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 HoangNguyen0403/agent-skills-standard --skill system-design-sessiongit clone --depth 1 https://github.com/HoangNguyen0403/agent-skills-standardWrote 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/hoangnguyen0403/agent-skills-standard/system-design-session)<a href="https://agentmods.dev/skills/hoangnguyen0403/agent-skills-standard/system-design-session"><img src="https://agentmods.dev/badge/skills/hoangnguyen0403/agent-skills-standard/system-design-session/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/hoangnguyen0403/agent-skills-standard/system-design-session"><img src="https://agentmods.dev/badge/skills/hoangnguyen0403/agent-skills-standard/system-design-session.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.01499 |
| Opus 5.5 | $0.00010 | $0.00600 |
| Sonnet 5.5 | $0.00005 | $0.00300 |
| Haiku 4.5 | $0.00003 | $0.00150 |
Grade A, and why
system-design-session 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 6d 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.
System Design Session Skill
[!IMPORTANT] Run an interactive system design session that turns a product goal into a scoped, evidence-qualified architecture and handoff.
Optional args: slug=, ticket=<id/url>, mode=interactive|autonomous|channel, channel=, auto_continue=true|false, profile=business|hybrid|technical.
Instructions
When the user asks to perform this workflow, execute the following steps:
System Design Workflow
Goal
Goal: Produce an evidence-qualified system design and handoff to design-solution, holding unresolved material decisions and distinguishing design readiness from implementation or operations.
Steps
- Load context. Read the product goal and relevant architecture. Review-existing mode uses current traffic/incident evidence when available. Load
system-design-methodologyand only relevant siblings:system-design-data-architecturefor consequential flows,system-design-mobile-clientfor client/SDK concerns, andcommon-architecture-diagrammingonly for a selected view. - Classify independently. State mode (new design | review existing | interview practice), depth (quick | full), and surface (backend | mobile/client | SDK/library | full stack; mixed may name multiple). Quick uses labeled assumptions; full confirms consequential gates. Escalate quick for hard constraints or irreversible choices. Interview practice follows
system-design-interview-coaching; the candidate designs, then receives the practice loop and six-criterion debrief. - Intake and estimate. Follow
system-design-methodology/references/four-phase-process.mdexit predicates. Bound intake to journeys, scope, inputs/outputs, trust/ownership boundaries, quality scenarios (trigger, environment, response, measure, owner), and assumptions. Ask at most 3 blocking questions per turn. Estimate only decision-relevant quantities; label target/estimated/measured and provenance. Confirm material scope and shaping estimates before physical choices in full sessions. - Trace before binding. Describe each consequential journey logically: source/sink, payload/purpose, transformations, authoritative owner/derived copies, invariant, user-visible outcomes, verification. Use
system-design-data-architecture/references/flow-contracts.md; do not duplicate C1. Bind accepted decisions to physical components/stores/contracts afterward. Link applicableFLOW-*design records throughREQ-* -> HLD-* -> CMP-* -> LLD-* -> VER-*;FLOW-*is not an outcome field. - Select views and deep dives conditionally. Choose zero or more from the named question, risk, surface, and time. Dataflow explains movement/authority; sequence ordering/acknowledgment; state lifecycle; ERD relationships; deployment placement. Prose/table is sufficient. No component, queue, store, specialist, or diagram quota. Practice uses commitment -> adverse timeline -> mechanism revision -> changed constraint -> evidence-based debrief.
- Hold material decisions. Full sessions do not commit affected design or claim readiness while a material owner/invariant, compliance/residency, or topology-changing budget decision remains unresolved. Record it in
decision_needed; preserve other gaps inmissing_evidence. Quick sketches may proceed with explicit assumptions, never false readiness. - Score and hand off. Run the declared-profile, scope-aware nine-axis
system-design-reviewscorecard and independentsystem-design-review/references/semantic-evaluation.md. Use applicable denominators and justifiedN/A. Semantic soundness requires >=85%, no applicable zero, and no hard failure; any failed material gate blocks readiness regardless of aggregate. The six-criterion interview rubric is separate. Preserve existing outcome fields/statuses; design evidence does not prove implementation or operations. - Prepare warranted delivery slices. Only when independent post-decision docs/diagram slices are warranted, define exact files, AC, evidence, checks, and integrator before execution. Use configured project/account/data-eligible routing; lead retains decisions/final review. Allow one focused correction, then configured eligible fallback or
BLOCKED. Disclose executor/model/settings, correction/fallback, and actual usage/cost orunavailable. This gate grants no model/provider execution authorization, including premium execution; workers must not change policy/profile settings, invoke unapproved model execution, or claim unrun checks.
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.
- 6d ago Changed · -11 lines · -12 tokens per session 6b7a5e4d2dc6
- 19d ago Changed eaf290bda91c
- 26d ago Changed · +2 lines 9f17731e65d1
- 28d ago Changed · +1 lines 7915e2085094
- 1mo ago Changed · -2 lines 4e069a0f4996
- 1mo ago Changed · +4 lines 3248b0f2d196
- 1mo ago Changed · +2 lines 25812530c9df
- 1mo ago First seen · 101 lines · 38 tokens per session scan A 86b5d2a0e332
system-design-session is a skill published in the GitHub repository HoangNguyen0403/agent-skills-standard (582 stars, last pushed today), licensed MIT. It adds 26 tokens to every session and 1,499 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 2026-09-03.
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