Hi - I answer from the OpenSmartRoute documentation: routing, the API, plans and quotas, self-hosting. Ask away, or open a support ticket if you need a person.
Grounded in the docs - follow a source before acting on it.
flashcards - Skill - OpenSmartRoute
Skillv1.0.0
flashcards
Turn lesson material into spaced-repetition flashcards in CSV form, ready to import into Anki. Use when the user asks for flashcards, cue cards, or revision cards.
Imported from YangShieh/LALM-skill-lab (skills/example-pack-flashcards/flashcards/SKILL.md). Install upstream with npx skills add YangShieh/LALM-skill-lab --skill flashcards. Copyright stays with the author.
Flashcards
Split the material into atomic facts - one idea per card.
Write each card as a question on the front and the shortest correct answer
on the back. If the back needs a comma, the card is doing too much: split it.
Save to flashcards.csv in the workspace with a front,back header row.
Include a ## Sources note at the bottom of the CSV file listing what the cards came from.
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://api.opensmartroute.ai/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 flashcards 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.
An Open Capability Manifest: the router reads it to know what this does, what it costs and when to pick it.
yangshieh-lalm-skill-lab-flashcards.ocm.jsonjson
{
"ocm": "1",
"id": "yangshieh-lalm-skill-lab-flashcards",
"kind": "skill",
"name": "flashcards",
"description": "Turn lesson material into spaced-repetition flashcards in CSV form, ready to import into Anki. Use when the user asks for flashcards, cue cards, or revision cards.",
"publisher": "YangShieh",
"version": "1.0.0",
"capabilities": {
"domains": [
"coding",
"data_analysis"
],
"tags": [
"skill-md",
"github"
],
"languages": [
"en"
]
},
"quality_prior": 0.6,
"examples": [
"Turn lesson material into spaced-repetition flashcards in CSV form, ready to import into Anki. Use when the user asks for flashcards, cue cards, or revision cards."
],
"primary": false,
"metadata": {
"source": {
"provider": "github",
"repository": "https://github.com/YangShieh/LALM-skill-lab",
"path": "skills/example-pack-flashcards/flashcards/SKILL.md",
"ref": "21ea8160304ce9159d97853bd6e66a32af1557e1",
"url": "https://github.com/YangShieh/LALM-skill-lab/blob/21ea8160304ce9159d97853bd6e66a32af1557e1/skills/example-pack-flashcards/flashcards/SKILL.md",
"key": "YangShieh/LALM-skill-lab/skills/example-pack-flashcards/flashcards/SKILL.md"
}
},
"instructions": "# Flashcards\n\n1. Split the material into atomic facts - one idea per card.\n2. Write each card as a question on the front and the shortest correct answer\n on the back. If the back needs a comma, the card is doing too much: split it.\n3. Save to `flashcards.csv` in the workspace with a `front,back` header row.\n\n4. Include a `## Sources` note at the bottom of the CSV file listing what the cards came from.",
"cost": {
"context_tokens": 101
}
}
Fetch it by URL: GET /api/v1/registry/yangshieh-lalm-skill-lab-flashcards/manifest?version=1.0.0
Reviews
Star ratings from people who tried it. One review per account; edit yours any time.
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