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 majiayu000/spellbook --skill architecture-researchgit clone --depth 1 https://github.com/majiayu000/spellbookWrote 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/majiayu000/spellbook/architecture-research)<a href="https://agentmods.dev/skills/majiayu000/spellbook/architecture-research"><img src="https://agentmods.dev/badge/skills/majiayu000/spellbook/architecture-research/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/majiayu000/spellbook/architecture-research"><img src="https://agentmods.dev/badge/skills/majiayu000/spellbook/architecture-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
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 →
- medium Excessive Agency · line 211 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00126 | $0.02203 |
| Opus 5 | $0.00063 | $0.01102 |
| Sonnet 5 | $0.00025 | $0.00441 |
| Haiku 4.5 | $0.00013 | $0.00220 |
Grade A, and why
architecture-research 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 8d 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 — 236 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Architecture Research
Understand how real systems work before committing to a technical direction. Produce a decision artifact backed by inspectable evidence, not a feature table, vendor narrative, or speculative target architecture.
Read both references before completing decision-grade work:
- Architecture lenses explains how to inspect ownership, authority, wiring, lifecycle, recovery, trade-offs, and adoption risk.
- Evidence matrix and decision template provides the output structure.
Operating Contract
- Direct actions: read-only discovery, source inspection, local experiments, decision recovery, comparison, and drafting within the requested access path.
- Escalate before: paid API use, new accounts or legal terms, publication of non-public findings, remote mutations, or an unauthorized production choice.
- Evidence-backed pushback: challenge category errors, unsupported architecture claims, false equivalence, and premature hyperscale design with cited facts.
- Feedback loop: test decisive claims, record unknowns and reversal evidence, then re-open the decision when its review trigger fires.
Scope and handoff
Use this skill for four related tasks:
- Landscape research: identify and compare relevant systems or approaches.
- System archaeology: reconstruct how a system actually works from source, deployment material, tests, runtime evidence, and authoritative documents.
- Architecture decision: choose whether to adopt, adapt, build, defer, or retain the current system.
- Decision reassessment: recover an earlier decision, check whether its assumptions still hold, and keep or revise it using current evidence.
This skill owns external research, evidence, comparison, and the decision
boundary. Once a direction is selected, hand detailed internal boundaries,
contracts, and target architecture to architecture-foundation. Use
product-discovery for customer or market validation without a technical
decision question.
What ships with it
2 files 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.
- 8d ago First seen · 236 lines · 126 tokens per session scan A 67ab4a9415e8
architecture-research is a skill published in the GitHub repository majiayu000/spellbook (278 stars, last pushed today), licensed MIT. It adds 126 tokens to every session and 2,203 once invoked, about $0.0006 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 2026-09-03.
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