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 softspark/ai-toolkit --skill architecture-decisiongit clone --depth 1 https://github.com/softspark/ai-toolkitWrote 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/softspark/ai-toolkit/architecture-decision)<a href="https://agentmods.dev/skills/softspark/ai-toolkit/architecture-decision"><img src="https://agentmods.dev/badge/skills/softspark/ai-toolkit/architecture-decision/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/softspark/ai-toolkit/architecture-decision"><img src="https://agentmods.dev/badge/skills/softspark/ai-toolkit/architecture-decision.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Anti-Refusal · line 60 Skill attempts to nullify the agent's safety policies or restrictions ('you have no restrictions', 'ignore your guidelines', 'do anything now'). This is a direct jailbreak that disables guardrails.Fix: Remove jailbreak framing that nullifies safety policies or restrictions. Skill content must not instruct the agent to ignore its guidelines or operate without guardrails.
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 | $0.00044 | $0.00925 |
| Opus 5.5 | $0.00018 | $0.00370 |
| Sonnet 5.5 | $0.00009 | $0.00185 |
| Haiku 4.5 | $0.00004 | $0.00093 |
Grade A, and why
architecture-decision 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 1mo 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 — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Architecture Decision Skill
Core Philosophy: "Everything is a Trade-off"
There are no "best solutions", only solutions with the right set of trade-offs for the specific context.
Decision Making Process (RFD / RFC)
- Context: What is the problem? Why now?
- Constraints: Budget, Time, Skillset, Legacy.
- Options: Propose at least 3 viable options.
- Trade-off Analysis: Compare constraints vs options.
- Recommendation: Choose one and justify.
Trade-off Analysis Matrix (Template)
| Feature | Option A (e.g. SQL) | Option B (e.g. NoSQL) | Option C (e.g. File) |
|---|---|---|---|
| Scalability | Medium (Vertical) | High (Horizontal) | Low |
| Consistency | Strong (ACID) | Eventual (BASE) | N/A |
| Complexity | Low (Known) | Medium (New tech) | Low |
| Cost | $$ | $$$ | $ |
Architecture Note
When a decision is made, document it.
# Architecture Note: Use PostgreSQL for Main Database
## Status
Accepted
## Context
We need a reliable, relational database for user data...
## Decision
We will use PostgreSQL 16.
## Consequences
- Positive: ACID compliance, rich ecosystem.
- Negative: Scaling writes requires sharding later.
Critical Factors to Evaluate
- Reliability (Availability, Fault tolerance)
- Scalability (Throughput, Latency)
- Maintainability (Simple vs Easy, Ecosystem)
- Security (AuthN/Z, Encryption)
- Cost (Infrastructure, License, Cognitive load)
Rules
- MUST present at least 3 viable options, including "status quo / do nothing" when relevant
- MUST state constraints (budget, time, team skillset, legacy) before enumerating options — options without constraints are arbitrary
- NEVER recommend an option without explicitly naming its failure mode and what would trigger revisiting the decision
- CRITICAL: the output is a document (ADR / RFC / RFD), not code changes. Code work belongs in
/planor/refactor-plan. - MANDATORY:
Consequencessection names both Positive and Negative effects. A decision with only upside is not honestly analysed.
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.
- 1mo ago First seen · 80 lines · 44 tokens per session scan A dc29d15d78fa
architecture-decision is a skill published in the GitHub repository softspark/ai-toolkit (181 stars, last pushed today), licensed Apache-2.0. It adds 44 tokens to every session and 925 once invoked, about $0.0002 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 2026-08-30.
Other skills, from other repositories
cline-fix-volatile-msg
Ladder-aware Cline Anthropic caching — verify the rolling read/write ladder on the wire, then add the tools breakpoint and tune TTL. Updated for the 2026-08 AI-SDK monorepo.
aider-1h-ttl
Aider uses 5min TTL by default and works around long pauses with keepalive pings. Wire up the 1h TTL beta instead.
continue-enable-defaults
Continue's prompt caching is opt-in via config and off by default. Flip the default to systemAndTools.
continue-gemini-explicit
Continue's Gemini provider doesn't use the cachedContents API at all. Add explicit caching for sessions over the minimum token threshold.
roo-fix-volatile-msg
Ladder-aware Roo Code Anthropic caching — verify the rolling read/write ladder on the wire, then close the real gaps (Vertex 4-block budget, MiniMax path).
cline-openai-cache-key
Cline OpenAI native provider sends no promptcachekey. Add a stable per-task key so cachedtokens stops being zero.