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chore: update claude-api skill [auto-sync] (#729)
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@@ -35,7 +35,8 @@ This file documents HTTP error codes returned by the Claude API, their common ca
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"error": {
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"type": "invalid_request_error",
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"message": "messages: roles must alternate between \"user\" and \"assistant\""
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}
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},
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"request_id": "req_011CSHoEeqs5C35K2UUqR7Fy"
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}
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```
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@@ -1,6 +1,57 @@
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# Claude Model Catalog
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**Only use exact model IDs listed in this file.** Never guess or construct model IDs — incorrect IDs will cause API errors. Use aliases wherever available. For the latest information, WebFetch the Models Overview URL in `shared/live-sources.md`.
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**Only use exact model IDs listed in this file.** Never guess or construct model IDs — incorrect IDs will cause API errors. Use aliases wherever available. For the latest information, WebFetch the Models Overview URL in `shared/live-sources.md`, or query the Models API directly (see Programmatic Model Discovery below).
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## Programmatic Model Discovery
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For **live** capability data — context window, max output tokens, feature support (thinking, vision, effort, structured outputs, etc.) — query the Models API instead of relying on the cached tables below. Use this when the user asks "what's the context window for X", "does model X support vision/thinking/effort", "which models support feature Y", or wants to select a model by capability at runtime.
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```python
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m = client.models.retrieve("claude-opus-4-6")
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m.id # "claude-opus-4-6"
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m.display_name # "Claude Opus 4.6"
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m.max_input_tokens # context window (int)
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m.max_tokens # max output tokens (int)
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# capabilities is an untyped nested dict — bracket access, check ["supported"] at the leaf
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caps = m.capabilities
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caps["image_input"]["supported"] # vision
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caps["thinking"]["types"]["adaptive"]["supported"] # adaptive thinking
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caps["effort"]["max"]["supported"] # effort: max (also low/medium/high)
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caps["structured_outputs"]["supported"]
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caps["context_management"]["compact_20260112"]["supported"]
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# filter across all models — iterate the page object directly (auto-paginates); do NOT use .data
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[m for m in client.models.list()
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if m.capabilities["thinking"]["types"]["adaptive"]["supported"]
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and m.max_input_tokens >= 200_000]
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```
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Top-level fields (`id`, `display_name`, `max_input_tokens`, `max_tokens`) are typed attributes. `capabilities` is a dict — use bracket access, not attribute access. The API returns the full capability tree for every model with `supported: true/false` at each leaf, so bracket chains are safe without `.get()` guards. TypeScript SDK: same method names, also auto-paginates on iteration.
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### Raw HTTP
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```bash
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curl https://api.anthropic.com/v1/models/claude-opus-4-6 \
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-H "x-api-key: $ANTHROPIC_API_KEY" \
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-H "anthropic-version: 2023-06-01"
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```
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```json
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{
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"id": "claude-opus-4-6",
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"display_name": "Claude Opus 4.6",
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"max_input_tokens": 1000000,
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"max_tokens": 128000,
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"capabilities": {
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"image_input": {"supported": true},
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"structured_outputs": {"supported": true},
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"thinking": {"supported": true, "types": {"enabled": {"supported": true}, "adaptive": {"supported": true}}},
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"effort": {"supported": true, "low": {"supported": true}, …, "max": {"supported": true}},
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…
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}
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}
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```
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## Current Models (recommended)
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@@ -28,9 +79,9 @@
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## Deprecated Models (retiring soon)
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| Friendly Name | Alias (use this) | Full ID | Status |
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|-------------------|---------------------|-------------------------------|------------|
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| Claude Haiku 3 | — | `claude-3-haiku-20240307` | Deprecated |
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| Friendly Name | Alias (use this) | Full ID | Status | Retires |
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|-------------------|---------------------|-------------------------------|------------|--------------|
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| Claude Haiku 3 | — | `claude-3-haiku-20240307` | Deprecated | Apr 19, 2026 |
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## Retired Models (no longer available)
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@@ -239,7 +239,7 @@ The memory tool enables Claude to store and retrieve information across conversa
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- Client-side tool — you control storage via your implementation
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- Supports commands: `view`, `create`, `str_replace`, `insert`, `delete`, `rename`
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- Operates on files in a `/memories` directory
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- The SDKs provide helper classes/functions for implementing the memory backend
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- The Python, TypeScript, and Java SDKs provide helper classes/functions for implementing the memory backend
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> **Security:** Never store API keys, passwords, tokens, or other secrets in memory files. Be cautious with personally identifiable information (PII) — check data privacy regulations (GDPR, CCPA) before persisting user data. The reference implementations have no built-in access control; in multi-user systems, implement per-user memory directories and authentication in your tool handlers.
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