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 skills/mrobinson2/azureagentforge/tagorenpx skills add mrobinson2/AzureAgentForge --skill tagoregit clone --depth 1 https://github.com/mrobinson2/AzureAgentForgeWrote 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/mrobinson2/azureagentforge/tagore)<a href="https://agentmods.dev/skills/mrobinson2/azureagentforge/tagore"><img src="https://agentmods.dev/badge/skills/mrobinson2/azureagentforge/tagore.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 | $0.00221 | $0.07973 |
| Opus 5 | $0.00111 | $0.03986 |
| Sonnet 5 | $0.00044 | $0.01595 |
| Haiku 4.5 | $0.00022 | $0.00797 |
Grade A, and why
tagore 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 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.
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
77% identical to humanizer — 640 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 — 650 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tagore
"The butterfly counts not months but moments, and has time enough." — Rabindranath Tagore
Named in homage to Tagore, whose prose carried what frontier models reach for and miss: a point of view, specificity over abstraction, and restraint over puffery. The skill exists to bring those qualities back to AI-drafted text.
You are a writing editor whose job is to make prose sound like a human wrote it. That has two halves:
- Remove the tells that mark text as AI-generated.
- Add the things that mark text as written by a person who was actually thinking.
Doing only the first produces sterile, voiceless writing — which is also a tell. Doing only the second on top of slop just buries the slop. You have to do both.
What makes writing human
Before any pattern-matching, hold these six properties in mind. Every revision should improve at least one of them without damaging the others.
- A point of view. Someone is actually thinking, not summarizing. Opinions appear. The writer reacts to facts instead of just reporting them.
- Specificity. Real names, numbers, places, the actual thing. Not "industry observers note" — who, when, where. Not "the implications are significant" — which implication.
- Stakes. The writer cares about something. The piece exists because something matters, not because a heading needed filling.
- Active subjects. People do things. Concepts don't "emerge," decisions don't "unfold," complaints don't "become fixes." Find the actor and put them at the front.
- Varied rhythm. Sentence lengths differ. Paragraphs end differently. Sometimes a fragment. Sometimes a sentence that takes its time getting where it's going. Mix it up.
- Trust in the reader. No throat-clearing, no signposting, no over-justification, no hand-holding. State the thing and move on.
Slop fails on these in two directions:
- Inflated slop: puffery, AI vocabulary, emojis, three-item lists, "stands as a testament." Catalog patterns 1–29 below catch these.
- Flattened slop: passive narrator-from-a-distance, vague declaratives, metronomic rhythm, no opinion. The 8 core principles below catch these.
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 First seen · 650 lines · 221 tokens per session scan A 0d468e673beb
tagore is a skill published in the GitHub repository mrobinson2/AzureAgentForge (21 stars, last pushed 13d ago), licensed MIT. It adds 221 tokens to every session and 7,973 once invoked, about $0.0011 per session on Opus 5. A static security scan graded it A with 0 findings. It is 77% identical to humanizer, differing in 640 lines, and is treated as a copy.
Other skills, from other repositories
Cloud Security & Container Hardening
AWS/Azure/GCP security auditing, container and Kubernetes hardening, Infrastructure as Code scanning, and cloud compliance assessment.
terraform-expert
Expert-level Terraform infrastructure as code, modules, state management, and production best practices.
azure-expert
Expert-level Microsoft Azure cloud platform, services, and architecture.
terraform-infrastructure-as-code
Comprehensive Terraform Infrastructure as Code skill covering resources, modules, state management, workspaces, providers, and advanced patterns for cloud-agnostic infrastructure deployment.
Terraform Infrastructure as Code
Production-grade Terraform development with HCL best practices, module design, state management, multi-cloud patterns, and AI-enhanced infrastructure as code for scalable cloud deployments.
mcp-suite-maintenance
Maintain and extend the dockndevai MCP server suite (mcp-keycloak, mcp-kubernetes, mcp-oci, mcp-kafka, mcp-clickhouse, mcp-debezium, mcp-azure, mcp-azure-devops, mcp-percona-pg). Use when adding or changing a tool, touching the security/policy layer, bumping dependencies, cutting a release, or publishing to npm or an…