How long does the integration take?

Change one base URL in an OpenAI-compatible client, or install the Python or TypeScript SDK; the quickstart routes a first request in a few minutes.

Will this lock us into another vendor?

No. The router is Apache-2.0 open source, your provider keys stay yours, and the API is OpenAI-compatible, so leaving is a change of base URL.

What happens when a provider fails?

The router falls back to the next model your policy allows and records the fallback in the trace, so an outage costs a retry, not an incident.

90 days of the enterprise, pro and team plans free, no card needed. See the plans

OpenSmartRoute

crypto-ta-analyzer - Skill - OpenSmartRoute

Skillv1.0.0

crypto-ta-analyzer

Name: crypto-ta-analyzer
Author: dkyazzentwatwa

Run multi-indicator technical analysis on crypto or market OHLCV data. Use for deterministic trend, momentum, volume, and divergence analysis.

by dkyazzentwatwa(0) 0 installs

Free

Free account. Installing gives you the manifest plus copy-paste snippets.

See reviews

About

Imported from dkyazzentwatwa/chatgpt-skills (crypto-ta-analyzer/SKILL.md) via skills.sh. Install upstream with npx skills add dkyazzentwatwa/chatgpt-skills --skill crypto-ta-analyzer. Copyright stays with the author.

Crypto TA Analyzer

Use the bundled indicators when the user needs explicit technical analysis rather than a narrative market opinion.

Workflow

Get normalized OHLCV data first.
Use scripts/data_converter.py or scripts/coingecko_converter.py when source formats need reshaping.
Run scripts/ta_analyzer.py for the actual indicator stack and signal scoring.
Explain indicator agreement, conflicts, and regime sensitivity instead of presenting one number without context.

Guardrails

Do not present signals as guaranteed outcomes.
Keep the distinction clear between deterministic indicator output and discretionary interpretation.

Use it

Copy one of these into your project. Installing also returns the manifest and these snippets.

# after Install: the listing is in your workspace's routing pool - a plan picks it for its slot
curl -s -X POST https://osr-api.kindrock-caaab1a2.centralindia.azurecontainerapps.io/api/v1/route -H 'Authorization: Bearer $OSR_API_KEY' -H 'Content-Type: application/json' -d '{"text": "...", "plan": true}'

Installed into a catalogue, chosen by a router

Install crypto-ta-analyzer and it becomes one more candidate the router can pick - when it fits.

A listing is a routing target with a manifest: what it does, which domains it covers, what it costs and who publishes it. Once installed it sits beside your own models and tools, is scored like any other candidate for each request, and shows up in the trace when it wins. Ratings come from workspaces that installed it, one per account.

Photo: RDNE Stock project

For the business

What it costs to adopt - in engineering time.

Same client, same code
One base URL
The OpenAI-compatible endpoint answers your existing SDK calls; model=auto lets the router choose.
The SDKs
One URL, every vendor
No vendor lock-in
Point your OpenAI-compatible client at one address; add, swap or retire providers in the catalogue without touching application code.
Every vendor side by side
Next eligible model answers
Failover built in
When a provider is down or over quota the request moves on; the trace says it did.

Manifest

An Open Capability Manifest: the router reads it to know what this does, what it costs and when to pick it.

dkyazzentwatwa-chatgpt-skills-crypto-ta-analyzer.ocm.jsonjson

{
  "ocm": "1",
  "id": "dkyazzentwatwa-chatgpt-skills-crypto-ta-analyzer",
  "kind": "skill",
  "name": "crypto-ta-analyzer",
  "description": "Run multi-indicator technical analysis on crypto or market OHLCV data. Use for deterministic trend, momentum, volume, and divergence analysis.",
  "publisher": "dkyazzentwatwa",
  "version": "1.0.0",
  "capabilities": {
    "domains": [
      "data_analysis"
    ],
    "tags": [
      "skill-md",
      "skills-sh"
    ],
    "languages": [
      "en"
    ]
  },
  "quality_prior": 0.6,
  "examples": [
    "Run multi-indicator technical analysis on crypto or market OHLCV data. Use for deterministic trend, momentum, volume, and divergence analysis."
  ],
  "primary": false,
  "metadata": {
    "source": {
      "provider": "skills.sh",
      "repository": "https://github.com/dkyazzentwatwa/chatgpt-skills",
      "path": "crypto-ta-analyzer/SKILL.md",
      "ref": "HEAD",
      "url": "https://www.skills.sh/dkyazzentwatwa/chatgpt-skills/crypto-ta-analyzer",
      "key": "dkyazzentwatwa/chatgpt-skills/crypto-ta-analyzer/SKILL.md"
    }
  },
  "instructions": "# Crypto TA Analyzer\n\nUse the bundled indicators when the user needs explicit technical analysis rather than a narrative market opinion.\n\n## Workflow\n\n1. Get normalized OHLCV data first.\n2. Use `scripts/data_converter.py` or `scripts/coingecko_converter.py` when source formats need reshaping.\n3. Run `scripts/ta_analyzer.py` for the actual indicator stack and signal scoring.\n4. Explain indicator agreement, conflicts, and regime sensitivity instead of presenting one number without context.\n\n## Guardrails\n\n- Do not present signals as guaranteed outcomes.\n- Keep the distinction clear between deter",
  "cost": {
    "context_tokens": 164
  }
}

Fetch it by URL: GET /api/v1/registry/dkyazzentwatwa-chatgpt-skills-crypto-ta-analyzer/manifest?version=1.0.0

About

Crypto TA Analyzer

Workflow

Guardrails

Use it

Install crypto-ta-analyzer and it becomes one more candidate the router can pick - when it fits.

What it costs to adopt - in engineering time.

One base URL

No vendor lock-in

Failover built in

Manifest

Reviews