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 deciqAI/knowledge-skills --skill latticeworkgit clone --depth 1 https://github.com/deciqAI/knowledge-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/deciqai/knowledge-skills/latticework)<a href="https://agentmods.dev/skills/deciqai/knowledge-skills/latticework"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/latticework/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/deciqai/knowledge-skills/latticework"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/latticework.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 109 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 | $0.00120 | $0.01544 |
| Opus 5 | $0.00060 | $0.00772 |
| Sonnet 5 | $0.00024 | $0.00309 |
| Haiku 4.5 | $0.00012 | $0.00154 |
Grade A, and why
latticework 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 9d 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 — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Latticework
Overview
Latticework is the practice of cross-wiring mental models from multiple disciplines on the same situation. Power comes from inter-connection: independent lenses converging = high-confidence signal; lenses diverging = unknown to investigate. When multiple forces align simultaneously they amplify — the lollapalooza effect (Munger, 1994). Composes with first-principles, second-order-thinking, probabilistic-thinking, and map-is-not-the-territory.
When to Use
- Stakeholders keep raising non-overlapping objections — each is right from their model
- Post-mortem shows failure was "outside the model we used"
- "Our analysis is solid" — but only one framework was applied
- Situation looks like a classic X but has anomalous features X cannot explain
- Designing a strategy/product where market, psychology, operations, and incentives all interact
- Judging an AI-boom / AI-adoption / AI-hype bet where "is it a bubble?" and "is it real?" are being argued through one lens each
Not when: problem is contained in one discipline; crisis triage (no time); decision too small for multi-model overhead.
Coaching Novices (Adaptive Front Door)
- Engine mode: user has a concrete case → run The Process directly.
- Coach mode: user is unfamiliar → guide step by step.
In Coach mode, respond one step at a time. Each [WAIT] is a hard stop — output only that step's question, then stop.
- One-liner: facts don't become knowledge until they hang on a latticework of theory (Munger's rule #1).
- Check fit: has one model already failed or felt incomplete? If yes, proceed.
- Elicit: what models applied so far? What disciplines are missing?
[WAIT — do not advance until user responds]
- Run The Process one step at a time with their input.
[WAIT — do not advance until user responds]
What ships with it
3 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.
- 9d ago First seen · 126 lines · 120 tokens per session scan A f41d5f5a4569
latticework is a skill published in the GitHub repository deciqAI/knowledge-skills (10 stars, last pushed 10d ago), licensed MIT. It adds 120 tokens to every session and 1,544 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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