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 python_mathgit 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/python_math)<a href="https://agentmods.dev/skills/trpc-group/trpc-agent-go/python_math"><img src="https://agentmods.dev/badge/skills/trpc-group/trpc-agent-go/python_math/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/python_math"><img src="https://agentmods.dev/badge/skills/trpc-group/trpc-agent-go/python_math.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 | $0.00013 | $0.00125 |
| Opus 5.5 | $0.00005 | $0.00050 |
| Sonnet 5.5 | $0.00003 | $0.00025 |
| Haiku 4.5 | $0.00001 | $0.00013 |
Grade A, and why
python-math 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 1mo 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
Overview
Run short Python scripts inside the skill workspace. Results can be returned as text and saved as output files.
Examples
-
Print the first N Fibonacci numbers
Command:
python3 scripts/fib.py 10 > out/fib.txt
-
Sum a list of integers
Command:
python3 - <<'PY' from sys import stdin nums = [int(x) for x in stdin.read().split()] print(sum(nums)) PY
Output Files
- out/fib.txt
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.
- 1mo ago First seen · 32 lines · 13 tokens per session scan A 42f6466dffde
python-math is a skill published in the GitHub repository trpc-group/trpc-agent-go (1,863 stars, last pushed yesterday), licensed Apache-2.0. It adds 13 tokens to every session and 125 once invoked, about $0.0001 per session on Opus 5.5. 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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