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 duc01226/EasyPlatform --skill scenariogit clone --depth 1 https://github.com/duc01226/EasyPlatformWrote 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/duc01226/easyplatform/scenario)<a href="https://agentmods.dev/skills/duc01226/easyplatform/scenario"><img src="https://agentmods.dev/badge/skills/duc01226/easyplatform/scenario/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/duc01226/easyplatform/scenario"><img src="https://agentmods.dev/badge/skills/duc01226/easyplatform/scenario.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 | $0.00033 | $0.02545 |
| Opus 5.5 | $0.00013 | $0.01018 |
| Sonnet 5.5 | $0.00007 | $0.00509 |
| Haiku 4.5 | $0.00003 | $0.00254 |
Grade A, and why
scenario 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 3d 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 — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Codex compatibility note:
- Invoke
$skill-name: load the registered.agents/skills/<name>/SKILL.mdand execute it with Codex tools; no separateSkilltool or Claude mode switch is needed. Author.claude/**; mirrors are generated.- Track steps before execution and keep progress/evidence current. Explicit skill requests execute their protocol. Use the native question tool for required questions.
- Map foreign tool names to available host capabilities. A name mismatch needs no approval; an actually unavailable required capability stops with its step/evidence and a user question before adaptation.
- Subagent authorization: when a skill is user-invoked or AI-detected and its protocol requires subagents, that skill activation authorizes use of the required
spawn_agentsubagent(s) for that task.- Preserve protocol order unless the user approves a deviation. Workflows use
$start-workflow: gates stay fixed; other steps may flex with logged reasons and evidence.
[BLOCKING] Run phases in order; update todo tracking before and after each phase. [BLOCKING] Every completed or skipped phase needs concise evidence or a reason.
Quick Summary
Goal: Turn one selected embedded outcome slice, explicit roadmap milestone, framework/library scope, or explicitly accepted isolated change into an adversarial, observable scenario set that exposes data corruption, misleading states, access leaks, and recovery gaps before an implementation plan can be approved.
Summary:
- Resolve the owning decomposition block, explicit roadmap milestone, framework technical scope, or EXEMPT scope and stable plan directory; block when the applicable upstream scope is missing or unapproved. The embedded branch does not require a product roadmap.
- Derive scenarios from the user journey and source-of-truth state, then stress refresh/replay, invalid input, concurrency, deletion, lifecycle, access, partial failure, and evidence hygiene.
- Map every high-impact scenario to an invariant, expected outcome, prevention/detection expectation, and TC/evidence; ask the owner about material choices.
- Write
{plan-id}/scenario-analysis.mdunder the plans root (defaultplans/; adocsRoots.plans.pathentry indocs/project-config.jsonoverrides the path) and mark the Scenario Gate PASS or BLOCKED;$plancannot cook from a blocked gate, and an EXEMPT plan still needs this artifact. - Main steps: resolve inputs/branch → reconstruct the selected journey and source of truth → generate adversarial scenarios → resolve owner decisions → write the analysis → run the Scenario Gate → hand off to
$planor record a conditional skip.
Workflow: 0) resolve inputs → 1) reconstruct scope → 2) generate adversarial scenarios → 3) resolve decisions → 4) write artifact → 5) run Scenario Gate → 6) hand off to $plan.
Key Rules:
- Scenarios describe situations and expected outcomes, not framework or database solutions.
- A happy path alone is never sufficient for persistent/stateful work.
- High-impact scenarios without evidence or an owner decision block the plan.
- Never put secrets, real payment data, tokens, or personal data in scenario/evidence artifacts.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 3d ago First seen · 146 lines · 33 tokens per session scan A 664d2361ceac
scenario is a skill published in the GitHub repository duc01226/EasyPlatform (12 stars, last pushed yesterday), licensed MIT. It adds 33 tokens to every session and 2,545 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 2026-10-18.
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