Results for “metrics”

Structure board meetings, investor updates, and executive communication that builds trust and drives decisions.

High-performance graph analysis for beads issue tracker using 9 metrics (PageRank, Betweenness, HITS, Critical Path, etc). Provides AI-driven task prioritization, dependency analysis, and architectural health monitoring via robot protocol.

Comprehensive architecture baseline scan. Two-wave AI analysis producing blueprint.json, per-folder CLAUDE.md, AI-synthesized rules, and health metrics. Use for first-time baselines or major refactors.

Turns client wins into structured case studies in multiple formats. Gathers before/after metrics, structures as Problem-Solution-Results, and outputs landing page copy, one-pager, social snippets, and email insert.

Classify AEM 6.5 LTS and AMS workflow issues by symptom, gather relevant logs and metrics, and map to runbooks or Splunk searches.

Track elapsed time from a set epoch with tamper-evident locking, supporting count-up, count-down, and count-between modes, milestones, and email notifications.

Use this skill for feature flags, gradual rollout, kill switches, metrics, experiment gates, rollback. Trigger when the task involves programming work related to Feature Flag Rollout, implementation, audits, debugging, strategy, or validation.

Visualize and map user flows with Mermaid diagrams, decision points, error states, and conversion metrics to optimize user journeys. Use when the user requests user flow mapping or provides relevant inputs for this workflow.

Operate and extend NanoClaw v2, a zero-dependency session-aware REPL built on claude -p, with commands for model switching, skill loading, session branching, search, compaction, export, and metrics.

Extract public Trustpilot company profile data from a company domain, including TrustScore, star rating, review counts, verification flags, category, contact info, and optional reply behavior metrics.

Analyzes past agent sessions to identify recurring failures and skill gaps, then automatically creates or patches skills and runs self-evolution to fix them, tracking improvement over time.

Perform survival analysis and time-to-event modeling in Python using scikit-survival, including Cox models, random survival forests, gradient boosting, survival SVMs, and evaluation metrics like concordance index and Brier score.

Verify an artifact that is about to leave the building — a partnership brief, pitch page, press release, customer email, RFP response, or any document sent to someone outside the org. Runs six checks before send — premise, confidentiality forward-test, evidence class, cold read by recipient personas, AI read, and tone metrics — and returns what to change with replacement copy. Use before sending anything outward-facing that carries customer detail, factual claims about a counterparty, or an ask.