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ProfileClaw keeps your assessments, materials, and long-term context ready for products like OpenClaw, Claude Work, and Nanobot, so AI can work with memory instead of starting cold.

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DocsAgentsAuth

Agent Auth

Keep credentials in the runtime, not in the prompt loop

Authentication for agents should be explicit, scope-aware, and operationally simple. The runtime injects keys, the model calls tools, and failures branch deterministically.

Format: AI-first docs
Source: DocsAgentsAuthPage
Warning

The model should never own secret management

Keys belong in runtime-controlled storage and transport layers, not in user-visible prompts or tool arguments authored by the model.

Auth responsibilities

Split responsibilities so auth stays predictable in production.

Runtime

Owns keys, scope assignment, rotation, and transport injection.

  • Attach `Authorization` or `X-API-Key` before the model sees the request.
  • Rotate credentials without rewriting prompts.
  • Keep staging and production isolated.

Model

Chooses which tool to call, not how to manage the secret.

  • The model should request capability, not raw credentials.
  • Forbidden responses should not trigger speculative retries.
  • Tool output should expose safe failure classifications only.

Operators

Need enough metadata to debug auth failures without seeing secrets.

  • Log request ids and key identity labels.
  • Track which scopes each environment key owns.
  • Separate setup failures from product logic failures.

Inject credentials at the runtime boundary

The clean pattern is simple: the model calls a tool, the tool adapter attaches the credential, and the API never depends on prompt-visible secrets.

  • Prefer Bearer auth as the default header shape.
  • Validate a new key with Context API before building deeper workflows.
  • Keep one secret store per environment boundary.

Use scopes to express capability boundaries

ProfileClaw exposes scope-aware operations, so keys should align with the exact jobs the runtime is allowed to perform.

  • Read-only assistants can stay on narrow read scopes.
  • Prediction, reasoning, and mutation paths should elevate only where needed.
  • Scope failures should branch into configuration work, not model improvisation.

Responsibility Split

Good auth behavior depends on clear ownership across the stack.

LayerOwnsShould not own
Runtime adapterSecrets, header injection, rotation, and retry-safe transport.Conversation wording or speculative reasoning.
ModelTool choice and workflow intent.Raw keys, token refresh, or scope repair logic.
OperationsEnvironment separation, audit trails, and incident recovery.Prompt-level credential handling.

Decision Matrix

Use these branches when an auth-related issue appears.

Situation

The request is unauthorized

Action

Treat it as missing, invalid, or expired credentials in the runtime.

Why

The model cannot repair a secret boundary issue.

Situation

The request is forbidden

Action

Check scopes and runtime capability configuration.

Why

The key exists, but the workflow lacks permission for that operation.

Situation

A new integration is being onboarded

Action

Validate the key against Context API before adding deeper calls.

Why

It confirms the auth path with the smallest viable request.

Header examples

Prefer a runtime-owned Bearer flow, with `X-API-Key` available as an alternative.

Bearer header
1curl "https://profileclaw.cn/api/v1/context" -H "Authorization: Bearer $PROFILECLAW_API_KEY"
Alternative header
1curl "https://profileclaw.cn/api/v1/context" -H "X-API-Key: $PROFILECLAW_API_KEY"

Next surfaces

Once auth is stable, optimize request size and recovery posture.

Open Caching
Open Retries
Open API Authentication