LLM Mart Basic

Competitive landscape analysis, competitor comparison, peer positioning, market share dynamics, competitive moat assessment, Porter five forces, industry competition, competitive advantage analysis, market positioning, strategic group mapping, compare competitors

Earnings sentiment analysis, analyst estimates vs guidance, earnings surprise history, consensus sentiment, earnings revision trends, analyst rating changes, earnings beat miss track record, guidance accuracy, whisper numbers, pre-announcement sentiment

Recent quarter performance analysis, quarterly earnings review, last quarter results, quarterly financial performance, analyze recent quarter, Q4 earnings, quarterly revenue breakdown, EPS this quarter, margin analysis recent quarter, sequential growth, quarterly performance revi

Risk analysis, regulatory risk assessment, competitive risk, macro risk, technology risk, litigation risk, financial risk assessment, enterprise risk, operational risk, geopolitical risk exposure

Secular technology trends, technology adoption cycle, disruption risk, AI impact analysis, digital transformation, industry 4.0 trends, technology moat, innovation trajectory, R&D effectiveness, tech competitive positioning

Turnaround analysis, stagnation detection, performance inflection, operational improvement, restructuring analysis, management change impact, cost cutting effectiveness, business transformation, recovery trajectory, operational metrics improvement

Valuation methods analysis, DCF inputs, comparable multiples, P/E ratio, EV/EBITDA, price to book, valuation assumptions, relative valuation, intrinsic value, fair value estimate

Weekly clinical-trial status diff — the 11-category change report over the stored weekly snapshots (spec 055 FR-B03). Surfaces exactly what changed on the trial registry for your coverage: New / Suspended / Withdrawn / Terminated / Recruiting / Recruitment-Complete / Completed /

Med-adapted earnings preview: consensus estimates, historical surprises, guidance sensitivities, and the FDA-catalyst overlay (PDUFA/AdCom/trial readouts near the print) for biotech/pharma names.

Device-track catalyst analysis: 510(k), PMA, and De Novo decision events, CMS coverage and NTAP milestones, recalls and watch actions as risk signals, and post-market surveillance obligations — dated, verified, and sized per event for any medtech ticker or watchlist.

CDER-track catalyst analysis for medicines: PDUFA target dates, AdCom votes, sNDA/sBLA label expansions, biosimilar interchangeability and 180-day exclusivity, Orange Book state, and CRL remediation timelines — enumerated, verified, and sized per event for any biotech/pharma tick

Vaccine catalyst analysis across the two-gate path: CBER BLA review and the ACIP recommendation gate that turns FDA approval into commercial availability. Lot release, procurement milestones, pediatric bridging, and healthy-population efficacy context — dated, verified, and sized

Weekly product-level commercial tracking — TRx/NRx with current/4-wk/12-wk share and YoY, launch curves overlaid with same-class analogs plus a consensus-implied trajectory, LOE/biosimilar erosion series, GTN/net-price stress brackets, and per-row data-caveat discipline. Use to t

Post-event analyst note (conferences, KOL events, site visits) with the professional note anatomy — headline verdict, per-stock takeaways with model numbers, KOL distillation, cross-trial comparison lattices, modeled deltas vs consensus (peak × POS), three what's-changed vectors,

Patient-flow market sizing for med products — prevalence → diagnosed → interested → affordable → covered → treated → persistent, priced as price × duration per cohort, with capacity constraints, named historical analog anchoring, and always bull/base/bear named-driver grids. Use

Med peer benchmarking: select actual biotech/pharma peers via the med universe (drug/indication overlap where possible) and compare med-relevant metrics — pipeline depth, catalyst density, cash position, margins, valuation multiples.

Device pipeline analysis: feasibility and pivotal study stages, design-iteration cycles, RWE studies, and post-market obligations, with reimbursement-aware value framing and decision-track awareness across the med universe.

Use when a Cypress end-to-end test has already run and failed and the user wants the root cause and a concrete fix. Trigger on a failing Cypress spec, Timed-out-retrying command, unresolved selector, cy.intercept alias or request race, suite-breaking hook, retry-only flake, hydra

Use when reviewing Playwright or Cypress E2E specs, Page Objects (POM), PRs, pull requests, patches, diffs, or changed test files — asked to review tests, audit test quality, or find weak, flaky, or silently-passing tests; when tests pass CI but prove nothing or miss bugs; when a

Use when a Playwright end-to-end test has already run and failed and the user wants the root cause and a concrete fix. Trigger on a failing Playwright spec, TimeoutError, broken or ambiguous selector, post-deploy suite failure, retry-only flake, hydration or timing race, or a pas

Use MCP Inspector to connect to local or remote servers, inspect capabilities, call tools, read resources, test prompts, and diagnose failures before release.

Build an MCP server in TypeScript with focused tools, validated schemas, local and remote transports, Inspector tests, and production security controls.

An MCP server exposes tools, resources, or prompts through a standard protocol so an AI application can discover and use external capabilities.

Treat an AI agent skill as both an instruction package and a software dependency: inspect what it says, what it runs, what it can access, and how it updates.

Add remote HTTP or local stdio MCP servers to Claude Code, choose the right scope, protect credentials, verify the connection, and test with least privilege.

Skills teach Claude a repeatable method, connectors provide governed access to apps and live data, and plugins package related capabilities for installation and sharing.

Use an agent skill to package reusable know-how and workflow instructions. Use an MCP server when an agent needs live, governed access to external data or actions.

Custom commands and skills can both create a slash-invoked workflow in Claude Code. The important choice is how the workflow is discovered, shared, and permissioned.

A useful Claude skill solves one recurring engineering job, is easy to inspect, and saves more time than it creates in setup and review.

Claude skills can live in your Claude account, your local Claude Code setup, or a repository. Install them where the sessions that need them can load them.

Build a portable AI agent skill from one repeatable job: a precise description, concise instructions, focused resources, and tests that prove it works.

AI agent skills package instructions, scripts, references, and templates into portable folders an agent loads only when the task calls for them.

AI made publishing cheap, which is exactly the problem. What separates a page worth ranking from a competent summary of the first ten results.

A prompt that works once isn't a quality system. Five cases, an observable rubric, and a regression set will tell you whether a change helped.

One character of YAML, four pods that never started, and two safety nets I didn't know were holding. Every restart is an audit. Schedule them before they schedule you.

"Verify your work" isn't an instruction. It's a mood. Here's the version that's an instruction. Verify with a different mechanism than the one that made the claim.

A prompt that works once may still fail in production. A lightweight eval set gives you repeatable cases, a clear rubric, and a way to see whether a prompt change actually improved the workflow.

The best AI tool is not the one with the longest feature list. It is the one that solves a defined job reliably, fits the workflow, handles data appropriately, and remains useful after the novelty wears off.

Use AI to speed research without losing trust. Learn to find primary sources, verify claims, preserve uncertainty, and keep an auditable source trail.

Better prompts aren't magic wording. They're short briefs that hand the model a task, the context it can't infer, the limits, and a quality bar.

What do I know about a topic

Find and add missing connections

Audit structure and repair what is mechanical

Merge two pages

Record a dated metrics snapshot

The monthly structural review

Find unreachable pages

Outline a piece from your concept pages

Audit what should not be in the vault

Where a project stands

Create a project

Find what is safe to remove

Check what is safe to publish

Test yourself on your own pages

Rename a page and fix every link

Write a research report

Fix a page's type

Periodic review of what the vault learned

Undo the last run

Set up scheduled maintenance

Make any song you can imagine

Leading AI-powered video generation platform that specializes in creating hyper-realistic talking avatars

Hermes Agent is an open-source, self-improving autonomous AI agent developed by Nous Research

Kilo Code is a popular, open-source AI coding agent and "agentic engineering" platform designed to help developers build, refactor, and debug software faster

General-purpose agent in one static Go binary. ReAct loop, ACP server for IDEs, OpenAI-compatible REST API with embedded web UI, Telegram gateway, cron schedule…

Autonomous agent framework with structured memory, safety hooks, and loop management. Built by the agent that runs on it.

TSP自托管、零运维的 A 股「选股 + 监控 + 回测」量化工作台 | 基于 TickFlow 数据源 | LLM能力驱使策略定制+个股分析+复盘 | 自由接入第三方数据源与个性化扩展数据 | 个人开源 ,非TickFlow官方项目

Curated, verified Agent Skills powered by ModelStudio.

Run Claude Code, Codex, Antigravity, Cursor Agent and OpenCode as one runtime — persistent sessions, multi-agent councils, an OpenAI-compatible endpoint, an MCP…

pi had nothing (nothing), so I made something (something) — sorry mariozechner-senpai, I went ahead and lovingly soiled your pure pi for you. opinionated fork o…

A persistent workspace for development work that self-improves and continues beyond one session.

Open-source memory and context for user-aware agents: scoped memory, provenance, retrieval quality, correction, boundaries, evals, and MCP/HTTP access.

📚 A zero-dependency, git-backed micro-lesson library for AI Agents to asynchronously share and search verified debugging experience. Python stdlib only. | http…

Deterministic, local-first memory and guardrails for AI coding agents with no LLM in the hot path.

Deterministic spec-orchestration for local LLMs in the pi coding agent — drives prompts through refine→research→grill→compose→critique, with bundled web/docs/fe…

Native Safari browser automation for AI agents. 97 tools via AppleScript — zero overhead, keeps logins, runs silently in background. Drop-in alternative to Chro…

Agent OS: keep specialist agents in a hub, spin up a temporary orchestrator per task. Local-first, works with any model.

Git for agent memory. Branches, diffs, PRs, and rollback for what your agents know.

Multi-Provider AI Gateway - No personal logs by design. Model autodiscovery, Failover groups, High availability, Android companion app, and more - "Because we h…

Production-grade MCP server for MikroTik RouterOS with secure AI-native network automation.