Results for “performance-bonds”

Monitor bonding curves, graduation progress, and trade analytics on Pump.fun

Constant-product AMM bonding curve math for Pump token pricing — buy/sell quoting, fee-aware calculations, market cap computation, tiered fees, ceiling division, virtual vs real reserves, and edge-case handling.

`analysis-agent`/`task-agent`/`review-agent`: use when latency, throughput, bundle, memory, CPU, query, rendering, or resource cost needs a budget; skip without performance risk.

Performance-coaching mode for repeated failures, passive behavior, completion-quality issues, or explicit try-harder requests. Uses structured troubleshooting and evidence-first delivery habits.

Performance-coaching mode for repeated failures, passive behavior, completion-quality issues, or explicit try-harder requests. Uses structured troubleshooting and evidence-first delivery habits.

Performance Profiler

Score and rank options contracts for any ticker using a multi-factor model covering liquidity, IV attractiveness, Greeks balance, and risk/reward. Returns scored option chains with the best contracts highlighted.

Reviews closed trades, partial exits, and monthly trade aggregates for process adherence, risk discipline, execution quality, and evidence-based trading behavior patterns.

Use when the app is slow, pages take too long to load, API responses exceed 200ms, memory usage is high, or renders are excessive. For profiling, identifying bottlenecks, optimizing React renders, reducing bundle size, improving database query speed, and measuring before/after improvements. Activate when user says "it's slow", "optimize this", "reduce load time", or "too many re-renders".

Use to compare BPO sites, vendors or partner teams fairly, adjusting for the work mix each is given before concluding anything about performance. Trigger for "compare our BPO sites", "which vendor is performing best", "site A scores lower than site B", outsourcer QBR packs, partner MI reporting, or setting contractual quality targets with a vendor.

Analyzes Stockbee-style Day 1 Episodic Pivot candidates by scoring catalyst quality alongside price/volume confirmation, gap/range expansion, volume shock, neglect/revaluation context, liquidity, and risk to the EP-day low.

Transaction-verified trading signals on Base. Register agent as signal provider, publish trades with TX hash proof, consume signals from top performers via REST API. All track records verified against blockchain data. No fake performance claims. Triggers on: "publish signal", "post trade signal", "register provider", "subscribe to signals", "copy trade", "bankr signals", "signal feed", "trading leaderboard", "read signals", "get top traders".

Aggregate closed trades from trader-memory-core into a weekly performance report with win rate, expectancy, profit factor, R-multiple, MAE/MFE, and pattern breakdowns by source skill, exit reason, sector, and mechanism.

Runs a side-by-side walk-forward backtest of a Bull Put Spread strategy with and without a FearScore entry signal, comparing performance metrics over ~8 years of daily data.

Sports betting fundamentals including spreads, moneylines, totals, parlays, teasers, props, and futures. Use when analyzing sports betting markets, converting odds formats, evaluating bet types, or building a sports betting strategy. Also trigger for 'point spread', 'moneyline', 'over under', 'parlay', 'prop bet', 'teaser', 'sports odds', or 'sportsbook'.

Measure-don't-guess performance audit across web, mobile, backend, and data layers — produces burndown and optimization plan with no fixes in this pass. Use when asked to "performance audit plan", "perf burndown", "measure before optimize", "bundle size audit", "LCP slow", "N+1 audit plan", "plan performance.

Trigger: web performance, slow load, bundle size, lazy loading, LCP, CWV optimization, fetch priority. Scope: Frontend optimization, loading speeds, asset minimization. Boundary: Excludes backend database indexing or visual design systems.

Measures application performance first, identifies bottlenecks, and applies targeted fixes for frontend and backend systems.

Systematically profile Node.js, Python, and Go applications to identify CPU, memory, and I/O bottlenecks, generate flamegraphs, analyze bundle sizes, optimize database queries, and run load tests with k6 and Artillery.

Benchmark, load test, capacity plan, and cache with k6, JMeter, Locust, and pgbench. Use when the user says "slow", "performance", "load test", "stress test", "how many users can it handle", "capacity", "cache", "benchmark", "k6".

波总个人财务中枢 v2.0 — 债务追踪 + 消费分析 + 还款日预测 + 暴力催收。当你收到"还了XX YY元""花呗清了""我的债务""截图""消费"等财务相关指令时使用。

Assess Active Directory security posture using PingCastle, BloodHound, and Purple Knight to identify misconfigurations, privilege escalation paths, and attack vectors.

Scores competitors across nine weighted dimensions with explicit 1–5 rubrics and a tension plot, producing comparable profile cards for competitive analysis.

Entry-point router for the local Pump.fun skill suite. Use when the user asks about launching Pump.fun tokens, bonding-curve or AMM trading, quotes, fees, claims, incentives, SDK work, agent/MCP integration, security, testing, or release workflows.

Token budget analytics and ROI scoring for AI agent actions. Track token cost per fix, detect wasteful loops, auto-route to fast tier when burn rate is too high. Integrates with token-budget-guard.sh hook. Triggered by /cost-report, "how much did that cost", "token usage", "am I wasting tokens".

Plan and review paid-media budgets, bidding, pacing, marginal return, forecasts, CPA, ROAS, MER, LTV:CAC, constraints, and allocation across supported platforms.

Renders Markdown, HTML, or PDF paid-advertising reports from a validated Claude Ads JSON run bundle.

Volume-based PUMP token reward system with day-indexed epochs, pro-rata distribution, accumulator tracking, and cross-program claiming on Solana.

Buy and sell tokens on Pump.fun bonding curves and AMM pools

Performance — Forge Skill

Improves measured performance while preserving correctness, reliability, and maintainability.

Screens for dividend growth stocks with 12%+ annual dividend growth and 1.5%+ yield that are experiencing temporary pullbacks identified by RSI oversold conditions (RSI ≤40).

Use this skill for performance, reliability, observability, SLO risk, production diagnostics. Trigger when the task involves agent profile work related to Performance SRE Agent, implementation, audits, debugging, strategy, or validation.

Analyze organic content performance for any active brand — your own published posts (engagement by topic, format, persona, angle, hook archetype, Direction) plus competitor content benchmarking — and produce a Performance Brief that feeds the social calendar.

Use when tuning RL reward function weights, fixing reward hacking, or addressing P&L gradient issues