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/dtannen/icon-agentsWrote 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/commands/dtannen/icon-agents/icon-data-ai-review)<a href="https://agentmods.dev/commands/dtannen/icon-agents/icon-data-ai-review"><img src="https://agentmods.dev/badge/commands/dtannen/icon-agents/icon-data-ai-review/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/commands/dtannen/icon-agents/icon-data-ai-review"><img src="https://agentmods.dev/badge/commands/dtannen/icon-agents/icon-data-ai-review.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00027 | $0.00724 |
| Opus 5 | $0.00014 | $0.00362 |
| Sonnet 5 | $0.00005 | $0.00145 |
| Haiku 4.5 | $0.00003 | $0.00072 |
Grade A, and why
Icon Data & AI Review 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 12d 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
A licence we could not identify
The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.
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.
- 12d ago First seen · 70 lines · 27 tokens per session scan A 647b420bd414
Icon Data & AI Review is a command published in the GitHub repository dtannen/icon-agents (23 stars, last pushed 1y ago), with no licence file. It adds 27 tokens to every session and 724 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 2026-08-30.
Other commands, from other repositories
hatch3r-workflow
Guided development lifecycle with 4 phases (Analyze, Plan, Implement, Review) and scale-adaptive Quick Mode for small tasks; --plan-file executes an approved plan document without re-deriving it.
greet
Generate contextual agent greeting using GreetingBuilder infrastructure.
add-rule
Adds a new rule to an existing SYNAPSE domain file.
validate-pipeline
Validate data pipeline configuration and data quality rules.
rag-retrieval
RAG pipeline patterns for grounded LLM responses. Use when building a Q&A system, adding citations, implementing a knowledge base, or preventing hallucinations. Triggers on RAG, retrieval augmented, knowledge base, Q&A pipeline, citations, hybrid search, context retrieval, hallucination prevention.
models
Search Ryu's model catalog and optionally activate a local model.