Results for “success-rate”

Use this skill when the user asks about DataQ — FMCSA's data review system at dataqs.fmcsa.dot.gov — for disputing inspection violations, crash records, or other entries that appear in a carrier's CSA / SMS score. Covers Request for Data Review (RDR) process, success rates, common dispute grounds, what evidence to attach, timeline expectations, and how successful disputes reduce BSI (BASIC Severity Indicator) scores. Cite 49 CFR 392.7 and the FMCSA DataQs User Guide.

rate(http_requests_total[5m])

Use this skill to evaluate which DataQ challenges have winning evidence and which don't. Covers documented vs anecdotal evidence and the 8 high-success patterns.

Correspondence Reply Modal

Conversion rate optimization for marketing pages and lead-capture forms. Use when the user wants to improve conversions on a homepage, landing page, pricing page, feature page, blog CTA, contact form, demo form, or campaign page. For product onboarding use user-onboarding; for lifecycle email use marketing-automation; for pricing and paywalls use pricing-strategy; for A/B testing use ab-test-setup.

当需要在多个领域积累独特竞争优势，避免单一技能风险时

Create product objectives, key results, initiatives, guardrails, and review cadence.

RICE feature prioritization with scoring and capacity planning. Usage: /rice prioritize <features.csv> [options]

Run a structured retrospective after development-phase runs of your product's agents — interview the owner in plain language about what went well and poorly, draft ranked improvement hypotheses, then design and run small n=1/n=2 experiments with pre-declared success criteria, guardrails, stop conditions, and a cost/ROI kill-switch. Load when the user says how did that run go, retro this run, the agent output was bad, what should we improve, draft hypotheses, run a small experiment, or after repeated dev runs of an agentic system produce uneven quality. Priority: output quality over performance over cost, each with diminishing-returns stops. NOT a product A/B test (experimentation), NOT coding-agent harness repair (harness-evolution), NOT production-scale learning (runtime-learning-loop).

v4.1.0 reward function redesign to fix overtrading and DSR dominance

Rehearse

Agent validation v4.3.0 — Make agents act effectively by disabling harmful actions, lowering gates, and injecting cross-run learning

React 18/19 patterns including hooks discipline, server/client component boundaries, Suspense + error boundaries, form actions, data fetching, state management decision trees, and accessibility-first composition. Use when writing or reviewing React components.

`analysis-agent`/`task-agent`/`review-agent`: use for recurrence guards on known defects, incidents, or escaped failures; skip speculative risk without a prior failure mechanism.

"Quality" is unmanageable until it is a set of numbers with agreed definitions.

Use to measure which help articles actually resolve contacts versus merely being read, including contact-after-view and assisted resolution. Trigger for "are our help articles working", article view counts misleading, deflection measurement, contact after reading an article, self-service success metrics, KB ROI, or stopping AI agents from optimising for page views.

Multi-agent autonomous startup system for Claude Code. Triggers on "Loki Mode". Orchestrates 100+ specialized agents across engineering, QA, DevOps, security, data/ML, business operations, marketing, HR, and customer success. Takes PRD to fully deployed, revenue-generating product with zero human intervention. Features Task tool for subagent dispatch, parallel code review with 3 specialized reviewers, severity-based issue triage, distributed task queue with dead letter handling, automatic deployment to cloud providers, A/B testing, customer feedback loops, incident response, circuit breakers, and self-healing. Handles rate limits via distributed state checkpoints and auto-resume with exponential backoff. Requires --dangerously-skip-permissions flag.

Optimize conversion rates with funnel analysis, A/B testing, statistical significance, and compliance-safe experiments.

Hardens Laravel applications against common vulnerabilities with guidance on authentication, authorization, validation, CSRF, mass assignment, file uploads, secrets, rate limiting, and secure deployment.

Diagnose and remove FPS caps so the editor and game run uncapped (or at a target FPS). Use when the user says the editor/game is "locked", "capped", or "stuck" at a frame rate (commonly 60 FPS), asks to "unlock"/"uncap"/"raise" FPS, or wants to set a max FPS. Covers t.MaxFPS, VSync, fixed/smoothed frame rate, and background CPU throttling (EngineSettingsService).

`analysis-agent`/`task-agent`/`review-agent`: use when symptoms, logs, metrics, regressions, or incidents need cause analysis; skip when no diagnosis decision exists.

Audits and optimizes conversion points across the funnel, applying behavioral science to produce prioritized, testable hypotheses.

Use when tenant success management, adoption optimization, expansion planning, or customer success strategy is needed. This agent specializes in SaaS customer success within the SaaSForge AI ecosystem.

Define success metrics framework — activation, engagement, retention, growth, and business metrics tied to journey stages

Guides the red-green-refactor cycle for implementing features with test-driven development, including test quality guidelines, framework setup, and commit patterns.

RICE feature prioritization with scoring and capacity planning. Usage: /rice prioritize <features.csv> [options]

MaxFuse parameter tuning for datasets with large protein:RNA cell ratios (>100:1)

Rice

Design and run a k6/Artillery load profile that measures throughput, latency percentiles, error rate, and the breaking point under concurrent traffic. Use when "load test this", "will it handle launch traffic", or "find the breaking point". Resilience-by-reading-code → audit-resilience. Never hit prod unsigned.

Rank a backlog of feature ideas by impact, effort, risk, and strategic alignment to identify the top 5 to pursue.

Selects and scores marketing ideas for SaaS products using a feasibility scoring system to prioritize high-impact, low-effort opportunities.

JACKAL — First Jump pyramider. FOX v1.6's exact five-layer entry gauntlet combined with RHINO's pyramiding mechanic. Enter at 30% on a qualifying First Jump, add 40% at +10% ROE and final 30% at +20% ROE — but only after re-validating 4h trend, SM alignment, and volume. Failed scouts cost $15 instead of FOX's $50. Full pyramids capture the same upside. DSL High Water Mode (mandatory).