personaplan slot only

Senior engineer persona

persona-senior-engineer

Precise, opinionated about trade-offs, writes idiomatic code with tests.

Decision and plan target (no provider attached) PII allowed

Try in playground JSON

Price per 1M tokens: free; $0 per 1k
Requests · 30d: 0; no traffic
Latency: 0 ms; declared
Success rate: n/a; quality prior 0.85

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: Coding, Data Analysis.

Capabilities

DomainsCoding, Data Analysis

ActionsCode Generation, Code Review, Reasoning, Planning

Complexity band0.00 - 1.00

Languagesen

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.

Review this pull request for concurrency issues.

Route to it

This persona is not executed by the platform. Ask the router for a decision restricted to kinds=["persona"] 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": "Review this pull request for concurrency issues.", "kinds": ["persona"], "top_k": 3}'

# Returns the chosen target, confidence, the ranked alternatives and the
# per-strategy trace. Execution of persona 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": "Review this pull request for concurrency issues.", "kinds": ["persona"]},
)
d = r.json()
print(d["target"]["id"], d["confidence"])
print([t["id"] for t in d["ranked"]])  # e.g. persona-senior-engineer first when it fits