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Software Development

Code Generation

Code Generation is a practical software engineering skill for building, reviewing, and debugging code with an execution loop. It supports implementation work, code review, refactors, and fast iteration inside bounded development environments. Developers, technical founders, and platform teams benefit when they need a reliable coding operator that can move from request to code to verification. It is flexible enough for small utilities and broad enough for feature work, debugging, and review tasks. What makes it production-grade is the workflow orientation. It is not only a text generator for snippets; it is designed around coding tasks with context, focus, execution, and validation in mind.

Nexus CertifiedClaude CodeCodexOpenClawGoogle Antigravity
codingdebuggingcode-reviewexecutionrefactoring

One-Time Purchase

$19.99

Sample Output

Implementation — rate_limiter.py

Summary

Distributed token-bucket rate limiter backed by Redis. Chose token bucket over sliding window for burst tolerance — short spikes are allowed, sustained traffic is capped. Atomicity is handled with a Redis pipeline so concurrent requests against the same key don't double-spend tokens. Bucket size and refill rate are configurable per client key. Two tests written, both pass.

Design choices

Why this shape

Algorithm — burst tolerance + sustained ceiling in one primitiveToken bucket
Atomicity — single round-trip, no Lua needed at this scaleRedis pipeline
Storage hygiene — idle keys auto-expire so we don't leak hash entriesPer-key TTL
Allows fractional refills between requests; integer ceiling on spendfloat tokens
DeliverableIncludedReview note
ImplementationYesRedis-backed token bucket
TestsYesHappy path and exhaustion path
Production caveatYesLua/CAS needed for hot keys

Code

import time
import redis


class TokenBucketRateLimiter:
    def __init__(
        self,
        redis_client: redis.Redis,
        max_tokens: int = 100,
        refill_rate: float = 10.0,
    ):
        self.redis = redis_client
        self.max_tokens = max_tokens
        self.refill_rate = refill_rate  # tokens per second

    def allow_request(self, client_key: str) -> bool:
        key = f"ratelimit:{client_key}"
        now = time.time()
        pipe = self.redis.pipeline()
        pipe.hmget(key, "tokens", "last_refill")
        result = pipe.execute()[0]

        tokens = float(result[0]) if result[0] else self.max_tokens
        last_refill = float(result[1]) if result[1] else now
        elapsed = now - last_refill
        tokens = min(self.max_tokens, tokens + elapsed * self.refill_rate)

        if tokens >= 1:
            tokens -= 1
            allowed = True
        else:
            allowed = False

        pipe.hset(key, mapping={"tokens": tokens, "last_refill": now})
        pipe.expire(key, int(self.max_tokens / self.refill_rate) + 60)
        pipe.execute()
        return allowed

Tests

def test_allows_requests_within_limit():
    limiter = TokenBucketRateLimiter(redis_client, max_tokens=5, refill_rate=1.0)
    results = [limiter.allow_request("test-client") for _ in range(5)]
    assert all(results)  # first 5 requests allowed


def test_blocks_after_exhaustion():
    limiter = TokenBucketRateLimiter(redis_client, max_tokens=2, refill_rate=0.1)
    limiter.allow_request("exhaust-client")
    limiter.allow_request("exhaust-client")
    assert not limiter.allow_request("exhaust-client")  # third request blocked
test_allows_requests_within_limit PASSED
test_blocks_after_exhaustion PASSED
2 passed in 0.34s

Tests written this round

Coverage

Requests within bucket capacity all return Truehappy path
Third request after two on a 2-token bucket returns Falseexhaustion
Burst-then-wait refill verified locally; not yet a test fixturemanual

Follow-ups

Race condition window

The pipeline reads then writes; between the two there is a small window where a second request on the same key could read stale token state. Acceptable at current QPS but a Lua script (CAS-style update) would close the gap if the limiter is moved onto a hot per-user path.

Observability hooks

No metrics emitted yet. Worth adding a counter for allowed/blocked decisions per key prefix so we can spot misconfigured limits before customers complain.

Config surface

max_tokens and refill_rate are constructor args. If the limiter needs to be configured per-tenant at runtime, switch to fetching them from a config map keyed on client_key prefix.


This sample illustrates the skill's output format. The implementation is illustrative; harden before production use.

View full sample →

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Includes support for Claude Code, Codex, OpenClaw, and Google Antigravity in the same license.

Also in Code Generation & Review

Bundle price: $44. Compare this skill with the full workflow bundle or Pro access.

Best for

Engineers using an AI coding harness as their primary editor for greenfield features, refactors of self-contained modules, and prototype work where the iteration loop matters more than artisanal style. Best on TypeScript, Python, and Go codebases under ~500K lines where the model can hold enough of the project in context to make safe changes.

Not ideal for

Very large monorepos where critical context lives in files the agent won’t read, or for languages and frameworks where training data is thin (proprietary DSLs, legacy COBOL, embedded firmware). Also a poor fit as a substitute for senior engineering review on safety-critical or revenue-critical paths.

Included in this purchase

  • Claude Code, Codex, OpenClaw, and Google Antigravity skill files.
  • Setup guidance for the right adapter in your workspace.
  • One-time license for the purchased skill version.

Setup

Plan for a short setup in the repository or workspace where the skill will run. Some coding familiarity helps for implementation-heavy outputs.

Claude CodeCodexOpenClawGoogle Antigravity

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Future Updates

This purchase includes the current version of the skill. If you want future adapter updates — meaning compatibility and packaging updates as supported platforms evolve — plus new catalog additions included automatically, upgrade to Pro.

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