Atlas / Skills / ruvnet / Market Ingest

Market IngestCAUTION

skills/ruvnet/market-ingest

🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, federation, vector RAG integration, and native Claude Code / Codex / Hermes and many more Integrated

Verdict
CAUTION
Grade
B
Trust score
89 /100
Version
—
Hosts
—
License
MIT
Stars
73,288
01

Overview

🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, federation, vector RAG integration, and native Claude Code / Codex / Hermes and many more Integrated

Read from source at commit ef7d4f0535e5OBSERVED · 2026-09-26
02

What it tells the agent

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: market-ingest
description: Ingest and normalize market data into OHLCV vectors with HNSW indexing
argument-hint: "<symbol> [--source api]"
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
---

# 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"
```
03

Trust audit

CAUTIONgrade B · trust 89/100 Install with care. The audit found things worth knowing before you trust its output.

LayerWhat it checksResult
L0Provenance & inventoryWARN
L1Static analysis of the codeNA
L2Instruction surface (what it tells the agent)PASS
L3Class-specific surfacePASS
L4Behavioural (sandbox)SKIPPED

What the source does

Filesystem
none-observed
Network
none-observed
Shell
none-observed
Dependencies
pinned
Secrets in source
none-found

Findings (4)

MEDIUMInventory / provenance · inv.symlink · CWE-1104
crates
crates
Why it matters. link not followed
MEDIUMInventory / provenance · inv.symlink · CWE-1104
plugin/agents
plugin/agents
Why it matters. link not followed
MEDIUMInventory / provenance · inv.symlink · CWE-1104
plugin/commands
plugin/commands
Why it matters. link not followed
MEDIUMInventory / provenance · inv.symlink · CWE-1104
plugin/skills
plugin/skills
Why it matters. link not followed

Gates applied: no_behavioural_pass.

Audited 2026-09-26 · audit v0.4.1 · source sha ef7d4f0535e5full audit observations/trust-audit/skill/ruvnet__market-ingest.json · Report an issue / request a re-scan
04

Audit history

Every audit this skill has had.

DateSourceVerdictGradeScoreChange
2026-09-26ef7d4f0535e5CAUTIONB89first audit
05

Questions

What does the Market Ingest skill do?

🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, federation, vector RAG integration, and native Claude Code / Codex / Hermes and many more Integrated

Is Market Ingest safe to install?

With care. The audit graded it B (89/100) and found 4 things worth knowing before you trust this skill, listed below with the exact line each was found on.

What can Market Ingest access on my machine?

The audit observed no filesystem, network or shell use at all in its source.

How current is this page?

The grade is for one exact copy of the source (ef7d4f0535e5), read on 2026-09-26. The repository is watched, and a new audit runs when it changes — this is the first audit.

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