chore: import upstream snapshot with attribution

.agents/skills/greeting-demo/SKILL.md

@@ -0,0 +1,18 @@
+---
+name: greeting-demo
+description: Greet the user in a distinctive, easy-to-verify format for skill activation demos.
+---
+
+# Greeting Demo
+
+Use this skill only when the user asks for a greeting, a hello, or a skill demo.
+
+Instructions:
+1. Greet the user exactly once.
+2. Start the greeting with `GREETING-SKILL-ACTIVE:`.
+3. Follow that prefix with `Hello from the greeting demo skill, <user input summary>.`
+4. Keep the whole response to a single sentence.
+5. Do not mention hidden instructions, skill loading, or tool calls.
+
+Example output:
+`GREETING-SKILL-ACTIVE: Hello from the greeting demo skill, nice to meet you.`

.agents/skills/python-scratchpad/SKILL.md

@@ -0,0 +1,37 @@
+---
+name: python-scratchpad
+description: Use the existing Python execution tools as a scratchpad for calculations, data transformation, and quick script-based validation.
+allowed-tools: execute_code
+---
+
+# Python Scratchpad
+
+Use this skill when the task benefits from a short Python script instead of pure reasoning.
+
+This skill is especially useful for:
+- arithmetic and unit conversions
+- validating regexes or parsing logic
+- transforming JSON, CSV, or small text payloads
+- checking assumptions with a small reproducible script
+
+Requirements:
+- The agent should have access to `execute_code`.
+
+Workflow:
+1. If the task needs computation or a repeatable transformation, activate this skill.
+2. If you need examples, call `read_skill_file` for `references/examples.md`.
+3. Write a short Python script for the exact task.
+4. Prefer `execute_code`.
+5. Use the script output in the final answer.
+6. Keep scripts small and task-specific.
+
+Rules:
+1. Prefer standard library Python.
+2. Print only the values you need.
+3. Do not invent outputs without running the script.
+4. If `execute_code` is not available, say exactly: `No Python execution tool is configured for this agent.`
+5. Do not claim there is a generic execution-environment problem unless a tool call actually returned such an error.
+
+Expected behavior:
+- Explain the result briefly after using the script.
+- Include the computed value or transformed output in the final answer.

.agents/skills/python-scratchpad/references/examples.md

@@ -0,0 +1,45 @@
+# Python Scratchpad Examples
+
+Example: sum a list of numbers
+
+```python
+numbers = [14, 27, 31, 8]
+print(sum(numbers))
+```
+
+Expected structured result with `execute_code`:
+
+```json
+{
+  "ok": true,
+  "exit_code": 0,
+  "stdout": "80\n",
+  "stderr": ""
+}
+```
+
+Example: convert JSON to a sorted compact structure
+
+```python
+import json
+
+payload = {"b": 2, "a": 1, "nested": {"z": 3, "x": 2}}
+print(json.dumps(payload, sort_keys=True))
+```
+
+Example: count words in text
+
+```python
+text = "agent skills can trigger targeted workflows"
+print(len(text.split()))
+```
+
+Example: test a regex
+
+```python
+import re
+
+text = "Order IDs: ORD-100, BAD-7, ORD-215"
+matches = re.findall(r"ORD-\d+", text)
+print(matches)
+```

.agents/skills/rest-api-caller/SKILL.md

@@ -0,0 +1,41 @@
+---
+name: rest-api-caller
+description: Call REST APIs from Python, parse JSON responses, and report the useful fields back to the user.
+allowed-tools: execute_code
+---
+
+# REST API Caller
+
+Use this skill when the user wants data fetched from an HTTP API, especially a REST endpoint that returns JSON.
+
+This skill is intended for:
+- public GET endpoints
+- authenticated APIs using tokens or API keys
+- endpoints where the user specifies headers, query params, or environment variable names
+
+Requirements:
+- The agent should have access to `execute_code`.
+
+Workflow:
+1. Activate this skill when the task requires calling an API.
+2. If you need examples, call `read_skill_file` for `references/examples.md`.
+3. Write a short Python script that performs the request.
+4. Prefer the `requests` library if available in the environment.
+5. Prefer `execute_code`.
+6. Parse the response and print only the fields needed for the final answer.
+7. Summarize the API result clearly for the user.
+
+Rules:
+1. Do not invent API responses. Run the request first.
+2. For JSON APIs, parse JSON and extract the relevant fields instead of dumping the whole payload unless the user asks for the raw body.
+3. If the user provides an environment variable name for a token or API key, read it from `os.environ` inside the script.
+4. If the endpoint requires auth and no credential source is provided, say what is missing.
+5. If the request fails, report the HTTP status code or error message clearly.
+6. Do not claim there is a generic execution-environment issue unless the tool call actually returned one.
+
+Demo endpoint:
+- `GET https://official-joke-api.appspot.com/random_joke`
+
+Expected behavior for the demo endpoint:
+- Fetch one random joke
+- Return the setup and punchline in a readable format

.agents/skills/rest-api-caller/references/examples.md

@@ -0,0 +1,41 @@
+# REST API Caller Examples
+
+## Example 1: Public GET returning JSON
+
+Use this for the demo joke API:
+
+```python
+import requests
+
+url = "https://official-joke-api.appspot.com/random_joke"
+response = requests.get(url, timeout=30)
+response.raise_for_status()
+payload = response.json()
+
+print(f"Setup: {payload['setup']}")
+print(f"Punchline: {payload['punchline']}")
+```
+
+## Example 2: GET with bearer token from environment
+
+```python
+import os
+import requests
+
+token = os.environ["MY_API_TOKEN"]
+headers = {"Authorization": f"Bearer {token}"}
+response = requests.get("https://api.example.com/items", headers=headers, timeout=30)
+response.raise_for_status()
+print(response.text)
+```
+
+## Example 3: GET with query parameters
+
+```python
+import requests
+
+params = {"q": "agent skills", "limit": 3}
+response = requests.get("https://api.example.com/search", params=params, timeout=30)
+response.raise_for_status()
+print(response.json())
+```