How do I install the Stockvaluation Io skill?

Run npx skillmds@latest add dvcrn/stockvaluation-io in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Stockvaluation Io safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: CAUTION, Skill Scanner: WARNING. Capability flags: makes network calls, reads secrets. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Stockvaluation Io?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Stockvaluation Io free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Stockvaluation Io?

dvcrn (@dvcrn) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Stockvaluation Io by dvcrn — Agent Skill

Name: Stockvaluation Io
Rating: 4.2 (5 reviews)
Author: dvcrn

File contents

StockValuation.io

Use this skill when the user wants help with StockValuation.io setup, local DCF runs, LLM provider or model experiments, prompt dumps, Docker logs, or valuation API usage.

Workflow

Identify the goal: setup or startup, run a valuation, compare models, debug a failure, or inspect repo internals.
If the repo is available, inspect README.md, .env.example, docker-compose.local.yml, and relevant service files before answering.
For installation, startup, and basic valuation runs, read {baseDir}/references/setup-and-run.md.
For provider or model changes, prompt dumping, or controlled comparisons, read {baseDir}/references/model-and-provider-experiments.md.
For runtime failures, health checks, logs, or recovery steps, read {baseDir}/references/troubleshooting.md.
Prefer exact commands, explicit service names, and reproducible steps.

Operating Rules

Prefer the manual clone plus Docker Compose path by default.
If the user wants the installer, tell them to download or inspect install.sh locally before running it instead of recommending curl | bash.
Never ask the user to paste real API keys into chat. Tell them to set keys in their local environment or .env.
Never print .env contents, echo live secrets, or suggest committing local secret files.
Treat prompt dumping as privacy-sensitive. When DUMP_PROMPTS=true, prompt contents are written to PROMPT_DUMP_DIR on disk.
Treat container teardown and volume deletion as destructive. Only suggest down -v when the user explicitly asks to reset local state.
When only LLM settings change, restart valuation-agent and bullbeargpt unless the user also changed other infrastructure.
When comparing experiments, keep the ticker, env changes, and output differences explicit so the comparison stays attributable.

Useful Repo Signals

Frontend UI: http://localhost:4200
Valuation service: http://localhost:8081
Valuation agent: http://localhost:5001
BullBearGPT: http://localhost:5002
Main flow often starts with POST /api-s/valuate
High-value repo files when present: README.md, .env.example, docker-compose.local.yml, shared/llm_models.py, and scripts/

---name: stockvaluation-iodescription: Set up, run, compare, and debug StockValuation.io, a local-first DCF valuation platform, including Docker startup, ticker valuations, LLM provider changes, prompt dumping, and troubleshooting.---# StockValuation.ioUse this skill when the user wants help with StockValuation.io setup, local DCF runs, LLM provider or model experiments, prompt dumps, Docker logs, or valuation API usage.## Workflow1. Identify the goal: setup or startup, run a valuation, compare models, debug a failure, or inspect repo internals.2. If the repo is available, inspect `README.md`, `.env.example`, `docker-compose.local.yml`, and relevant service files before answering.3. For installation, startup, and basic valuation runs, read `{baseDir}/references/setup-and-run.md`.4. For provider or model changes, prompt dumping, or controlled comparisons, read `{baseDir}/references/model-and-provider-experiments.md`.5. For runtime failures, health checks, logs, or recovery steps, read `{baseDir}/references/troubleshooting.md`.6. Prefer exact commands, explicit service names, and reproducible steps.## Operating Rules- Prefer the manual clone plus Docker Compose path by default.- If the user wants the installer, tell them to download or inspect `install.sh` locally before running it instead of recommending `curl | bash`.- Never ask the user to paste real API keys into chat. Tell them to set keys in their local environment or `.env`.- Never print `.env` contents, echo live secrets, or suggest committing local secret files.- Treat prompt dumping as privacy-sensitive. When `DUMP_PROMPTS=true`, prompt contents are written to `PROMPT_DUMP_DIR` on disk.- Treat container teardown and volume deletion as destructive. Only suggest `down -v` when the user explicitly asks to reset local state.- When only LLM settings change, restart `valuation-agent` and `bullbeargpt` unless the user also changed other infrastructure.- When comparing experiments, keep the ticker, env changes, and output differences explicit so the comparison stays attributable.## Useful Repo Signals- Frontend UI: `http://localhost:4200`- Valuation service: `http://localhost:8081`- Valuation agent: `http://localhost:5001`- BullBearGPT: `http://localhost:5002`- Main flow often starts with `POST /api-s/valuate`- High-value repo files when present: `README.md`, `.env.example`, `docker-compose.local.yml`, `shared/llm_models.py`, and `scripts/`

Frequently asked questions

Stockvaluation Io