959 mods tagged fastapi that install into Codex, measured the same four ways as everything else here: what each costs in tokens on every session, what a security scan found and why, whether it is the original, and what changed.
Use when doing single-beat sketch quality control and preparing correction labels from a SuperTale project path and episode number. This skill turns one episode's selected sketches plus local script beat data into selectresult.jsonl, selectsummary.json, tasks.jsonl, and labels.jsonl for edit execution. Prefer using…
Use this skill when the user wants Python data models, Pydantic models, dataclasses, TypedDicts, msgspec structs, or type-safe Python classes generated from OpenAPI, AsyncAPI, JSON Schema, GraphQL, JSON/YAML/CSV sample data, MCP tool schemas, Protocol Buffers, XML Schema, Apache Avro, or existing Python model objects.…
Turns a threat report, a malware analysis, vendor tool documentation, or a raw log sample into draft Sigma detection rules, validated against sigma-cli where a shell exists and labelled "not machine-validated" where not, each paired with a validation note covering assumptions, false positives, evasion gaps, and a test…
Use when building or modifying CRUD endpoints with FastCRUD (the fastcrud PyPI package) in a FastAPI project — covers FastCRUD, crudrouter, EndpointCreator, FilterConfig, JoinConfig, auto-relationship detection, the filter operator syntax (gte, in, ilike, etc.), cursor pagination, soft delete, and how to avoid N+1…
MCP stdio bridge for Auto Browser (metapackage for uvx auto-browser-mcp). Runs locally from the auto-browser-mcp Python package. Needs 3 environment variables to run.
Production-ready security middleware for FastAPI. Use when adding IP filtering, rate limiting, per-route security decorators, route-resolution strict mode, global behavior rules, passive/log-only mode, or Guard Agent SaaS telemetry to a FastAPI app. Covers SecurityMiddleware setup, SecurityConfig tuning, and the…
Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files). Triggers include: any mention of 'Word doc', 'word document', '.docx', or requests to produce professional documents with formatting like tables of contents, headings, page numbers, or letterheads. Also use when…
Configure or use the aiocache caching layer. Use when: adding cache reads/writes, configuring cache backends, working with TTLs, enabling/disabling caching, or understanding the NoOpCache fallback pattern.
Apache-2.0 read-only Model Context Protocol (MCP) server for GeoLens. Lets coding agents discover datasets, inspect schemas, and ask spatial questions against any GeoLens instance. Runs locally from the geolens-mcp Python package. Needs 3 environment variables to run.
★not rated 291▲
+8 todayA
tokens not measured
originalApache-2.0
Deep-research methodology with a ROLE-BASED team of parallel sub-agents. One delegatetask batch dispatches 2–3 researchers (each on a distinct sub-question), 1 critic (adversarial counter-search), and 1 fact-checker (numeric/date verification). The lead synthesises their findings into a cited report at ./report.md.…
An agent skill that turns a natural-language video topic into a short video with voice-over, subtitles, and transitions. It also creates a Jianying editing-project draft; Jianying is a video-editing app widely used in China.
Use this skill when an AI agent is connected to Horosa Skill through MCP, CLI, Cursor, Claude, Codex, OpenClaw, Open WebUI, or another local-first client and needs to call Horosa metaphysics tools, generate reports, store memory, or debug user-facing results.
An e-commerce customer-service decision skill for classifying customer questions and choosing among order, shipping, refund, and image tools. It also sets rules for checking evidence and handling risk.
Technical guidance for recognizing human actions in video without training a new machine-learning model or using an LLM. It describes a pipeline that samples video frames, estimates body poses, measures movement, and assigns labels with rules.
GlobalPercent — build a global-macro-probability panel for an investment research system. Merges public probability data from prediction markets (Polymarket + Kalshi), classifies every market into macro modules (monetary policy / macro economy / AI / etc.), and shows the whole market's expected-probability state at a…
Scans knowledge/, analyzes documents, generates summaries/concepts/connections to wiki/ with reference graph. Updates existing articles instead of creating duplicates.
★not rated 76 5mo agoA30 tokens
originalMIT
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: