skill

Summarization skill

skill-summarize

Map-reduce summarizer for long documents.

Decision and plan target (no provider attached) PII allowed

Try in playground JSON

Price per 1M tokens: $0.80; $0.0008 per 1k
Requests · 30d: 0; no traffic
Latency: 1200 ms; declared
Success rate: n/a; quality prior 0.82

Traffic over 30 days

Requests per day this target answered on this deployment, with the cost line.

No requests yet. Route something from the playground to see usage here.

Tokens: 0
Spend: $0
Previous window: 0 req

Routed for

Domains the signal layer detected on requests that ended here.

No routed requests yet. Declared domains: General, Legal, Finance.

Capabilities

DomainsGeneral, Legal, Finance

ActionsSummarize

Complexity band0.00 - 1.00

Languages*

Context windowundeclared

Streamingyes

Policy constraints

Hard stops enforced before scoring.

Data boundaryPublic

Regionsanywhere

PIIallowed

Max input tokensunlimited

Tenantsall

Representative prompts

Examples the similarity strategy matches against.

Summarize this 40-page contract into key obligations.
TL;DR of the attached quarterly report.

Route to it

This skill is not executed by the platform. Ask the router for a decision restricted to kinds=["skill"] and dispatch the winner in your own stack; send feedback afterwards so the learners improve.

curlbash

curl https://api.opensmartroute.ai/api/v1/route \
  -H "Authorization: Bearer $OSR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"text": "Summarize this 40-page contract into key obligations.", "kinds": ["skill"], "top_k": 3}'

# Returns the chosen target, confidence, the ranked alternatives and the
# per-strategy trace. Execution of skill targets happens in your stack.

httpxpython

import httpx

r = httpx.post(
    "https://api.opensmartroute.ai/api/v1/route",
    headers={"Authorization": "Bearer osr_live_..."},
    json={"text": "Summarize this 40-page contract into key obligations.", "kinds": ["skill"]},
)
d = r.json()
print(d["target"]["id"], d["confidence"])
print([t["id"] for t in d["ranked"]])  # e.g. skill-summarize first when it fits