初始化项目版本

.agents/skills/claude-api/shared/token-counting.md

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+# Token Counting
+
+Use the `count_tokens` endpoint (`POST /v1/messages/count_tokens`) for accurate
+token counts against Claude models. Token counts are **model-specific** — pass
+the same model ID you'll use for inference.
+
+**Do not use `tiktoken`.** It's OpenAI's tokenizer. It undercounts Claude
+tokens by ~15–20% on typical text, and by much more on code or non-English
+input. Any estimate from `tiktoken`, `gpt-tokenizer`, or similar is wrong for
+Claude.
+
+## Count a file or string
+
+```python
+from anthropic import Anthropic
+
+client = Anthropic()
+resp = client.messages.count_tokens(
+    model="claude-opus-5",
+    messages=[{"role": "user", "content": open("CLAUDE.md").read()}],
+)
+print(resp.input_tokens)
+```
+
+TypeScript: `await client.messages.countTokens({model, messages})` →
+`.input_tokens`. See `{lang}/claude-api/README.md` for other SDKs.
+
+## CLI
+
+```sh
+ant messages count-tokens --model claude-opus-5 \
+  --message '{role: user, content: "@./CLAUDE.md"}' \
+  --transform input_tokens -r
+```
+
+## Diffing a file across two versions
+
+The endpoint is stateless — count each version separately and subtract:
+
+```python
+from anthropic import Anthropic
+import subprocess
+
+client = Anthropic()
+def count(text: str) -> int:
+    return client.messages.count_tokens(
+        model="claude-opus-5",
+        messages=[{"role": "user", "content": text}],
+    ).input_tokens
+
+before = subprocess.check_output(["git", "show", "HEAD:CLAUDE.md"], text=True)
+after = open("CLAUDE.md").read()
+print(count(after) - count(before))
+```
+
+Full docs: see the Token Counting entry in `shared/live-sources.md`.