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 TalonT-Org/AutoSkillit --skill arch-lens-scenariosgit clone --depth 1 https://github.com/TalonT-Org/AutoSkillitWrote 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/talont-org/autoskillit/arch-lens-scenarios)<a href="https://agentmods.dev/skills/talont-org/autoskillit/arch-lens-scenarios"><img src="https://agentmods.dev/badge/skills/talont-org/autoskillit/arch-lens-scenarios/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/talont-org/autoskillit/arch-lens-scenarios"><img src="https://agentmods.dev/badge/skills/talont-org/autoskillit/arch-lens-scenarios.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 | $0.02301 |
| Opus 5 | $0.00016 | $0.01151 |
| Sonnet 5 | $0.00007 | $0.00460 |
| Haiku 4.5 | $0.00003 | $0.00230 |
Grade A, and why
arch-lens-scenarios 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 11d 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 — 298 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Scenarios Architecture Lens
Cognitive Mode: Validation (+1 Validator) Primary Question: "Do the components work together?" Focus: End-to-End User Journeys, Component Cooperation, Scenario Validation
When to Use
- Need to validate component cooperation
- Documenting key user scenarios
- Analyzing end-to-end flows through architecture
- User invokes
/autoskillit:arch-lens-scenariosor/autoskillit:make-arch-diag scenarios
Critical Constraints
NEVER:
- Modify any source code files
- Show internal component details
- Include all possible scenarios (pick key ones)
- Run subagents in the background (
run_in_background: trueis prohibited)
ALWAYS:
- Focus on END-TO-END journeys
- Show component touchpoints in sequence
- Select 3-5 representative scenarios
- Validate components work together
- BEFORE creating any diagram, LOAD the
/autoskillit:mermaidskill using the Skill tool - this is MANDATORY - If the Skill tool cannot be used (disable-model-invocation) or refuses this invocation, do NOT proceed with diagram creation. Abort this step and omit the diagram from output.
- After writing the diagram file, emit the absolute path as a structured output
token as your final output. Resolve the relative
temp/arch-lens-scenarios/...save path to absolute by prepending the full CWD:
This token is MANDATORY — the pipeline cannot proceed without it.diagram_path = /absolute/cwd/temp/arch-lens-scenarios/{filename}.md
Arguments
/autoskillit:arch-lens-scenarios [context_path]
- context_path (optional) — Absolute path to a PR context file containing new files (★-prefixed) and modified files (●-prefixed) from the PR diff. When provided, read this file before beginning analysis and focus the diagram on the architectural areas affected by these specific files. When absent, explore the full CWD.
Analysis Workflow
Step 0: Read PR context (when provided)
If a context_path positional argument is present:
- Read the file at
context_path - Extract: new files list (★-prefixed), modified files list (●-prefixed)
- Focus Step 1 exploration on the modules/components these files belong to
- Apply ★ prefix on diagram nodes representing new files/components
- Apply ● prefix on diagram nodes representing modified files/components
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.
- 11d ago First seen · 298 lines · 33 tokens per session scan A 24474d80e3d5
arch-lens-scenarios is a skill published in the GitHub repository TalonT-Org/AutoSkillit (5 stars, last pushed today), licensed MIT. It adds 33 tokens to every session and 2,301 once invoked, about $0.0002 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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