Simulates API rate limits before you ship them - token bucket, fixed window, sliding log and sliding counter, per client, endpoint, tier or global - against generated or recorded traffic with retrying clients. Shows who gets 429s and for how long, fixed-window boundary bursts, retry herds, noisy neighbours, abusive clients that still get through and peaks over backend capacity. Includes an offline stdlib Python simulator with --self-test.
Checks retry, backoff and timeout settings across a call chain to prevent retry storms. Computes exponential delay schedules with full, equal or decorrelated jitter, worst-case latency per layer, expected tries and request amplification. Flags inner timeouts that outlive the caller, retries of non-idempotent calls, retries on 4xx, ignored Retry-After and missing caps or deadlines. Includes a stdlib Python calculator with --self-test.
Compares an OpenAPI YAML/JSON spec to a list of implemented routes and flags drift: missing operations, extra routes, method mismatches, and path-parameter shape differences. Use when reviewing API PRs, before a release, or asking "does our code still match the OpenAPI?". Includes a stdlib Python checker with --self-test.
Decodes a JWT without trusting it and lints the header and claims: alg none, remote jku/x5u keys, missing or expired exp, nbf/iat clock skew, millisecond timestamps, long lifetimes, iss/aud mismatches, sensitive data in the payload, and HMAC signature checks with a secret from an env var. Use when a login or API call fails with 401, or when reviewing token settings. Includes a stdlib Python inspector with --self-test.
Sizes database connection pools for Postgres/MySQL apps from a short JSON of services, pods, workers, threads and pool settings - worst-case connections at autoscale max and during deploy surges vs max_connections, busy connections from rps x hold time, per-process wait odds (Erlang C), CPU and memory limits, PgBouncer client and server limits. Recommends pool sizes or proxy settings. Includes an offline stdlib Python calculator with --self-test.
Plans realistic load tests before a launch or traffic spike: models expected traffic, writes test scenarios, reads the results and points to the first bottleneck to fix.
Finds out why your CI builds are slow: tracks job times over weeks, spots missing caches, serial steps and oversized runners, and suggests concrete changes ranked by minutes saved.