About Convex Agents Debugging
A debugging skill for developers building agents with Convex Agents. It helps inspect model requests, context, messages, and stored data, and covers tool-call tracing and common type issues.
Key features
- 01Log model requests and responses
- 02Inspect context messages
- 03Query agent data tables
- 04Fetch context manually
- 05Trace tool calls and results
- 06Analyze message ordering
Use cases
- 01Investigate unexpected agent behavior
- 02Check whether context is being used
- 03Audit tool calls and results
- 04Analyze message order and token usage
Install
Copy the command and run it in a terminal.
$
npx skills add https:/ / github.com/ sstobo/ convex-skills --skill convex-agents-debuggingAfter installing, type/convex-agents-debuggingin Claude Code to confirm it loaded.
Details
From the project READMEPurpose
Debugging tools help understand what's happening inside agents, what the LLM receives, and what's stored. Essential for developing reliable agent applications.
When to Use This Skill
- Agent behavior is unexpected
- LLM responses are off-target
- Investigating why certain context isn't being used
- Understanding message ordering
- Checking file storage and references
- Auditing tool calls and results
- Profiling token usage
Log Raw LLM Requests and Responses
const myAgent = new Agent(components.agent, {
name: "My Agent",
languageModel: openai.chat("gpt-4o-mini"),
rawRequestResponseHandler: async (ctx, { request, response }) => {
console.log("LLM Request:", JSON.stringify(request, null, 2));
console.log("LLM Response:", JSON.stringify(response, null, 2));
await ctx.runMutation(internal.logging.saveLLMCall, {
request,
response,
timestamp: Date.now(),
});
},
});
Log Context Messages
See exactly what context the LLM receives:
const myAgent = new Agent(components.agent, {
name: "My Agent",
languageModel: openai.chat("gpt-4o-mini"),
contextHandler: async (ctx, args) => {
console.log("Context Messages:", {
recent: args.recent.length,
search: args.search.length,
input: args.inputMessages.length,
});
args.allMessages.forEach((msg, i) => {
console.log(`Message ${i}:`, {
role: msg.role,
contentLength: typeof msg.content === "string"
? msg.content.length
: JSON.stringify(msg.content).length,
});
});
return args.allMessages;
},
});
Inspect Database Tables
Query agent data directly:
export const getThreadMessages = query({
args: { threadId: v.string() },
handler: async (ctx, { threadId }) => {
return await ctx.db
.query(components.agent.tables.messages)
.filter((msg) => msg.threadId === threadId)
.collect();
},
});
Fetch Context Manually
Inspect what context would be used:
import { fetchContextWithPrompt } from "@convex-dev/agent";
export const inspectContext = action({
args: { threadId: v.string(), prompt: v.string() },
handler: async (ctx, { threadId, prompt }) => {
const { messages } = await fetchContextWithPrompt(ctx, components.agent, {
threadId,
prompt,
});
return {
contextMessages: messages.length,
messages: messages.map((msg) => ({
role: msg.role,
contentType: typeof msg.content,
})),
};
},
});
Trace Tool Calls
Log all tool invocations:
export const myTool = createTool({
description: "My tool",
args: z.object({ query: z.string() }),
handler: async (ctx, { query }): Promise<string> => {
console.log("[TOOL] myTool called with:", query);
const result = await someOperation(query);
console.log("[TOOL] myTool returned:", result);
return result;
},
});
Fix Type Errors
Common circular reference issue:
// WRONG - no return type
export const myFunction = action({
args: { prompt: v.string() },
handler: async (ctx, { prompt }) => {
return await someLogic();
},
});
// CORRECT - explicit return type
export const myFunction = action({
args: { prompt: v.string() },
returns: v.string(),
handler: async (ctx, { prompt }): Promise<string> => {
return await someLogic();
},
});
Analyze Message Structure
Debug message ordering:
export const analyzeMessages = query({
args: { threadId: v.string() },
handler: async (ctx, { threadId }) => {
const messages = await listMessages(ctx, components.agent, {
threadId,
paginationOpts: { cursor: null, numItems: 100 },
});
return messages.results.map((msg) => ({
order: msg.order,
stepOrder: msg.stepOrder,
role: msg.message.role,
status: msg.status,
}));
},
});
Key Principles
- Log early: Capture data while developing
- Use console for quick checks: Fast iteration
- Save important events: Archive LLM calls for analysis
- Explicit return types: Prevents circular references
- Dashboard inspection: Easiest way to see database state
Next Steps
- See playground for interactive debugging
- See fundamentals for agent setup
- See context for context-aware debugging
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