REPL. New AgentCard in md fromat and CLI loading/lazy hot swap with --agent-cards | --watch | --reload options. New workflow-md samples

AGENTS.md

@@ -1,2 +1,7 @@
-Present links to images and other content in Markdown links -- for example: ![Image](https://link.to.image)
+## fast-agent contributor notes
 
+- Use `uv run` for repo scripts and examples.
+- Always run `uv run scripts/lint.py` and `uv run scripts/typecheck.py` after code changes.
+- Keep examples under `examples/` in sync with packaged resources when relevant.
+- Prefer small, focused diffs; avoid reformatting unrelated code.
+- Use Markdown links for images and other content (example: `![Image](https://link.to.image)`).

examples/mcp/elicitations/elicitation_forms_server.py

@@ -7,7 +7,7 @@
 
 import logging
 import sys
-from typing import Optional, TypedDict
+from typing import Optional, TypedDict, cast
 
 from mcp import ReadResourceResult
 from mcp.server.elicitation import (
@@ -51,7 +51,10 @@ def _create_enum_schema_options(data: dict[str, str]) -> list[TitledEnumOption]:
         >>> _create_enum_schema_options({"dark": "Dark Mode", "light": "Light Mode"})
         [{"const": "dark", "title": "Dark Mode"}, {"const": "light", "title": "Light Mode"}]
     """
-    return [{"const": k, "title": v} for k, v in data.items()]
+    options: list[TitledEnumOption] = [
+        cast("TitledEnumOption", {"const": k, "title": v}) for k, v in data.items()
+    ]
+    return options
 
 
 @mcp.resource(uri="elicitation://event-registration")

examples/mcp/elicitations/game_character_handler.py

@@ -33,8 +33,9 @@ async def game_character_elicitation_handler(
     """Custom handler that creates an interactive character creation experience."""
     logger.info(f"Game character elicitation handler called: {params.message}")
 
-    if params.requestedSchema:
-        properties = params.requestedSchema.get("properties", {})
+    requested_schema = getattr(params, "requestedSchema", None)
+    if requested_schema:
+        properties = requested_schema.get("properties", {})
         content: dict[str, Any] = {}
 
         console.print("\n[bold magenta]🎮 Character Creation Studio 🎮[/bold magenta]\n")

examples/tensorzero/simple_agent.py

@@ -18,7 +18,7 @@ async def main():
     async with fast.run() as agent_app:
         agent_name = "default"
         print("\nStarting interactive session with template_vars set via decorator...")
-        await agent_app.interactive(agent=agent_name)
+        await agent_app.interactive(agent_name=agent_name)
 
 
 if __name__ == "__main__":

examples/workflows-md/agents_as_tools_extended/London-Project-Manager.md

@@ -0,0 +1,8 @@
+---
+type: agent
+name: London-Project-Manager
+servers:
+- time
+- fetch
+---
+You are a London project manager. For each given topic, get the current local time in London and a brief, project-relevant news summary using the 'time' and 'fetch' MCP servers. If a source returns HTTP 403 or is blocked by robots.txt, try up to five alternative public sources before giving up and clearly state any remaining access limits. Hint: BBC: https://www.bbc.com/ and FT: https://www.ft.com/

examples/workflows-md/agents_as_tools_extended/NY-Project-Manager.md

@@ -0,0 +1,8 @@
+---
+type: agent
+name: NY-Project-Manager
+servers:
+- time
+- fetch
+---
+You are a New York project manager. For each given topic, get the current local time in New York and a brief, project-relevant news summary using the 'time' and 'fetch' MCP servers. If a source returns HTTP 403 or is blocked by robots.txt, try up to five alternative public sources before giving up and clearly state any remaining access limits. Hint: Fast-Agent site: https://fast-agent.ai

examples/workflows-md/agents_as_tools_extended/PMO-orchestrator.md

@@ -0,0 +1,13 @@
+---
+type: agent
+name: PMO-orchestrator
+default: true
+agents:
+- NY-Project-Manager
+- London-Project-Manager
+history_mode: scratch
+max_parallel: 128
+child_timeout_sec: 120
+max_display_instances: 20
+---
+Get project updates from the New York and London project managers. Ask NY-Project-Manager three times about different projects: Anthropic, evalstate/fast-agent, and OpenAI, and London-Project-Manager for economics review. Return a brief, concise combined summary with clear city/time/topic labels.

examples/workflows-md/agents_as_tools_simple/London-Project-Manager.md

@@ -0,0 +1,7 @@
+---
+type: agent
+name: London-Project-Manager
+servers:
+- time
+---
+Return London time + timezone, plus a one-line news update.

examples/workflows-md/agents_as_tools_simple/NY-Project-Manager.md

@@ -0,0 +1,7 @@
+---
+type: agent
+name: NY-Project-Manager
+servers:
+- time
+---
+Return NY time + timezone, plus a one-line project status.

examples/workflows-md/agents_as_tools_simple/PMO-orchestrator.md

@@ -0,0 +1,9 @@
+---
+type: agent
+name: PMO-orchestrator
+default: true
+agents:
+- NY-Project-Manager
+- London-Project-Manager
+---
+Get reports. Always use one tool call per project/news. Responsibilities: NY projects: [OpenAI, Fast-Agent, Anthropic]. London news: [Economics, Art, Culture]. Aggregate results and add a one-line PMO summary.

examples/workflows-md/chaining/post_writer.md

@@ -0,0 +1,9 @@
+---
+type: chain
+name: post_writer
+default: true
+sequence:
+- url_fetcher
+- social_media
+---
+Chain processes requests through a series of agents in sequence, the output of each agent is passed to the next.

examples/workflows-md/chaining/social_media.md

@@ -0,0 +1,7 @@
+---
+type: agent
+name: social_media
+---
+
+    Write a 280 character social media post for any given text. 
+    Respond only with the post, never use hashtags.

examples/workflows-md/chaining/url_fetcher.md

@@ -0,0 +1,7 @@
+---
+type: agent
+name: url_fetcher
+servers:
+- fetch
+---
+Given a URL, provide a complete and comprehensive summary

examples/workflows-md/evaluator/cover_letter_writer.md

@@ -0,0 +1,13 @@
+---
+type: evaluator_optimizer
+name: cover_letter_writer
+generator: generator
+evaluator: evaluator
+min_rating: EXCELLENT
+max_refinements: 3
+refinement_instruction: null
+---
+
+    You implement an iterative refinement process where content is generated,
+    evaluated for quality, and then refined based on specific feedback until
+    it reaches an acceptable quality standard.

examples/workflows-md/evaluator/evaluator.md

@@ -0,0 +1,21 @@
+---
+type: agent
+name: evaluator
+model: o3-mini.medium
+---
+Evaluate the following response based on the criteria below:
+    1. Clarity: Is the language clear, concise, and grammatically correct?
+    2. Specificity: Does the response include relevant and concrete details tailored to the job description?
+    3. Relevance: Does the response align with the prompt and avoid unnecessary information?
+    4. Tone and Style: Is the tone professional and appropriate for the context?
+    5. Persuasiveness: Does the response effectively highlight the candidate's value?
+    6. Grammar and Mechanics: Are there any spelling or grammatical issues?
+    7. Feedback Alignment: Has the response addressed feedback from previous iterations?
+
+    For each criterion:
+    - Provide a rating (EXCELLENT, GOOD, FAIR, or POOR).
+    - Offer specific feedback or suggestions for improvement.
+
+    Summarize your evaluation as a structured response with:
+    - Overall quality rating.
+    - Specific feedback and areas for improvement.

examples/workflows-md/evaluator/generator.md

@@ -0,0 +1,10 @@
+---
+type: agent
+name: generator
+model: gpt-5-nano.low
+servers:
+- fetch
+---
+You are a career coach specializing in cover letter writing.
+    You are tasked with generating a compelling cover letter given the job posting,
+    candidate details, and company information. Tailor the response to the company and job requirements.

examples/workflows-md/fastagent.config.yaml

@@ -0,0 +1,26 @@
+# Please edit this configuration file to match your environment (on Windows).
+# Examples in comments below - check/change the paths.
+#
+#
+
+logger:
+  type: file
+  level: error
+  truncate_tools: true
+
+mcp:
+  servers:
+    filesystem:
+      # On windows update the command and arguments to use `node` and the absolute path to the server.
+      # Use `npm i -g @modelcontextprotocol/server-filesystem` to install the server globally.
+      # Use `npm -g root` to find the global node_modules path.`
+      # command: "node"
+      # args: ["c:/Program Files/nodejs/node_modules/@modelcontextprotocol/server-filesystem/dist/index.js","."]
+      command: "npx"
+      args: ["-y", "@modelcontextprotocol/server-filesystem", "."]
+    fetch:
+      command: "uvx"
+      args: ["mcp-server-fetch"]
+    time:
+      command: "uvx"
+      args: ["mcp-server-time"]