Results for “token-screening”

Access 31 pay-per-use tools for quantum security, agent safety, research, data, and earn on Base, paid via x402 protocol.

Evaluates Base ERC-20 tokens by contract address, returning a 0-100 score across five criteria, launch protocol classification, security flags, and a narrative interpretation.

Perform forensic on-chain analysis of EVM tokens to detect scams, rug pulls, and soft rugs by cross-referencing on-chain state against team narratives.

Scan text or a file for accidentally committed secrets (API keys, tokens)

Scans TON (The Open Network) smart contracts for 3 critical vulnerabilities including integer-as-boolean misuse, fake Jetton contracts, and forward TON without gas checks. Use when auditing FunC contracts.

Scans Algorand smart contracts for 11 common vulnerabilities including rekeying attacks, unchecked transaction fees, missing field validations, and access control issues.

Scans codebases for security vulnerabilities by reasoning about code context, data flow, and component interactions, covering injection flaws, secrets exposure, authentication issues, and weak cryptography across multiple languages.

Deploy and manage projects on Vercel using token-based authentication, without interactive login.

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".

Detects and responds to OAuth token theft and replay attacks in cloud environments, focusing on Microsoft Entra ID token protection, conditional access policies, and sign-in anomaly detection.

Reduce OpenClaw token usage and API costs through smart model routing, heartbeat optimization, budget tracking, and native 2026.2.15 features (session pruning, bootstrap size limits, cache TTL alignment). Use when token costs are high, API rate limits are being hit, or hosting multiple agents at scale. The 4 executable scripts (context_optimizer, model_router, heartbeat_optimizer, token_tracker) are local-only — no network requests, no subprocess calls, no system modifications. Reference files (PROVIDERS.md, config-patches.json) document optional multi-provider strategies that require external API keys and network access if you choose to use them. See SECURITY.md for full breakdown.

Token architecture, component specifications, and slide generation. Three-layer tokens (primitive→semantic→component), CSS variables, spacing/typography scales, component specs, strategic slide creation. Use for design tokens, systematic design, brand-compliant presentations.

Intercepts responses to let users choose the depth and token budget before answering, with heuristic token estimation and preset depth levels.

Generates at most one token recommendation and one prediction-market pick per run, each with a falsifiable thesis, entry, sizing, and kill criterion. Returns NO_PICK when no candidate meets the bar.

Computer vision engineering skill for object detection, image segmentation, and visual AI systems. Covers CNN and Vision Transformer architectures, YOLO/Faster R-CNN/DETR detection, Mask R-CNN/SAM segmentation, and production deployment with ONNX/TensorRT. Includes PyTorch, torchvision, Ultralytics, Detectron2, and MMDetection frameworks. Use when building detection pipelines, training custom models, optimizing inference, or deploying vision systems.

Design a theming architecture that supports brand variants, dark mode, and high-contrast modes with token mapping.

Performs advanced network reconnaissance using Nmap's scripting engine, timing controls, evasion techniques, and output parsing to discover hosts, enumerate services, detect vulnerabilities, and fingerprint operating systems across authorized target networks.

Protect APIs from abuse and resource exhaustion by implementing rate limiting with token bucket, sliding window, and fixed window algorithms using Redis-backed counters, API gateway plugins, or application middleware.

Detect privilege escalation attempts including token manipulation, UAC bypass, unquoted service paths, kernel exploits, and sudo/doas abuse across Windows and Linux.

Run authenticated vulnerability scans using valid credentials to deeply inspect target systems for missing patches, misconfigurations, and security weaknesses.

Audits typographic decisions on a screen for scale usage, readability, consistency, and token compliance, providing specific fixes.

Audit design token usage across a product for consistency and coverage, identifying hard-coded values and gaps.

Scans top 24-hour token movers across major chains via GeckoTerminal, applies pump-risk filters, and outputs a chain leaderboard with per-chain top 5 runners.

4-stage funnel that screens all 500+ Hyperliquid perps down to the top trading opportunities. Scores setups 0-400 across smart money, market structure, technicals, and funding. BTC macro filter, hourly trend gate (counter-trend = hard skip), cross-scan momentum tracking. Near-zero LLM tokens — all computation in Python. Use when scanning for new trading opportunities on Hyperliquid, evaluating setups, or checking market conditions.

Token Standards

Use when a project's visual foundation — typography scale, color palette, spacing — needs establishing as canonical design tokens; the target has no design system yet (the 0→1 case), the A-Team design phase needs tokens for the lofi and the spec's design-system mapping, or a human runs the token flow standalone ("set up the design system", "pick fonts and colors", "define design tokens"). In the A-Team pipeline it is conducted by ateam-design in pipeline mode — no interview; inputs derive from context.md's

Token-efficient code review using Tree-sitter AST graphs and MCP. Reduces AI assistant token usage by 6.8–49x by computing blast radius of changes instead of reading entire codebases. Uses SQLite graph database for structural analysis.

Use for UI/UX and design-system work when Codex should convert visual direction or existing UI into reusable design tokens.

Identifies the weakest samples per ground-truth label in NVIDIA TAO VCN Classify experiments by running a Docker container that performs threshold sweep, weakness scoring, and per-lighting expansion, then surfaces top-K weak samples for downstream augmentation or relabeling.

Embeds target and source image parquets, then mines nearest-neighbour source images for augmentation in VCN AOI workflows.

Inspect B20 token contract addresses on Base to verify factory recognition, initialization, policies, pause state, and risk flags via the public B20 Console API.

Deploy and monitor Canary Tokens via the Thinkst Canary API for deception-based breach detection using web bug tokens, DNS tokens, document tokens, and AWS key tokens.

Scan container images, filesystems, and Kubernetes manifests for vulnerabilities, misconfigurations, exposed secrets, and license compliance issues using Aqua Security Trivy with SBOM generation and CI/CD integration.

`task-agent`/`review-agent`: use when image layers, build context, runtime user, secrets, health checks, shutdown, or provenance change; skip when container behavior is unaffected.

Reads a public API using a declared token.