracking lineage frequencies and growth advantages over time, pinning pangolin-data / Nextclade dataset versions for reproducibility, handling ARTIC primer dropouts (V4.1 amplicons 64 / 76 / 88-90), or running variant surveillance for SARS-CoV-2 / influenza / Mpox / RSV / H5N1 / measles.

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。

Aligns and QCs methylated-RNA-immunoprecipitation (MeRIP / m6A-seq) IP and input libraries using STAR or HISAT2 splice-aware mapping, samtools sort/index, IP/input matched-pair tracking, antibody-lot metadata recording, replicate concordance via deepTools multiBamSummary + plotCorrelation, IP enrichment QC via plotFingerprint and per-transcript IP/input ratio distributions, library-complexity saturation curves via PreSeq c_curve / lc_extrap, and the explicit do-NOT-deduplicate convention for standard non-UMI MeRIP. Use when preparing paired IP and input BAM files for exomePeak2 / MeTPeak / MACS3 peak calling, evaluating MeRIP replicate concordance and IP enrichment, deciding whether to deduplicate (standard MeRIP typically NOT — see Tips), choosing genome-vs-transcriptome alignment for downstream peak vs m6Anet workflows, recording antibody clone and lot metadata for downstream cross-batch reconciliation, detecting failed IPs via saturation curves and IP/input distribution shape, or generating IP-over-Input bigWig tracks for downstream visualisation.

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。

Resolves rsIDs, navigates RsMergeArch/SNPHistory merge chains, and converts between rsID, SPDI, HGVS, and VCF representations using the dbSNP Build 156 JSON architecture. Use when normalizing variant identifiers, joining variant databases by cluster ID, or tracking deprecated rsIDs through historical merges.

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 this skill when the user asks how to design or improve a Preventive Maintenance (PM) program for a fleet — mileage vs time intervals, A/B/C/D inspection levels, ATA standards, common PM tasks, scheduling software, cost tracking, and how PM affects roadside inspections + CSA scores. Reference ATA Equipment Maintenance Council standards.

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。