Results for “pr-review”

Tracks media progress, reviews, collections, analytics, and calendar in Ryot, with automation support.

Scrapes Amazon product data from ASINs using browseract.com automation API and performs competitive analysis, comparing specifications, pricing, review quality, and visual strategies.

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

Review the current git diff for correctness, security, and performance risks before you commit. Produces severity-ranked findings with the exact file:line and a suggested fix. Pure Claude Code — no MCP, no signup.

Extract public Trustpilot company profile data from a company domain, including TrustScore, star rating, review counts, verification flags, category, contact info, and optional reply behavior metrics.

Provides a standardized interface for ingesting raw data across domains such as genomics, network analysis, document review, and spatial mapping, converting it into semantic vectors for agent use.

Defensive review of an LLM/agent application for OWASP-LLM-style risks — prompt injection, unsafe tool calls, excessive agency, and PII/secret leakage. Reads your code, flags issues with file:line. Pure Claude Code, no signup.

Review PostgreSQL code for best practices, anti-patterns, and quality standards including JSONB, arrays, custom types, schema design, functions, and security features like Row Level Security.

Post-launch metrics & funnel analysis — cohort retention, channel performance, and progress against targets from $metrics

`analysis-agent`/`task-agent`/`review-agent`: use when SQL changes affect NULL, cardinality, constraints, locks, precision, or dialect semantics; skip tool-only work.

Create, run, configure, and review BenchmarkDotNet microbenchmarks for .NET code, covering project setup, comparison strategies, and cost-aware execution.

For analysis/task/review agents using a Professional Skill on batch, stream, warehouse, lineage, replay, or data quality; not for transactions without distributed-data impact.

Designs analytics architecture, plans events, defines KPIs, sets attribution boundaries, and reviews instrumentation across product and growth.

Verifica la reproducibilidad y consistencia de un análisis de datos antes de presentarlo, validando contra la pregunta original y documentando limitaciones.

Executes MySQL database development and review tasks based on user-provided rules, covering naming constraints, index design, and data archiving for large datasets.

Tracks media progress, reviews, collections, analytics, and calendar for a Ryot instance, with automated daily and weekly reports via GraphQL API.

Write, review, debug, or interpret Python statistical models using statsmodels, including formulas, regression, GLM, time series, robust covariance, diagnostics, prediction intervals, and inference.

Extract structured best-selling product data from Amazon, including titles, prices, ratings, reviews, sales volume, and promotions, using the BrowserAct API.

Manages SurrealDB schemas as desired-state .surql files, with sync for disposable databases and reviewed rollouts for shared or production environments, plus seeding and declarative testing.

Explains MariaDB server-side prepared statements (PREPARE, EXECUTE, DEALLOCATE, EXECUTE IMMEDIATE), including syntax, allowed statements, placeholders, session scope, and restrictions. Use when writing or reviewing dynamic SQL for MariaDB.

Evaluates Power BI data model architecture, relationships, storage modes, and performance to identify optimization opportunities and ensure adherence to best practices.

Agent profile for design data pipelines, transformations, imports, exports, warehouse models, validation, and freshness checks. Use when Codex needs a specialist agent perspective for planning, implementation, review, debugging, validation, or handoff in this domain.

Explains MariaDB's three CREATE FUNCTION forms — stored functions, stored aggregate functions, and loadable UDFs — covering syntax, privileges, and behavior differences for writing or reviewing MariaDB SQL.

Use for creating, reviewing, debugging, or testing dbt SQL projects involving models, sources, ref, tests, macros, materializations, incremental models, snapshots, seeds, selectors, compiled SQL, or dbt artifacts. Do not use for generic SQL with no dbt graph, warehouse administration, semantic-layer product configuration, or orchestration outside dbt.

Audits codebases for GDPR and CCPA/CPRA compliance by inventorying PII fields, mapping data collection points, reviewing consent mechanisms, verifying data subject rights, tracing third-party data sharing, and checking retention policies.

Explains MariaDB Connector/Python's DB API 2.0 behavior, including qmark placeholders, autocommit, prepared statements, buffered cursors, connection pooling, and error handling, for writing and reviewing Python code that uses the mariadb module.

Explains MariaDB-specific behavior of DROP USER and RENAME USER, including multiple accounts per statement, IF EXISTS handling, active-connection warnings, and effects on privileges and definers. Use when writing or reviewing account-lifecycle SQL for MariaDB.

Read-only audit of a codemod or bulk mechanical transform for behavior-preservation — compiles/lints is not same-behavior. Use when "did this codemod break anything", "audit this bulk refactor", or before merging a mass find-replace. Diff quality → audit-code-review. SQL → plan-data-integrity.

Analyzes a target job description and a Chinese resume to map evidence, identify gaps, rewrite the resume for ATS/HR/interview consistency, and generate application materials for the Chinese job market.

Explains MariaDB-specific CREATE INDEX and DROP INDEX syntax, including mapping to ALTER TABLE, prefix lengths for TEXT/BLOB, lack of expression indexes, real descending indexes, IGNORED indexes, and index kinds. Use when writing or reviewing index statements for MariaDB.