Borrowing it
Nothing to install: this file belongs to Undertone0809/rudder. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Undertone0809/rudder/main/.agents/skills/maintainer/rudder-real-runtime-verifier-maintainer/SKILL.mdgit clone --depth 1 https://github.com/Undertone0809/rudderWrote 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/undertone0809/rudder/rudder-real-runtime-verifier-maintainer)<a href="https://agentmods.dev/skills/undertone0809/rudder/rudder-real-runtime-verifier-maintainer"><img src="https://agentmods.dev/badge/skills/undertone0809/rudder/rudder-real-runtime-verifier-maintainer/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/undertone0809/rudder/rudder-real-runtime-verifier-maintainer"><img src="https://agentmods.dev/badge/skills/undertone0809/rudder/rudder-real-runtime-verifier-maintainer.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 | $0.00099 | $0.01640 |
| Opus 5 | $0.00049 | $0.00820 |
| Sonnet 5 | $0.00020 | $0.00328 |
| Haiku 4.5 | $0.00010 | $0.00164 |
Grade A, and why
rudder-real-runtime-verifier-maintainer scanned grade A with 1 finding 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 4d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
description: "Use when verifying Rudder agent runtime behavior in a real local environment, especially MCP/native Rudder tools across Codex, Claude, OpenCode, Pi, or user-named runtimes. Trigger for requests like 真是/真实环境 How it starts
The opening of the file, as written. The whole thing — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Rudder Real Runtime Verifier Maintainer
Verify Rudder agent runtime behavior on the user's real local Rudder instance. This is a black-box runtime acceptance workflow, not an implementation or code review workflow.
Default to Chinese when the user asks in Chinese. Put the current truth first: which runtimes passed, failed, or were blocked, and what transcript evidence proves it.
Role Boundary
Default to verification and diagnosis only:
- Run real local runtime probes and inspect run transcripts, logs, API state, issue state, comments, and run metadata.
- Create disposable orgs, agents, issues, and runs when needed for proof.
- Separate provider/model failure from Rudder adapter failure.
- Report exact blockers and smallest likely fixes.
- As an independent verifier, do not edit source, configs, Git state, or product docs. Return findings to the implementer. The parent retains any existing fix authority; verification does not require that authority to be repeated.
If the user asks to fix the issue, hand back to the lifecycle implementation route or make the smallest explicit patch, then require this skill's real runtime proof again before claiming done.
When This Skill Wins
Use this skill when the core question is whether an agent runtime actually did the work through Rudder-managed tools in a real local run.
Typical prompts:
- "你所有的 agent runtime 都本地测过跑过真实环境了吗?"
- "OpenCode and Pi agent 你也测了吗?"
- "看 transcript,别让它 fallback 用 rudder cli"
- "排查所有 rudder tools,都试一遍"
- "MCP tool 报 org id/auth 问题,正常 agent 调 tool 不该传 org"
- "Codex/Claude/OpenCode/Pi 真实环境跑一下"
If the user asks for general product acceptance that is not runtime/tool-call
specific, use product-acceptance-verifier-maintainer instead. If the user
provides only one failed run id and wants root cause, use
debug-run-transcript-maintainer first, then return here for rerun proof after
a fix.
Runtime Matrix
Select the runtime matrix from the user's request and the changed integration. Test one runtime for a runtime-specific claim. Use the full supported matrix for an explicit all-runtime claim or a shared adapter/tool change that affects it:
What ships with it
7 files 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.
- 4d ago Changed · +5 lines 1cbf02203cc5
- 11d ago First seen · 152 lines · 99 tokens per session scan A 4356922f80ea
rudder-real-runtime-verifier-maintainer is a skill published in the GitHub repository Undertone0809/rudder (288 stars, last pushed yesterday), licensed Apache-2.0. It adds 99 tokens to every session and 1,640 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
research-engineer
An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.
tika-eval-compare
Compare extracts from two Tika builds over a corpus to detect regressions in content, encoding, exceptions, and embedded-document handling. Use for "compare before/after extracts", "eval this change against the corpus".
neuron-evaluation-engineer
Create and run AI evaluations with datasets, assertions, and output drivers in Neuron AI. Use this skill whenever the user mentions evaluation, testing AI systems, creating evaluators, dataset-driven testing, assertion-based validation, or wants to measure AI system performance. Also trigger for tasks involving…
jetson-validate-image
Use after jetson-flash-image to run static BSP checks, on-target smoke/regression tests on a flashed DUT, or both. Not for build or flash steps. Triggers: validate bsp, on-target validation.
atmos-validation
Validate Atmos projects, components, arbitrary JSON Schema inputs, EditorConfig, and GitHub Actions; use affected-file selection and native CI annotations.
skill-benchmark
Benchmark AI skill effectiveness by measuring implementation quality against legacy constraints.