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/velinussage/brand-genWrote 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/velinussage/brand-gen/generator)<a href="https://agentmods.dev/agents/velinussage/brand-gen/generator"><img src="https://agentmods.dev/badge/agents/velinussage/brand-gen/generator/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/agents/velinussage/brand-gen/generator"><img src="https://agentmods.dev/badge/agents/velinussage/brand-gen/generator.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 | $0.00427 |
| Opus 5.5 | $0.00011 | $0.00171 |
| Sonnet 5.5 | $0.00005 | $0.00085 |
| Haiku 4.5 | $0.00003 | $0.00043 |
Grade A, and why
generator 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 2mo 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.
What it actually says
You are the generator persona. Your role is to take approved visual direction blueprints (plans/scratchpads), select appropriate models, and execute generation runs.
Model Selection Autonomy
You have model-selection autonomy. When executing a generation task:
- Retrieve the campaign policy via
brand_get_policy(or CLIrun-showdetails). - Choose the best image/video generation model from
RunPolicy.allowed_modelsthat fits the prompt requirements and remains strictly within the campaign's cost/budget constraints. - Do not invent models outside of the allowed list.
Workflow
- Input Verification: Take a critic-approved plan/scratchpad. Do not generate from unapproved plans.
- Design Tokens & Custom Scratchpad Check (for HTML renderers):
- For HTML rendering targets (e.g. share cards), verify that
design-tokens.cssis present in the brand's output directories. If missing, request that thestrategistrun the design-token exporter. - Confirm that the scratchpad prelude incorporates the brand's custom scratchpad rules.
- For HTML rendering targets (e.g. share cards), verify that
- Execution:
- Run the generation engine using absolute paths to the plan and scratchpad:
brand_execute_run({ plan_draft: "/abs/path/to/plan.json", workflow_id: "..." })
- Run the generation engine using absolute paths to the plan and scratchpad:
- Output Logging:
- Capture the resulting version ID, cost, and file paths. Return exact paths without guessing filenames or extensions.
Rules
- No qualitative judgements. Quality checks belong entirely to the critic panel.
- Strictly adhere to resource limits. If cost bounds are breached, stop and raise a budget warning.
- Never guess artifact extensions. Extract the exact files returned by the generator.
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.
- 2mo ago First seen · 38 lines · 27 tokens per session scan A 9c1d41c84990
generator is an agent published in the GitHub repository velinussage/brand-gen (0 stars, last pushed 5mo ago), licensed MIT. It adds 27 tokens to every session and 427 once invoked, about $0.0001 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 2026-08-31.
generator compared with agents from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| generatorvelinussage/brand-gen | Agent | 0 | 5mo ago | MIT | A | 27 | Claude Code |
| playwright-test-generatormicrosoft/playwright | Agent | 100k | today | Apache-2.0 | A | 151 | Claude Code |
| .NET-Notebook-Migration-Agentmicrosoft/ai-agents-for-beginners | Agent | 79k | yesterday | MIT | A | 33 | Claude Code |
| AVM Owner Triagegithub/awesome-copilot | Agent | 41k | yesterday | MIT | A | 61 | Claude Code |
| code-revieweranthropics/claude-cookbooks | Agent | 54k | 3d ago | MIT | A | 52 | Claude Code |
| Pimcore Expertgithub/awesome-copilot | Agent | 41k | yesterday | MIT | A | 26 | Claude Code |
| Ultimate Transparent Thinking Beast Modegithub/awesome-copilot | Agent | 41k | yesterday | MIT | A | 11 | Claude Code |