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Business logic flaws are application vulnerabilities where valid functions are abused in unintended ways: price manipulation via hidden field tampering, workflow step-skipping, function call limit bypass (coupon reuse), process timing exploitation (race conditions on balance updates), and request forging via guessable/predictable parameters. Detect using Burp Suite proxy interception, HTTP POST/GET parameter analysis, and misuse-case testing against multi-step workflows. Tools: Burp Suite, OWASP ZAP.

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Business logic vulnerability playbook. Use when reasoning about workflows, race conditions, price manipulation, coupon abuse, state machines, and multi-step authorization gaps.

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Identify and exploit flaws in the core business rules and logic of web applications. This skill focuses on manipulation of application workflows, pricing, inventory limitations, and multi-step processes. Use this skill when bug hunting or testing e-commerce, banking, or SaaS platforms where standard technical vulnerabilities (e.g., XSS/SQLi) are not present but the application's logic is flawed.

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Entry P1 category router for business logic testing. Use when workflow abuse, race conditions, pricing flaws, or multi-step state attacks matter more than parser-level input injection.

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Cloudflare-first platform selection. Decision trees for Workers, D1, R2, KV, DO, Queues, Vectorize, Containers, Sandboxes, Flagship, Agent Memory, Workflows v2. Default stack, override conditions, auth, data patterns, reliability.

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One to three sentences describing what this skill does and the conditions under which an agent should activate it. Start with a verb, name the tools and artifacts involved, and end with the trigger phrasing (e.g. "Activates for requests involving ...").

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Use when selecting or composing behavior-preserving refactoring techniques after structural evidence is known, especially when multiple candidate transformations, preconditions, or ordering choices must be compared.

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Use when a task needs the judgment of an Environmental Health Specialist (Registered Sanitarian) — classifying a food-establishment temperature violation as critical vs. priority-foundation, determining pool closure and hyperchlorination protocol after a fecal/vomit incident, evaluating a septic percolation test against site-limiting conditions, deciding whether a complaint pattern meets the threshold for an outbreak investigation, or issuing an imminent-health-hazard closure.

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Use when a task needs the judgment of a Dragline and Excavating/Loading Machine Operator in surface mining — converting a rated bucket capacity into bank cubic yards moved per shift, deciding whether a swing angle or spoil-placement plan needs to be flagged to pit engineering, matching loading pass count and payload to a haul truck's rated capacity, checking ground bearing conditions before walking or tracking a machine onto fill or spoil, or reading a berm/highwall condition against MSHA thresholds.

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Use when a task needs the judgment of a construction/maintenance painter — scoping an exterior or interior repaint, diagnosing why a paint job failed (blistering, alligatoring, peeling), pricing a job against real coat-count and prep requirements, deciding whether EPA lead-paint rules apply, or timing application against moisture and weather conditions.

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Use when a task needs the judgment of a Construction and Building Inspector — deciding whether a phase of work passes a hold-point inspection (foundation, framing, rough-in, insulation, final) or gets red-tagged, writing a correction notice that will hold up on appeal, resolving a conflict between the approved plans and field conditions, applying a specific IRC/IBC section to a borderline condition (egress, smoke/CO detector placement, GFCI/AFCI locations), or deciding whether schedule pressure from a contractor changes the call.

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Use when a task needs the judgment of a Business Teacher, Postsecondary — grading case analysis on the rigor of business reasoning rather than matching a single "correct" answer, updating stale textbook examples against current market conditions rather than teaching them as still-current, distinguishing taught analytical frameworks from personal business opinion presented as universal fact, and preserving the incomplete-information trade-offs of real business decisions rather than simplifying problems into false certainty.

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Use when a task needs the judgment of an atmospheric scientist/operational meteorologist — interpreting ensemble forecast guidance, deciding whether conditions cross a severe-weather warning threshold, calibrating a raw model probability against verification climatology, or writing a forecast discussion or warning product under time pressure.

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Use when a task needs the judgment of an auto-glass installer/repairer — deciding whether a chip or crack qualifies for resin repair versus full replacement, calculating a safe drive-away time for the adhesive and conditions on a job, determining whether a windshield replacement triggers ADAS camera recalibration, or diagnosing a cut-out/pinch-weld defect before it becomes a leak or corrosion claim.

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Use when a task needs the judgment of a Biomass Plant Technician — adjusting combustion parameters in response to actual measured fuel moisture content rather than a fixed setpoint, diagnosing a fuel feed interruption as mechanical bridging rather than a combustion issue, adjusting soot-blowing frequency to actual observed slagging conditions rather than a fixed calendar schedule, or monitoring emissions more actively given fuel batch variability rather than a "set and monitor occasionally" approach appropriate for consistent fossil fuel.

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Audit an existing Lamport-style hierarchical mathematical proof forward for validity and whether its hierarchy, scope, dependencies, side conditions, and proof constructs discharge the stated theorem. Use when the central question concerns a top-down proof with numbered levels, subproofs, ASSUME/PROVE, SUFFICES, PICK, CASE, DEFINE, Q.E.D., or prose equivalents. For an ordinary proof that first needs source-preserving hierarchy, use convert-lamport; for conclusion-first AND/OR obligation reconstruction, use reverse-lamport. Do not use to generate or replace a proof, or to audit Lean, Coq, Isabelle, or other proof-assistant source.

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Audit an existing mathematical, logical, algorithmic, or technical proof from its stated conclusion backward as a bounded AND/OR graph of exact obligations. Use to reconstruct conclusion dependencies, determine whether a proof-supplied route establishes the conclusion, or expose hidden assumptions, unmet side conditions, cycles, overly strong steps, or silent route switches. For a source-mapped Lamport rendering use convert-lamport, and for forward hierarchy, construct, and scope conformance use forward-lamport before this skill. This does not decide full theorem-level entailment by searching for a different proof; do not turn the audit into a linear reversed proof, exhaustive proof search, or replacement proof.

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Write measurable acceptance criteria for requirements or user stories. Use when the user says "write acceptance criteria", "definition of done", "how do we test this", "fit criteria", "given when then", "Gherkin scenarios", "what does done look like", "testable conditions", "how will we know this works" - even if they don't explicitly say "acceptance criteria".

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Prove existing work meets acceptance conditions without expanding scope. Use for validation-only tasks, completion checks, focused gate runs, and last-mile proof.

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Diagnoses GKE nodes reporting NotReady or Unknown status by inspecting node conditions, events, kubelet/containerd logs, and node metrics, then proposing safe remediations. Use when nodes show NotReady, when the kubelet stops posting node status, or when workloads are evicted or stuck Pending due to node health. Don't use for pod-level application failures (use gke-workload-troubleshooting), autoscaler scale-up/scale-down decisions (use gke-cluster-autoscaler), or non-GKE compute.

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Configure single-project Google Cloud Logging: regional log buckets, log sinks, log views, restricting or hiding sensitive logs in the default view (_Default) filter, IAM permissions for views (Logs View Accessor, IAM conditions), logs-based metrics, log exclusions, and sampling. Don't use for cross-project logging or multi-project setups.

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Configures alerting policies in Terraform for Google Kubernetes Engine (GKE) clusters, workloads, and services using PromQL and Google Cloud Managed Service for Prometheus. Use when writing, analyzing, validating, or deploying Terraform alerting policies to monitor GKE service latency, traffic, error rates using Multi-Window Multi-Burn-Rate SLO alerts, memory saturation, and cluster health such as CrashLoopBackOff and Node NotReady conditions. Don't use for non-GKE compute runtimes such as standalone Compute Engine VMs or standalone Cloud Run services without GKE.

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Diagnoses and prevents vbar_control_agent segfaults, out-of-memory (OOM) errors, and TPU device initialization failures on TPU v6e nodes in GKE caused by race conditions during TPU device resets or high-frequency metrics polling. Use when troubleshooting vbar_control_agent crashes, memory cgroup OOMs in serial console logs, tpu-device-plugin metrics checksum corruption errors, or custom TPU metrics collection conflicts on GKE TPU v6e nodes. Don't use for general non-TPU container OOM troubleshooting or standard GKE node lifecycle operations.

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Leverages BigQuery's built-in machine learning and GenAI capabilities for advanced data analytics. Use when you need to write SQL queries that perform time-series forecasting, predict values, detect outliers or anomalies, find key drivers, perform semantic search or vector search, classify text, calculate similarity, summarize content, translate language, evaluate models, filter by semantic conditions, measure the causal effect of an intervention, compute correlations between columns, detect change points or structural breaks, extract trend or seasonality components, or leverage generative AI capabilities in BigQuery. Do not use for general BigQuery dataset, table, or job management requests.

日本語の概要は準備中です。原文の説明を表示しています。