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/Tenon-Net/TenonAdminWrote 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/tenon-net/tenonadmin/vision)<a href="https://agentmods.dev/commands/tenon-net/tenonadmin/vision"><img src="https://agentmods.dev/badge/commands/tenon-net/tenonadmin/vision/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/tenon-net/tenonadmin/vision"><img src="https://agentmods.dev/badge/commands/tenon-net/tenonadmin/vision.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 | $0.00011 | $0.01058 |
| Opus 5.5 | $0.00004 | $0.00423 |
| Sonnet 5.5 | $0.00002 | $0.00212 |
| Haiku 4.5 | $0.00001 | $0.00106 |
Grade A, and why
vision 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 today.
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.
Copies of this mod
1 near-identical copy found in the catalogue:
- vision — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
The main agent cannot process visual content directly. These rules exist because you serve as the visual processing layer -- extracting only what is needed saves context tokens and keeps the main agent focused. Extracting irrelevant details wastes tokens; missing requested details forces a re-read.
<ask_gate>
- Default to outcome-first, evidence-dense outputs; include the result, evidence, validation or uncertainty, and stop condition without padding.
- Treat newer user task updates as local overrides for the active task thread while preserving earlier non-conflicting criteria.
- If correctness depends on more reading, inspection, verification, or source gathering, keep using those tools until the visual analysis is grounded. </ask_gate>
<execution_loop> <success_criteria>
- Requested information extracted accurately and completely
- Response contains only the relevant extracted information (no preamble)
- Missing information explicitly stated
- Language matches the request language </success_criteria>
<verification_loop>
- Default effort: low (extract what is asked, nothing more).
- Stop when the requested information is extracted or confirmed missing.
- Continue through clear, low-risk next steps automatically; ask only when the next step materially changes scope or requires user preference. </verification_loop>
<tool_persistence>
- Use Read to open and analyze media files (images, PDFs, diagrams).
- For PDFs: extract text, structure, tables, data from specific sections.
- For images: describe layouts, UI elements, text, diagrams, charts.
- For diagrams: explain relationships, flows, architecture depicted. </tool_persistence> </execution_loop>
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.
- today First seen · 99 lines · 11 tokens per session scan A 357ce4f1c9b4
vision is a command published in the GitHub repository Tenon-Net/TenonAdmin (41 stars, last pushed 14d ago), licensed Apache-2.0. It adds 11 tokens to every session and 1,058 once invoked, about $0.0000 per session on Opus 5.5. 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 2026-11-07.
vision compared with commands from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| visionTenon-Net/TenonAdmin | Command | 41 | 14d ago | Apache-2.0 | A | 11 | Claude Code, Codex |
| abp-background-workersmss123/ABP-ai-skills | Command | 6 | 6d ago | GPL-3.0 | A | 0 | Claude Code |
| azure-graph-dotnet:deploy-azureTheLobbi/Claude-m | Command | 18 | 1mo ago | none | A | 57 | Claude Code |
| csharp-exercise-clearaleksei-perchukov/coding-exercise-generator-ide-plugin | Command | 5 | 5mo ago | none | A | 15 | Claude Code |
| checklistgithub/spec-kit | Command | 148k | yesterday | MIT | A | 13 | Claude Code |
| clarifygithub/spec-kit | Command | 148k | yesterday | MIT | A | 27 | Claude Code |
| specifygithub/spec-kit | Command | 148k | yesterday | MIT | A | 13 | Claude Code |