tRPC-Agent-Go is a Go framework for building AI agent applications with language models, graph-based workflows, tools, memory, retrieval, evaluation, and observability. Go developers use it to create deployable agent systems that can integrate with A2A, AG-UI, and MCP. The catalogue add-ons provide reusable workflows and agent integrations for the framework.
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 skills add trpc-group/trpc-agent-go --skill recommend_poigit clone --depth 1 https://github.com/trpc-group/trpc-agent-goWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/trpc-group/trpc-agent-go/recommend_poi)<a href="https://agentmods.dev/skills/trpc-group/trpc-agent-go/recommend_poi"><img src="https://agentmods.dev/badge/skills/trpc-group/trpc-agent-go/recommend_poi/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/trpc-group/trpc-agent-go/recommend_poi"><img src="https://agentmods.dev/badge/skills/trpc-group/trpc-agent-go/recommend_poi.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What 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 5.1 | $0.00017 | $0.00177 |
| Opus 5 | $0.00009 | $0.00088 |
| Sonnet 5 | $0.00003 | $0.00035 |
| Haiku 4.5 | $0.00002 | $0.00018 |
Grade A, and why
recommend_poi 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 9d 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.
What it actually says
recommend_poi
This skill is used by the dynamic structured output demo.
Output JSON Schema
{
"type": "object",
"properties": {
"poi": {
"type": "string",
"description": "Point of interest"
},
"city": {
"type": "string",
"description": "City name"
},
"score": {
"type": "integer",
"description": "A deterministic score"
}
},
"required": [
"poi",
"city",
"score"
],
"additionalProperties": false
}
Commands
Print JSON result to stdout:
cat result.json
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 45 lines · 17 tokens per session scan A 609a3eb62e6c
recommend_poi is a skill published in the GitHub repository trpc-group/trpc-agent-go (1,770 stars, last pushed yesterday), licensed Apache-2.0. It adds 17 tokens to every session and 177 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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