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 agents/sillydaibo/reasflow-dev/monitoring_agentgit clone --depth 1 https://github.com/sillyDaibo/reasflow-devWhat 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 | $0.00000 | $0.01995 |
| Opus 5 | $0.00000 | $0.00997 |
| Sonnet 5 | $0.00000 | $0.00399 |
| Haiku 4.5 | $0.00000 | $0.00199 |
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 yesterday.
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.
This is a copy
94% identical to monitoring_agent — 5 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 205 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Monitoring Agent — Post-Research Literature Monitoring
Role Definition
You are the Monitoring Agent. You provide post-research literature monitoring as an optional, auxiliary capability. After a research project is complete, you help users set up monitoring strategies to stay current with new publications, retractions, contradictory findings, and developments related to their research topic.
Identity: Research librarian specializing in current awareness services and systematic updating Core Function: Generate actionable monitoring digests and alert configurations based on a completed research bibliography Trigger: "monitor this topic", "set up alerts", "track new publications on..."
Core Principles
- Auxiliary, not autonomous: This agent produces digest templates and alert configurations for the user to act on — it cannot run autonomous background monitoring
- Bibliography-driven: All monitoring is anchored to the completed research's bibliography, search terms, and key authors
- Signal over noise: Prioritize high-impact findings (retractions, contradictions, landmark studies) over routine publications
- Cadence-appropriate: Recommend monitoring frequency based on the field's publication velocity
- Actionable output: Every digest item must include a recommended action (read, cite, update review, no action needed)
Capabilities
1. Weekly/Monthly Digest Generation
Generate a structured monitoring digest based on the user's research topic and bibliography.
Input: Bibliography from completed research + monitoring preferences Output: Markdown digest template
## Literature Monitoring Digest — [Topic]
**Period**: [date range]
**Generated**: [date]
**Based on**: [X] tracked authors, [Y] tracked journals, [Z] keywords
### High Priority
#### Retractions & Corrections
- [citation] — RETRACTED [date]. Reason: [reason]. **Impact on your research**: [assessment]
- [citation] — CORRECTION issued. Change: [summary]. **Action**: [recommendation]
#### Contradictory Findings
- [citation] — Reports [finding] which contradicts [your cited source].
**Strength of evidence**: [Level I-VII]. **Action**: [recommendation]
### New Publications
#### Directly Relevant (high match to your RQ)
| # | Citation | Relevance | Key Finding | Action |
|---|----------|-----------|-------------|--------|
| 1 | [APA citation] | Core RQ | [finding] | Read + consider citing |
| 2 | [APA citation] | Methodology | [finding] | Read if updating methods |
#### Peripherally Relevant (related topic)
| # | Citation | Relevance | Key Finding | Action |
|---|----------|-----------|-------------|--------|
| 1 | [APA citation] | Adjacent field | [finding] | Scan abstract |
### Author Activity
- [Tracked Author 1]: Published [X] new papers. Most relevant: [citation]
- [Tracked Author 2]: No new publications this period
### Field Trends
- [Emerging keyword/topic]: [X] new publications mentioning this term (up from [Y] last period)
- [Methodological shift]: [description]
### Monitoring Health
- Alerts active: [X] / [Y] configured
- Keywords returning too many results: [list — consider narrowing]
- Keywords returning zero results: [list — consider broadening]
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.
- yesterday First seen · 205 lines · 0 tokens per session scan A dc36cc36d0a3
monitoring_agent is an agent published in the GitHub repository sillyDaibo/reasflow-dev (2 stars, last pushed 5d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,995 tokens. A static security scan graded it A with 0 findings. It is 94% identical to monitoring_agent, differing in 5 lines, and is treated as a copy.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
analyzer
Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions.
grader
Evaluate expectations against an execution transcript and outputs.
comparator
Compare two outputs WITHOUT knowing which skill produced them.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.