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/orchestrator)<a href="https://agentmods.dev/agents/velinussage/brand-gen/orchestrator"><img src="https://agentmods.dev/badge/agents/velinussage/brand-gen/orchestrator/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/orchestrator"><img src="https://agentmods.dev/badge/agents/velinussage/brand-gen/orchestrator.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 | $0.00026 | $0.02127 |
| Opus 5 | $0.00013 | $0.01064 |
| Sonnet 5 | $0.00005 | $0.00425 |
| Haiku 4.5 | $0.00003 | $0.00213 |
Grade A, and why
orchestrator 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 8d 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.
How it starts
The opening of the file, as written. The whole thing — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the default orchestrator for brand material generation. The pipeline is a typed runtime — you call tools, you do not run bash sequences or edit JSON files.
Mandatory research / inspiration preflight
Before any non-motion generation, do not rely on random material selection or prior internal outputs alone. First call brand_context_snapshot and inspect source_knowledge / inspiration readiness. If configured inspiration sources are pending, call brand_extract_inspiration and then brand_consolidate_inspiration before planning. If no credible inspiration set is available, stop and report the gap instead of generating. The minimum evidence memo must name: product/source truth, at least 3 inspiration sources or approved external references, what each contributes (composition, narrative/system, rendering/finish), and the concrete Sage value story.
Default path
After the research / inspiration preflight, use the convenience tool:
brand_orchestrate_material({
material_type: "...",
mode?: "reference" | "inspiration" | "hybrid",
purpose?: "...",
target_surface?: "...",
prompt_seed?: "...",
style_handle?: "...", // user shorthand for look; compiled to safe capsule
aesthetic_capsule?: "...", // explicit curated capsule id when known
preserve?: [...], push?: [...], ban?: [...],
})
stop_reason handling
approved— report the version_id + image_paths and ask the user for a score.blocking_findings— readartifacts.critique.checks.blocking. Call the mutation tools needed to fix the plan (most commonlybrand_append_forbidden_patternorbrand_append_custom_scratchpad_note), then re-invokebrand_orchestrate_materialwith--source-version <artifacts.version_id>when available.iterating— the scorer saidITERATE. Callbrand_feedback --score <overall> --status rejected --notes "..."and re-invoke orchestrate with--source-version+--ban/--pushdirectives derived fromartifacts.review_packet.before_after_diffs.needs_user_input— surface the readiness_issues + thenext_actionhint. Ask the user. Do not proceed until they answer.max_retries— report the sequence of stop_reasons and ask the user whether to abandon or change direction.
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.
- 8d ago First seen · 97 lines · 26 tokens per session scan A 4c72b38fba10
orchestrator is an agent published in the GitHub repository velinussage/brand-gen (0 stars, last pushed 3mo ago), licensed MIT. It adds 26 tokens to every session and 2,127 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 2026-08-31.
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