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Update claude-api skill: auth, cloud providers, Managed Agents fixes, token counting (#1276)

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* Sync claude-api skill with latest upstream updates

- Add token-counting.md and SKILL.md trigger description update
- Add auth guidance: env credential resolution, ant auth login, OAuth/WIF doc links, 401 causes
- Add mid-conversation system messages (beta) to prompt-caching, agent-design, SKILL.md, Python/TS READMEs
- Add cache pre-warming (max_tokens: 0) section to prompt-caching
- Add Managed Agents pre-flight viability check to onboarding and overview
- Add Bedrock model-ID section to model-migration; add Bedrock row to live-sources
- Add /claude-api migrate subcommand row and migrate-entry callout
- Fix MA networking config: limited type with allow_package_managers/allow_mcp_servers
- Bump MA create-operations rate limit to 300 RPM
- Fix MA SDK drift: sessions.events.stream(), event.name, typed event arrays
- Add SDK coverage: stop_details, error .type, C# tool runner + MA support, Go model constants, Java 2.34.0, client config, response helpers, auto-pagination, advisor tool
- Move Sonnet 4 / Opus 4 to deprecated in models.md

* Add Anthropic CLI and Claude Platform on AWS docs to claude-api skill

- Add shared/anthropic-cli.md: install, auth profiles, OAuth scopes, command
  structure, version-controlled Managed Agents resources, credential traps
- Add shared/claude-platform-on-aws.md: AnthropicAWS clients, SigV4 auth,
  workspace_id, regions, feature availability
- Restore cross-references to both files throughout SKILL.md and the
  managed-agents docs (previously rewritten to live-sources.md pointers)
- Restore Claude Platform on AWS provider taxonomy in SKILL.md, the
  migration-guide section, and live-sources rows
This commit is contained in:
Lance Martin
2026-06-07 13:21:33 -07:00
committed by GitHub
parent da20c92503
commit c30d329f58
30 changed files with 960 additions and 83 deletions
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skills/claude-api/SKILL.md
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@@ -1,6 +1,9 @@
---
name: claude-api
description: "Build, debug, and optimize Claude API / Anthropic SDK apps. Apps built with this skill should include prompt caching. Also handles migrating existing Claude API code between Claude model versions (4.5 → 4.6, 4.6 → 4.7, retired-model replacements). TRIGGER when: code imports `anthropic`/`@anthropic-ai/sdk`; user asks for the Claude API, Anthropic SDK, or Managed Agents; user adds/modifies/tunes a Claude feature (caching, thinking, compaction, tool use, batch, files, citations, memory) or model (Opus/Sonnet/Haiku) in a file; questions about prompt caching / cache hit rate in an Anthropic SDK project. SKIP: file imports `openai`/other-provider SDK, filename like `*-openai.py`/`*-generic.py`, provider-neutral code, general programming/ML."
description: |-
Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration.
TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG/LLM-judge/computer-use; generate/summarize/extract/classify/rewrite/converse over NL; debugging refusals/cutoffs/streaming/tool-calls/tokens).
SKIP only when another provider is being worked on (overrides all triggers): OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST if no provider named — don't Read the file).
license: Complete terms in LICENSE.txt
---
@@ -35,6 +38,9 @@ For the Claude model version, please use Claude Opus 4.8, which you can access v
If the User Request at the bottom of this prompt is a bare subcommand string (no prose), search every **Subcommands** table in this document — including any in sections appended below — and follow the matching Action column directly. This lets users invoke specific flows via `/claude-api <subcommand>`. If no table in the document matches, treat the request as normal prose.
| Subcommand | Action |
|---|---|
| `migrate` | Migrate existing Claude API code to a newer model. **Read `shared/model-migration.md` immediately** and follow it in order: Step 0 (confirm scope — ask which files/directories before any edit), Step 1 (classify each file), then the per-target breaking-changes section. Do not summarize the guide — execute it. If the user did not name a target model, ask which model to migrate to in the same turn as the scope question. |
---
@@ -81,11 +87,11 @@ Before reading code examples, determine which language the user is working in:
| Java | Yes (beta) | Yes (beta) | Beta tool use with annotated classes |
| Go | Yes (beta) | Yes (beta) | `BetaToolRunner` in `toolrunner` pkg |
| Ruby | Yes (beta) | Yes (beta) | `BaseTool` + `tool_runner` in beta |
| C# | No | No | Official SDK |
| C# | Yes (beta) | Yes (beta) | `BetaToolRunner` + raw JSON schema |
| PHP | Yes (beta) | Yes (beta) | `BetaRunnableTool` + `toolRunner()` |
| cURL | N/A | Yes (beta) | Raw HTTP, no SDK features |
> **Managed Agents code examples**: dedicated language-specific READMEs are provided for Python, TypeScript, Go, Ruby, PHP, Java, and cURL (`{lang}/managed-agents/README.md`, `curl/managed-agents.md`). Read your language's README plus the language-agnostic `shared/managed-agents-*.md` concept files. **Agents are persistent — create once, reference by ID.** Store the agent ID returned by `agents.create` and pass it to every subsequent `sessions.create`; do not call `agents.create` in the request path. The Anthropic CLI is one convenient way to create agents and environments from version-controlled YAML — its URL is in `shared/live-sources.md`. If a binding you need isn't shown in the README, WebFetch the relevant entry from `shared/live-sources.md` rather than guess. C# does not currently have Managed Agents support; use cURL-style raw HTTP requests against the API.
> **Managed Agents code examples**: dedicated language-specific READMEs are provided for Python, TypeScript, Go, Ruby, PHP, Java, and cURL (`{lang}/managed-agents/README.md`, `curl/managed-agents.md`). Read your language's README plus the language-agnostic `shared/managed-agents-*.md` concept files. **Agents are persistent — create once, reference by ID.** Store the agent ID returned by `agents.create` and pass it to every subsequent `sessions.create`; do not call `agents.create` in the request path. The Anthropic CLI (`ant`) is one convenient way to create agents and environments from version-controlled YAML — see `shared/anthropic-cli.md`. If a binding you need isn't shown in the README, WebFetch the relevant entry from `shared/live-sources.md` rather than guess. C# has beta Managed Agents support via `client.Beta.Agents` and related namespaces.
---
@@ -105,16 +111,16 @@ Before reading code examples, determine which language the user is working in:
> **Note:** Managed Agents is the right choice when you want Anthropic to run the agent loop *and* host the container where tools execute — file ops, bash, code execution all run in the per-session workspace. If you want to host the compute yourself or run your own custom tool runtime, Claude API + tool use is the right choice — use the tool runner for automatic loop handling, or the manual loop for fine-grained control (approval gates, custom logging, conditional execution).
> **Third-party providers (Amazon Bedrock, Google Vertex AI, Microsoft Foundry):** Managed Agents is **not available** on Bedrock, Vertex, or Foundry. If you are deploying through any third-party provider, use **Claude API + tool use** for all use cases — including ones where Managed Agents would otherwise be the recommended surface.
> **Cloud-provider access.** **Claude Platform on AWS** is Anthropic-operated with same-day API parity — Managed Agents and every feature in this skill work there, **except self-hosted sandboxes** (see `shared/claude-platform-on-aws.md`). **Amazon Bedrock**, **Google Vertex AI**, and **Microsoft Foundry** do **not** support Managed Agents or Anthropic server-side tools; use **Claude API + tool use** on those.
### Decision Tree
```
What does your application need?
0. Are you deploying through Amazon Bedrock, Google Vertex AI, or Microsoft Foundry?
└── Yes → Claude API (+ tool use for agents) — Managed Agents is 1P only.
No → continue.
0. Which provider?
├── First-party API or Claude Platform on AWS → continue (full surface available).
└── Amazon Bedrock, Google Vertex AI, or Microsoft Foundry → Claude API (+ tool use for agents); Managed Agents not available there.
1. Single LLM call (classification, summarization, extraction, Q&A)
└── Claude API — one request, one response
@@ -157,7 +163,7 @@ Everything goes through `POST /v1/messages`. Tools and output constraints are fe
**Structured outputs** — Constrains the Messages API response format (`output_config.format`) and/or tool parameter validation (`strict: true`). The recommended approach is `client.messages.parse()` which validates responses against your schema automatically. Note: the old `output_format` parameter is deprecated; use `output_config: {format: {...}}` on `messages.create()`.
**Supporting endpoints** — Batches (`POST /v1/messages/batches`), Files (`POST /v1/files`), Token Counting, and Models (`GET /v1/models`, `GET /v1/models/{id}` — live capability/context-window discovery) feed into or support Messages API requests.
**Supporting endpoints** — Batches (`POST /v1/messages/batches`), Files (`POST /v1/files`), Token Counting (`POST /v1/messages/count_tokens` — see `shared/token-counting.md`), and Models (`GET /v1/models`, `GET /v1/models/{id}` — live capability/context-window discovery) feed into or support Messages API requests.
---
@@ -173,7 +179,7 @@ Everything goes through `POST /v1/messages`. Tools and output constraints are fe
**ALWAYS use `claude-opus-4-8` unless the user explicitly names a different model.** This is non-negotiable. Do not use `claude-sonnet-4-6`, `claude-sonnet-4-5`, or any other model unless the user literally says "use sonnet" or "use haiku". Never downgrade for cost — that's the user's decision, not yours.
**CRITICAL: Use only the exact model ID strings from the table above — they are complete as-is. Do not append date suffixes.** For example, use `claude-sonnet-4-5`, never `claude-sonnet-4-5-20250514` or any other date-suffixed variant you might recall from training data. If the user requests an older model not in the table (e.g., "opus 4.5", "sonnet 3.7"), read `shared/models.md` for the exact ID — do not construct one yourself.
**CRITICAL: Use only the exact model ID strings from the table above — they are complete as-is. Do not append date suffixes.** For example, use `claude-sonnet-4-6`, never `claude-sonnet-4-6-20251114` or any other date-suffixed variant you might recall from training data. If the user requests an older model not in the table (e.g., "opus 4.5", "sonnet 3.7"), read `shared/models.md` for the exact ID — do not construct one yourself.
A note: if any of the model strings above look unfamiliar to you, that's to be expected — that just means they were released after your training data cutoff. Rest assured they are real models; we wouldn't mess with you like that.
@@ -211,6 +217,8 @@ See `{lang}/claude-api/README.md` (Compaction section) for code examples. Full d
**Prefix match.** Any byte change anywhere in the prefix invalidates everything after it. Render order is `tools` → `system` → `messages`. Keep stable content first (frozen system prompt, deterministic tool list), put volatile content (timestamps, per-request IDs, varying questions) after the last `cache_control` breakpoint.
**Mid-conversation operator instructions** (beta header `mid-conversation-system-2026-04-07`, on supporting models): append `{"role": "system", ...}` to `messages[]` instead of editing top-level `system`. Preserves the cached history prefix and is the prompt-injection-safe operator channel. See `shared/prompt-caching.md` § Mid-conversation system messages.
**Top-level auto-caching** (`cache_control: {type: "ephemeral"}` on `messages.create()`) is the simplest option when you don't need fine-grained placement. Max 4 breakpoints per request. Minimum cacheable prefix is ~1024 tokens — shorter prefixes silently won't cache.
**Verify with `usage.cache_read_input_tokens`** — if it's zero across repeated requests, a silent invalidator is at work (`datetime.now()` in system prompt, unsorted JSON, varying tool set).
@@ -223,7 +231,7 @@ For placement patterns, architectural guidance, and the silent-invalidator audit
**Managed Agents** is a third surface: server-managed stateful agents with Anthropic-hosted tool execution. You create a persisted, versioned Agent config (`POST /v1/agents`), then start Sessions that reference it. Each session provisions a container as the agent's workspace — bash, file ops, and code execution run there; the agent loop itself runs on Anthropic's orchestration layer and acts on the container via tools. The session streams events; you send messages and tool results back.
**Managed Agents is first-party only.** It is not available on Amazon Bedrock, Google Vertex AI, or Microsoft Foundry. For agents on third-party providers, use Claude API + tool use.
**Managed Agents is available on the first-party API and Claude Platform on AWS.** It is **not** available on Amazon Bedrock, Google Vertex AI, or Microsoft Foundry — for agents there, use Claude API + tool use.
**Mandatory flow:** Agent (once) → Session (every run). `model`/`system`/`tools` live on the agent, never the session. See `shared/managed-agents-overview.md` for the full reading guide, beta headers, and pitfalls.
@@ -233,9 +241,9 @@ For placement patterns, architectural guidance, and the silent-invalidator audit
| Subcommand | Action |
|---|---|
| `managed-agents-onboard` | Walk the user through setting up a Managed Agent from scratch. **Read `shared/managed-agents-onboarding.md` immediately** and follow its interview script: mental model → know-or-explore branch → template config → session setup → emit code. Do not summarize — run the interview. |
| `managed-agents-onboard` | Walk the user through setting up a Managed Agent from scratch. **Read `shared/managed-agents-onboarding.md` immediately** and follow its interview script: mental model → know-or-explore branch → template config → session setup → **pre-flight viability check** → emit code. The viability check (reconcile the stated job against configured tools/credentials/data) catches under-resourced setups — missing a tool, credential, or data access — before the agent burns budget. Do not summarize — run the interview. |
**Reading guide:** Start with `shared/managed-agents-overview.md`, then the topical `shared/managed-agents-*.md` files (core, environments, tools, events, outcomes, multiagent, webhooks, memory, client-patterns, onboarding, api-reference). For Python, TypeScript, Go, Ruby, PHP, and Java, read `{lang}/managed-agents/README.md` for code examples. For cURL, read `curl/managed-agents.md`. **Agents are persistent — create once, reference by ID.** Store the agent ID returned by `agents.create` and pass it to every subsequent `sessions.create`; do not call `agents.create` in the request path. The Anthropic CLI is one convenient way to create agents and environments from version-controlled YAML (URL in `shared/live-sources.md`). If a binding you need isn't shown in the language README, WebFetch the relevant entry from `shared/live-sources.md` rather than guess. C# does not currently have Managed Agents support; use raw HTTP from `curl/managed-agents.md` as a reference.
**Reading guide:** Start with `shared/managed-agents-overview.md`, then the topical `shared/managed-agents-*.md` files (core, environments, tools, events, outcomes, multiagent, webhooks, memory, client-patterns, onboarding, api-reference). For Python, TypeScript, Go, Ruby, PHP, and Java, read `{lang}/managed-agents/README.md` for code examples. For cURL, read `curl/managed-agents.md`. **Agents are persistent — create once, reference by ID.** Store the agent ID returned by `agents.create` and pass it to every subsequent `sessions.create`; do not call `agents.create` in the request path. The Anthropic CLI (`ant`) is one convenient way to create agents and environments from version-controlled YAML — see `shared/anthropic-cli.md`. If a binding you need isn't shown in the language README, WebFetch the relevant entry from `shared/live-sources.md` rather than guess. C# has beta Managed Agents support via `client.Beta.Agents` and related namespaces.
**When the user wants to set up a Managed Agent from scratch** (e.g. "how do I get started", "walk me through creating one", "set up a new agent"): read `shared/managed-agents-onboarding.md` and run its interview — same flow as the `managed-agents-onboard` subcommand.
@@ -261,6 +269,8 @@ After detecting the language, read the relevant files based on what the user nee
→ Read `shared/model-migration.md`
**Prompt caching / optimize caching / "why is my cache hit rate low":**
→ Read `shared/prompt-caching.md` + `{lang}/claude-api/README.md` (Prompt Caching section)
**Count tokens in a file / prompt / diff ("how many tokens is X"):**
→ Read `shared/token-counting.md` — use `messages.count_tokens`, never `tiktoken`
**Function calling / tool use / agents:**
→ Read `{lang}/claude-api/README.md` + `shared/tool-use-concepts.md` + `{lang}/claude-api/tool-use.md`
@@ -275,7 +285,7 @@ After detecting the language, read the relevant files based on what the user nee
→ Read `{lang}/claude-api/README.md` + `{lang}/claude-api/files-api.md`
**Managed Agents (server-managed stateful agents with workspace):**
→ Read `shared/managed-agents-overview.md` + the rest of the `shared/managed-agents-*.md` files. For Python, TypeScript, Go, Ruby, PHP, and Java, read `{lang}/managed-agents/README.md` for code examples. For cURL, read `curl/managed-agents.md`. **Agents are persistent — create once, reference by ID.** Store the agent ID returned by `agents.create` and pass it to every subsequent `sessions.create`; do not call `agents.create` in the request path. The Anthropic CLI is one convenient way to create agents and environments from version-controlled YAML (URL in `shared/live-sources.md`). If a binding you need isn't shown in the language README, WebFetch the relevant entry from `shared/live-sources.md` rather than guess. C# does not currently support Managed Agents — use raw HTTP from `curl/managed-agents.md` as a reference.
→ Read `shared/managed-agents-overview.md` + the rest of the `shared/managed-agents-*.md` files. For Python, TypeScript, Go, Ruby, PHP, and Java, read `{lang}/managed-agents/README.md` for code examples. For cURL, read `curl/managed-agents.md`. **Agents are persistent — create once, reference by ID.** Store the agent ID returned by `agents.create` and pass it to every subsequent `sessions.create`; do not call `agents.create` in the request path. The Anthropic CLI (`ant`) is one convenient way to create agents and environments from version-controlled YAML — see `shared/anthropic-cli.md`. If a binding you need isn't shown in the language README, WebFetch the relevant entry from `shared/live-sources.md` rather than guess. C# has beta Managed Agents support — see `csharp/claude-api.md` for details, or `curl/managed-agents.md` for raw HTTP reference.
### Claude API (Full File Reference)
@@ -316,7 +326,7 @@ Live documentation URLs are in `shared/live-sources.md`.
- **Opus 4.6 / Sonnet 4.6 thinking:** Use `thinking: {type: "adaptive"}` — do NOT use `budget_tokens` for new 4.6 code (deprecated on both Opus 4.6 and Sonnet 4.6; for gradual migration of existing code, see the transitional escape hatch in `shared/model-migration.md` — note this carve-out does not apply to Opus 4.7 or 4.8). For older models, `budget_tokens` must be less than `max_tokens` (minimum 1024). This will throw an error if you get it wrong.
- **4.6/4.7/4.8 family prefill removed:** Assistant message prefills (last-assistant-turn prefills) return a 400 error on Opus 4.6, Opus 4.7, Opus 4.8, and Sonnet 4.6. Use structured outputs (`output_config.format`) or system prompt instructions to control response format instead.
- **Confirm migration scope before editing:** When a user asks to migrate code to a newer Claude model without naming a specific file, directory, or file list, **ask which scope to apply first** — the entire working directory, a specific subdirectory, or a specific set of files. Do not start editing until the user confirms. Imperative phrasings like "migrate my codebase", "move my project to X", "upgrade to Sonnet 4.6", or bare "migrate to Opus 4.8" are **still ambiguous** — they tell you what to do but not where, so ask. Proceed without asking only when the prompt names an exact file, a specific directory, or an explicit file list ("migrate `app.py`", "migrate everything under `services/`", "update `a.py` and `b.py`"). See `shared/model-migration.md` Step 0.
- **`max_tokens` defaults:** Don't lowball `max_tokens` — hitting the cap truncates output mid-thought and requires a retry. For non-streaming requests, default to `~16000` (keeps responses under SDK HTTP timeouts). For streaming requests, default to `~64000` (timeouts aren't a concern, so give the model room). Only go lower when you have a hard reason: classification (`~256`), cost caps, or deliberately short outputs.
- **`max_tokens` defaults:** Don't lowball `max_tokens` — hitting the cap truncates output mid-thought and requires a retry. For non-streaming requests, default to `~16000` (keeps responses under SDK HTTP timeouts). For streaming requests, default to `~64000` (timeouts aren't a concern, so give the model room). Only go lower when you have a hard reason: classification (`~256`), cost caps, deliberately short outputs, or **`max_tokens: 0`** for cache pre-warming (see `shared/prompt-caching.md` → Pre-warming).
- **128K output tokens:** Opus 4.6, Opus 4.7, and Opus 4.8 support up to 128K `max_tokens`, but the SDKs require streaming for values that large to avoid HTTP timeouts. Use `.stream()` with `.get_final_message()` / `.finalMessage()`.
- **Tool call JSON parsing (4.6/4.7/4.8 family):** Opus 4.6, Opus 4.7, Opus 4.8, and Sonnet 4.6 may produce different JSON string escaping in tool call `input` fields (e.g., Unicode or forward-slash escaping). Always parse tool inputs with `json.loads()` / `JSON.parse()` — never do raw string matching on the serialized input.
- **Structured outputs (all models):** Use `output_config: {format: {...}}` instead of the deprecated `output_format` parameter on `messages.create()`. This is a general API change, not 4.6-specific.