Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/get-convex/convex-agent-plugins/workflowgit clone --depth 1 https://github.com/get-convex/convex-agent-pluginsWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00020 | $0.00878 |
| Opus 5 | $0.00010 | $0.00439 |
| Sonnet 5 | $0.00004 | $0.00176 |
| Haiku 4.5 | $0.00002 | $0.00088 |
Grade A, and why
workflow scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Durable multi-step workflows → @convex-dev/workflow
When the task is "do step A, then B, then C, and retry each step independently if it fails" — a pipeline, ETL, or orchestration that must survive crashes — use the workflow component. Do NOT hand-roll it with a jobs table + chained ctx.scheduler.runAfter calls: that reinvents durability, loses per-step retry/backoff, and (measured) scores worse than a plain implementation. Copy this pattern.
Wire the component
// convex/convex.config.ts
import { defineApp } from "convex/server";
import workflow from "@convex-dev/workflow/convex.config";
const app = defineApp();
app.use(workflow);
export default app;
Define the workflow — one step.run* call per stage, retried independently
// convex/workflows.ts
import { WorkflowManager } from "@convex-dev/workflow";
import { components, internal } from "./_generated/api";
import { v } from "convex/values";
export const workflow = new WorkflowManager(components.workflow, {
// Per-step default: retry each failed step independently with backoff.
defaultRetryBehavior: { maxAttempts: 4, initialBackoffMs: 1000, base: 2 },
retryActionsByDefault: true,
});
export const transcribeAndSummarize = workflow.define({
args: { url: v.string(), userEmail: v.string() },
handler: async (step, args): Promise<void> => {
// Each step.runAction is durable + independently retried. If summarize fails
// 3× then succeeds, transcribe is NOT re-run — completed steps are memoized.
const transcript = await step.runAction(internal.youtube.transcribe, { url: args.url });
const summary = await step.runAction(internal.llm.summarize, { transcript });
await step.runAction(internal.email.sendSummary, { to: args.userEmail, summary });
},
});
- The handler's first arg is
step, notctx. Callstep.runAction/step.runMutation/step.runQuerywith a codegen'dinternal.*reference — neverctx.run*inside a workflow (that breaks durability/memoization). - Each
step.run*is a durable checkpoint. On crash or retry, completed steps are replayed from their stored result, not re-executed — so steps must targetinternalAction/internalMutations that do the real work. - Override retry per step when one stage is flakier:
step.runAction(ref, args, { retry: { maxAttempts: 6, initialBackoffMs: 500, base: 2 } }). Set{ retry: false }for a step that must not repeat (already-idempotent external charge). - The actual work (the YouTube fetch, the LLM call, the email send) lives in ordinary
internalActions — external APIs go in actions (seeconvex-external-apis), email via@convex-dev/resend(seecrons).
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 67 lines · 20 tokens per session scan A d444a1080aec
workflow is a command published in the GitHub repository get-convex/convex-agent-plugins (112 stars, last pushed 4d ago), licensed MIT. It adds 20 tokens to every session and 878 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
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