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.
git clone --depth 1 https://github.com/tuoxie2046/claude-code-research-skillsWrote 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/agents/tuoxie2046/claude-code-research-skills/monitoring_agent)<a href="https://agentmods.dev/agents/tuoxie2046/claude-code-research-skills/monitoring_agent"><img src="https://agentmods.dev/badge/agents/tuoxie2046/claude-code-research-skills/monitoring_agent.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00023 | $0.02025 |
| Opus 5 | $0.00012 | $0.01012 |
| Sonnet 5 | $0.00005 | $0.00405 |
| Haiku 4.5 | $0.00002 | $0.00202 |
Grade A, and why
monitoring_agent 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 8d 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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.
- 8d ago First seen · 210 lines · 23 tokens per session scan A 76179537d4be
monitoring_agent is an agent published in the GitHub repository tuoxie2046/claude-code-research-skills (5 stars, last pushed 2mo ago), with no licence file. It adds 23 tokens to every session and 2,025 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 2026-08-31.
Other agents, from other repositories
quality-gates
Runs the repo's quality gates (lint, format, typecheck, dead-code, scoped tests) and returns a concise pass/fail report. Invoke only ONCE per slice / PR, immediately before commit — not mid-iteration, not after every file edit. Before delegating, the caller should run the project's auto-formatter on touched files…
brainstorm-swarm:designer
Brainstorming persona — UX / Product Designer. Use when the swarm-protocol skill spawns parallel persona agents and a design perspective is needed. Asks about user flow, friction, accessibility, and aesthetic coherence.
shipkit-reviewer-planning
Planning judgment worker — assesses alignment between product definitions, engineering definitions, and specs. Writes structured assessment for the planning orchestrator.
ui-designer
Use this agent when UI/UX work is needed: creating custom SwiftUI components, implementing animations, fixing layout issues, polishing visual design, building a design system, or improving accessibility. For example: adding a custom tab bar animation, implementing a skeleton loading view, auditing VoiceOver support…
ml-engineer
Use this agent when working with model architecture, training loops, loss functions, optimizers, hyperparameter tuning, experiment tracking, or model evaluation. For example: building a PyTorch model, writing a training loop with mixed precision, setting up an Optuna hyperparameter sweep, configuring MLflow experiment…
brainstorm-swarm:veteran
Brainstorming persona — Veteran / Lived Experience. Use when the swarm-protocol skill spawns parallel persona agents and pattern-matching against past failures would help. Brings war stories — "I've seen this before, here's what bit us" — with specific lessons grounded in past systems.