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Agent skill

Market Ingest

by ruvnet in ruvnet/ruflo

Ingest and normalize market data into OHLCV vectors with HNSW indexing

MITAuto-check: notesDatabases

Install Market Ingest

skills CLI
$ npx skills add ruvnet/ruflo --skill market-ingest -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install ruvnet/ruflo market-ingest --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/ruvnet/ruflo.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/ruflo-market-data/skills/market-ingest .claude/skills/market-ingest && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
market-ingest
GitHub stars
74k
Token cost
~529 tokens
SKILL.md length
203 words
Files
1
Skills in repo
265
Repo updated
First seen
Licence
MIT

At a glance

Ingest and normalize market data into OHLCV vectors with HNSW indexing

  • Works in 6 steps: Fetch data -- retrieve OHLCV data for… → Normalize -- convert raw prices to… → Vectorize -- encode each candle as a… → …
  • Tasks that involve Stock and market analysis
  • SKILL.md covers When to use, Steps and CLI alternative
  • Calls npx

What it does

Market Ingest is an agent skill from ruvnet/ruflo. Ingest and normalize market data into OHLCV vectors with HNSW indexing

Its SKILL.md is about 530 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Databases, covering Stock and market analysis and Vector databases. It works with Model Context Protocol. The repository describes itself as: 🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory…. The licence is MIT.

When your agent uses it

  • Tasks that involve Stock and market analysis
  • Tasks that involve Vector databases

Example prompts

  • “/market-ingest”

Requirements

  • Node.js
  • Pre-approved tools (allowed-tools): Bash, mcp__plugin_ruflo-core_ruflo__memory_store, mcp__plugin_ruflo-core_ruflo__memory_search, mcp__plugin_ruflo-core_ruflo__ruvllm_hnsw_create, mcp__plugin_ruflo-core_ruflo__ruvllm_hnsw_add, mcp__plugin_ruflo-core_ruflo__embeddings_generate

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Fetch data -- retrieve OHLCV data for the symbol from the configured data source (REST API, CSV file, or manual input)
  2. Normalize -- convert raw prices to relative values
  3. Vectorize -- encode each candle as a 64-dimension padded vector (5 normalized OHLCV values + padding). For semantic embeddings of pattern…
  4. Store -- call mcpplugin_ruflo-core_ruflomemory_store --namespace market-data to persist normalized OHLCV data with symbol+date keys. The…
  5. Index -- call mcpplugin_ruflo-core_rufloruvllm_hnsw_add to add vectors to the HNSW index for nearest-neighbor search.
  6. Report -- summarize: candles ingested, date range, price range, average volume

What it can do on your machine

Read from SKILL.md and the folder at commit 6c04654. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Bash
    • mcp__plugin_ruflo-core_ruflo__memory_store
    • mcp__plugin_ruflo-core_ruflo__memory_search
    • mcp__plugin_ruflo-core_ruflo__ruvllm_hnsw_create
    • mcp__plugin_ruflo-core_ruflo__ruvllm_hnsw_add
    • mcp__plugin_ruflo-core_ruflo__embeddings_generate

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • npx

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use npx, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Market Ingest loads about 529 tokens when it runs. Until then it costs about 21 tokens; SKILL.md has 203 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~21
When it runs · the whole SKILL.md, loaded when a task matches
~529

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Bash, mcp__plugin_ruflo-core_ruflo__memory_store, mcp__plugin_ruflo-core_ruflo__memory_search, mcp__

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from ruvnet/ruflo at commit 6c04654, republished under its MIT licence (© ruvnet). 203 words, ~529 tokens.

Download SKILL.mdSave it as .claude/skills/market-ingest/SKILL.md (or your agent's skills folder).
name
market-ingest
description
Ingest and normalize market data into OHLCV vectors with HNSW indexing
allowed-tools
Bash, mcp__plugin_ruflo-core_ruflo__memory_store, mcp__plugin_ruflo-core_ruflo__memory_search, mcp__plugin_ruflo-core_ruflo__ruvllm_hnsw_create, mcp__plugin_ruflo-core_ruflo__ruvllm_hnsw_add, mcp__plugin_ruflo-core_ruflo__embeddings_generate
argument-hint
<symbol> [--source api]

Market Ingest

Fetch market data for a symbol, normalize to OHLCV vectors, and store with HNSW indexing for fast pattern search.

When to use

When you need to ingest raw market data (price and volume) for a symbol and prepare it for pattern detection and similarity search. This is the first step before running pattern detection or comparison.

Steps

  1. Fetch data -- retrieve OHLCV data for the symbol from the configured data source (REST API, CSV file, or manual input)
  2. Normalize -- convert raw prices to relative values:
    • Open: (open - prev_close) / prev_close
    • High: (high - open) / open
    • Low: (low - open) / open
    • Close: (close - open) / open
    • Volume: Z-score against rolling mean/std
  3. Vectorize -- encode each candle as a 64-dimension padded vector (5 normalized OHLCV values + padding). For semantic embeddings of pattern descriptions, use mcp__plugin_ruflo-core_ruflo__embeddings_generate (NOT embeddings_embed — that tool name does not exist).
  4. Store -- call mcp__plugin_ruflo-core_ruflo__memory_store --namespace market-data to persist normalized OHLCV data with symbol+date keys. The memory_* tool family routes by namespace; the agentdb_hierarchical-* family routes by tier (working|episodic|semantic) and ignores namespace strings, so use memory_* here.
  5. Index -- call mcp__plugin_ruflo-core_ruflo__ruvllm_hnsw_add to add vectors to the HNSW index for nearest-neighbor search.
  6. Report -- summarize: candles ingested, date range, price range, average volume

CLI alternative

bash
npx @claude-flow/cli@latest memory store --namespace market-data --key "symbol-SYMBOL-DATE" --value "OHLCV_JSON"

© ruvnet, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in plugins/ruflo-market-data/skills/market-ingest of ruvnet/ruflo.

Open the folder on GitHubat commit 6c04654

Compare with similar skills

Market Ingest next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Market Ingest compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Market Ingest this skillruvnet/ruflo74k—~529Automated safety check: NotesMIT
Polymarket Tennislivetennisapi/livetennisapi-mcp152—~3kAutomated safety check: PassMIT
Investlongsizhuo/openInvest108—~5.9kAutomated safety check: NotesMIT
Setupdaloopa/investing489—~1kAutomated safety check: NotesApache-2.0
Codebase Explorationgiancarloerra/SocratiCode3.3k1 repos~1.5kAutomated safety check: PassAGPL-3.0
Stock APIzhangxiangliang/stock-api2k—~507Automated safety check: PassMIT

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Works with

Categories

Questions about Market Ingest

What does Market Ingest do?

Ingest and normalize market data into OHLCV vectors with HNSW indexing. Market Ingest is an agent skill from ruvnet/ruflo.

When should I use Market Ingest?

Market Ingest fits situations like: tasks that involve Stock and market analysis; tasks that involve Vector databases.

How do I install Market Ingest in Claude Code?

Run `npx skills add ruvnet/ruflo --skill market-ingest -a claude-code`. Or copy the skill folder (plugins/ruflo-market-data/skills/market-ingest in ruvnet/ruflo) into .claude/skills/market-ingest in your project. Claude Code loads it when a task matches its description.

How do I install Market Ingest in Codex?

Run `npx skills add ruvnet/ruflo --skill market-ingest -a codex`. Or copy the skill folder (plugins/ruflo-market-data/skills/market-ingest in ruvnet/ruflo) into .agents/skills/market-ingest in your project. Codex loads it when a task matches its description.

Can I use Market Ingest in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ruvnet/ruflo --skill market-ingest -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/market-ingest, .gemini/skills/market-ingest, .github/skills/market-ingest and .opencode/skills/market-ingest in your project.

What does Market Ingest need to run?

Going by SKILL.md and its folder, Market Ingest needs the command-line tools its instructions call (npx). Our summary lists: Node.js. Its frontmatter pre-approves these tools: Bash, mcp__plugin_ruflo-core_ruflo__memory_store, mcp__plugin_ruflo-core_ruflo__memory_search, mcp__plugin_ruflo-core_ruflo__ruvllm_hnsw_create, mcp__plugin_ruflo-core_ruflo__ruvllm_hnsw_add, mcp__plugin_ruflo-core_ruflo__embeddings_generate.

Does Market Ingest access the network?

SKILL.md contains no URLs. Its commands use npx, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Market Ingest safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Market Ingest use?

Market Ingest is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Market Ingest use?

About 529 tokens (SKILL.md is roughly 2.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Market Ingest?

Skills that share tags, products or a category with Market Ingest: Polymarket Tennis (livetennisapi/livetennisapi-mcp, 152 stars), Invest (longsizhuo/openInvest, 108 stars), Setup (daloopa/investing, 489 stars) and Codebase Exploration (giancarloerra/SocratiCode, 3.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Market Ingest?

ruvnet (a GitHub user) maintains it in ruvnet/ruflo, which has 74,222 GitHub stars. The repository holds 265 skills in this directory. The repository was last updated on October 10, 2026.

Source: ruvnet/ruflo on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.