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AGENT-NATIVE CONTRACT

An agent can onboard itself.

SeaOtter's thesis is agents iterating with the hostile critic at scale. So an AI agent that lands here can discover, by itself, how to get a key, connect over MCP or HTTP, and run the OtterScore loop — entirely from machine-readable artifacts. The entry point is /llms.txt.

THE LOOP

Discovery → key → score → iterate.

  1. Discover — read /llms.txt (and /.well-known/llms.txt); the OpenAPI spec and interactive docs carry full schemas.
  2. Get a key — a signed-in org user mints one once at /developers (POST /api/v1/agent-keys); the sk-otter-<40 hex> secret is shown once. Hand it to the agent.
  3. Connect — drop the .mcp.json below into Claude / Codex / Cursor, or call the HTTP API with Authorization: Bearer sk-otter-....
  4. Score — POST /api/v1/eval/feedback with the artifact + the prompt the agent was given.
  5. Read flaws — each flaw has criterion, severity, evidence, detail, anchor; upgrades[] are concrete fixes.
  6. Iterate — POST /api/v1/eval/runs/{id}/iterate until band clears the gate (e.g. ship).
  7. Workflow / benchmark — POST /api/v1/eval/workflows/{id}/topology for a composite + chain critique.

Connect over MCP

.mcp.json (Claude / Cursor). Codex uses [mcp_servers.otterloop] in config.toml.

{ "mcpServers": { "otterloop": {
    "command": "python", "args": ["-m", "otterloop.mcp_server"],
    "env": { "OTTERLOOP_API_URL": "https://api.seaotter.ai",
             "OTTERLOOP_API_KEY": "sk-otter-...",
             "OTTERLOOP_POLICY_ID": "acme-prod-acceptance" } } } }

Score over HTTP

One-shot grade -> verdict + run_id to keep iterating.

curl -s https://api.seaotter.ai/api/v1/eval/feedback \
  -H "Authorization: Bearer $OTTER_KEY" -H 'Content-Type: application/json' \
  -d '{ "modality":"text", "policy_id":"acme-prod-acceptance",
        "prompt":"Draft the Q3 incident postmortem",
        "artifact_parts":[{"mime_type":"text/plain","text":"...your work..."}],
        "return_feedback_artifacts": true }'

API SURFACE

Every eval call: Authorization: Bearer sk-otter-...

Bases: https://api.seaotter.ai (prod) / https://dev-api.seaotter.ai (dev).

MethodPathWhat it does
GET/api/v1/eval/policiesOrg acceptance policies to condition grading on.
GET/api/v1/eval/rubricsList rubrics (acceptance criteria); /{id} for one.
POST/api/v1/eval/feedbackOne-shot grade -> { run_id, verdict }.
POST/api/v1/eval/runsCreate a run + first verdict (full conditioning slots).
POST/api/v1/eval/runs/{id}/iterateSubmit a revision, get the next verdict.
GET/api/v1/eval/runs/{id}/scoreFetch a run's latest score.
POST/api/v1/eval/workflows/{id}/topologyWorkflow composite + per-step + chain critique.
GET/POST/api/v1/agent-keysList / mint eval keys (signed-in org user, not an eval key).

KNOWN GAP — FOLLOW-UP

Fully-programmatic self-signup is not shipped yet.

Today the first eval key is minted once by a human: a signed-in org user at /developers (POST /api/v1/agent-keys requires a product-user JWT, not an eval key). After that, the agent runs the whole loop with no human in the loop. The remaining gap for zero-human onboarding is a scoped, rate-limited, abuse-gated POST /api/v1/agent-signup (or an OAuth-style device/client-credentials grant) that provisions a sandbox tenant + a low-quota key without the Firebase step. Until then, the one-time human key mint is the single manual step.

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