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 stanislavnianko/product-discovery-claude-skills --skill solution-architecturegit clone --depth 1 https://github.com/stanislavnianko/product-discovery-claude-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/stanislavnianko/product-discovery-claude-skills/solution-architecture)<a href="https://agentmods.dev/skills/stanislavnianko/product-discovery-claude-skills/solution-architecture"><img src="https://agentmods.dev/badge/skills/stanislavnianko/product-discovery-claude-skills/solution-architecture/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/stanislavnianko/product-discovery-claude-skills/solution-architecture"><img src="https://agentmods.dev/badge/skills/stanislavnianko/product-discovery-claude-skills/solution-architecture.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 | $0.00084 | $0.01930 |
| Opus 5 | $0.00042 | $0.00965 |
| Sonnet 5 | $0.00017 | $0.00386 |
| Haiku 4.5 | $0.00008 | $0.00193 |
Grade A, and why
solution-architecture 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 12d 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 — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Solution Architecture
Part of the discovery-phase skill pack ·
scopinggroup · readsscope-doc.md(runfeature-scopingfirst if missing) and feedsestimation.
Produces a discovery-grade architecture: enough detail to estimate effort, surface technical risks, and explain choices to the client — but not detailed design. Detailed design happens in delivery, not here. Where the BA isn't a tech lead, this skill is best run pair-mode with an architect; otherwise it produces vague boxes-and-arrows.
Step 1 — Read context + scope
Read discovery-context.md (sections 2. Product / Initiative, 6. Constraints, 7. Tech Context), then scope-doc.md (or mvp-definition.md if MVP track), then risk-assumption-map.md.
If scope-doc.md is missing, recommend feature-scoping first — architecture without a defined scope drifts into "general platform" territory and stops being useful for estimation.
If discovery-context.md is missing, ask inline: "(a) any client-mandated tech constraints (cloud, language, vendor)? (b) integration list — what must this connect to? (c) team's existing stack expertise?" — tag unknowns [ASSUMED].
Step 2 — System context (one diagram, in text)
Write a single system context diagram in text or Mermaid: the system in the middle, actors on one side, external systems on the other. This is the C4 "Level 1" view — no internals.
flowchart LR
user[End User]
admin[Admin]
system[<<system under discovery>>]
payment[Payment Provider]
crm[Client CRM]
user --> system
admin --> system
system --> payment
system --> crm
Explicitly state what's out of scope for this system (e.g., "billing UI is consumed from existing client portal, not built here"). Out-of-scope boundaries are where most estimation surprises hide.
Step 3 — Logical components (3-7)
Decompose the system into 3-7 logical components — single-responsibility boxes. For each:
- Name —
<component>(e.g.,auth-service,event-ingestion,report-generator) - Responsibility — one sentence, one job
- Owns data? — yes / no / shared
- Talks to — which other components / external systems
- New or existing? — building from scratch / extending existing client component / adopting a library
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.
- 12d ago First seen · 145 lines · 84 tokens per session scan A eeba6a051b67
solution-architecture is a skill published in the GitHub repository stanislavnianko/product-discovery-claude-skills (1 stars, last pushed 4mo ago), licensed MIT. It adds 84 tokens to every session and 1,930 once invoked, about $0.0004 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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