Results for “spec-tracking”

Perform a post-implementation retrospective analysis measuring spec adherence, implementation deviations, and lessons learned.

Scan codebases for technical debt, score severity, track trends, and generate prioritized remediation plans. Use when users mention tech debt, code quality, refactoring priority, debt scoring, cleanup sprints, or code health assessment. Also use for legacy code modernization planning and maintenance cost estimation.

Identify underspecified areas in the current feature spec by asking targeted clarification questions and encoding answers back into the spec.

Scan codebases for technical debt, score severity, track trends, and generate prioritized remediation plans.

spec-ship

Progress Tracking

Weekly engineering retrospective. (gstack)

Track stocks, ETFs, indices, crypto (where available), and FX pairs with caching + provider fallbacks.

User Request

Break a plan, spec, or the current conversation into a set of tracer-bullet tickets, each declaring its blocking edges, published to the configured tracker — edges as text in one file per ticket locally, or native blocking links on a real tracker.

Use this skill when creating, managing, or working with Conductor tracks - the logical work units for features, bugs, and refactors. Applies to spec.md, plan.md, and track lifecycle operations.

Weekly engineering retrospective. (gstack)

Set up and track KPI dashboards with targets, actuals, and trend analysis. TRIGGERS - Use when user wants to define KPIs, track metrics, or create a scorecard.

Scan codebases for technical debt, score severity, track trends, and generate prioritized remediation plans. Use when users mention tech debt, code quality, refactoring priority, debt scoring, cleanup sprints, or code health assessment. Also use for legacy code modernization planning and maintenance cost estimation.

Set up and track KPI dashboards with targets, actuals, and trend analysis. TRIGGERS - Use when user wants to define KPIs, track metrics, or create a scorecard.

Imported skill spec_parsing from openai

Manufacturing execution system tracker

Convierte especificaciones aprobadas en un plan técnico detallado, documentando decisiones de arquitectura, flujo de datos y cambios de archivos.

Performance Profiler

Tracks team OKRs with quarter banner, objective columns, key result progress bars, owner avatars, and status pills.

Chains /mvp and /backend-spec to analyze an app from video, screenshots, or description, then generate implementation stories from the analysis.

Spec Craft

Analyzes dependencies between stories, code modules, tickets, or specs to compute an optimal implementation order with parallel batches, cycle detection, and critical path analysis.

Weekly engineering retrospective. (gstack)

Profile a target (script, process, GPU, memory, interconnect) using external tools and code instrumentation. Produces structured performance reports with actionable recommendations. Use when user says "profile", "benchmark", "bottleneck", or wants performance analysis.

Eng manager-mode plan review. Lock in the execution plan — architecture, data flow, diagrams, edge cases, test coverage, performance. Walks through issues interactively with opinionated recommendations. Use when asked to "review the architecture", "engineering review", or "lock in the plan". Proactively suggest when the user has a plan or design doc and is about to start coding — to catch architecture issues before implementation. (gstack) Voice triggers (speech-to-text aliases): "tech review", "technical review", "plan engineering review".

Follow a request end-to-end through the stack from route to database

Implements tasks from an OpenSpec change, tracking progress and pausing for clarification when needed.

Implements tasks from an OpenSpec change, guiding the agent through selecting a change, reading context, and completing tasks with progress tracking.

This skill provides guidance for video analysis and processing tasks using computer vision techniques. It should be used when analyzing video frames, detecting motion or events, tracking objects, extracting temporal data (e.g., identifying specific frames like takeoff/landing moments), or performing frame-by-frame processing with OpenCV or similar libraries.