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 skills add scenario-labs/skills --skill scenario-moderationgit clone --depth 1 https://github.com/scenario-labs/skillsWrote 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/scenario-labs/skills/scenario-moderation)<a href="https://agentmods.dev/skills/scenario-labs/skills/scenario-moderation"><img src="https://agentmods.dev/badge/skills/scenario-labs/skills/scenario-moderation/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/skills/scenario-labs/skills/scenario-moderation"><img src="https://agentmods.dev/badge/skills/scenario-labs/skills/scenario-moderation.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 | $0.00092 | $0.01361 |
| Opus 5 | $0.00046 | $0.00681 |
| Sonnet 5 | $0.00018 | $0.00272 |
| Haiku 4.5 | $0.00009 | $0.00136 |
Grade A, and why
scenario-moderation 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 9d 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 — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Scenario Blocked Generations
Overview
Content filters run on the model provider's side, not on Scenario. A block is therefore a property of the model that was picked, not of the account or of the prompt in the abstract, and the same prompt usually passes on other models in the catalog. Treat a block as a routing problem first and a wording problem second. This skill is about false positives on content a team is entitled to make; it is not a way to produce content a provider prohibits. Core loop: see the scenario skill. If a sibling skill named here is missing from your available skills, ask the user to install it (npx skills add scenario-labs/skills --skill <name>); unattended, proceed from tool schemas and flag the gap.
Quick reference
| Step | Call |
|---|---|
| Read the actual error | job_get with job_id: the row carries error and hint, plus modelId (the model to exclude) and cuCost (what the failed run charged); verbose=true adds metadata.input with the exact prompt the job ran. Or read error and hint off the jobs_wait row |
| Find alternative models | recommend with the failed job's capability (txt2img for a text-to-image block, img2img with a reference in play) plus the user's own words; set max_cost_cu a little above the failed row's cuCost per asset to stay in the cost band, and drop the failed modelId from the ranking yourself, since recommend has no exclusion argument |
| Price an alternative | model_run with dry_run=true |
| Re-test the same intent | One model_run per candidate, prompt unchanged, so the model stays the only variable |
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.
- 9d ago Changed 51028156efcc
- 12d ago First seen · 59 lines · 92 tokens per session scan A 861d6448a84d
scenario-moderation is a skill published in the GitHub repository scenario-labs/skills (11 stars, last pushed today), licensed MIT. It adds 92 tokens to every session and 1,361 once invoked, about $0.0005 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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