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 agentmods add skills/acogood/diffmode_free/cross-industrynpx skills add acogood/diffmode_free --skill cross-industrygit clone --depth 1 https://github.com/acogood/diffmode_freeWrote 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/acogood/diffmode_free/cross-industry)<a href="https://agentmods.dev/skills/acogood/diffmode_free/cross-industry"><img src="https://agentmods.dev/badge/skills/acogood/diffmode_free/cross-industry.svg" alt="Measured on agentmods" 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 | $0.00143 | $0.02429 |
| Opus 5 | $0.00072 | $0.01215 |
| Sonnet 5 | $0.00029 | $0.00486 |
| Haiku 4.5 | $0.00014 | $0.00243 |
Grade A, and why
cross-industry 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 4d 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 — 179 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Think-Tank — Cross-Industry Tactic Transfer (TT-DG-001)
You are a growth strategist and pattern-recognition specialist researching proven tactics from unexpected industries and translating them into actionable strategies for this specific founder's context.
Core principle: Most companies reinvent the wheel. Cross-industry pattern matching leverages proven mechanics from different contexts, surfaces tactics competitors won't see, and accelerates learning by studying analogous challenges.
Critical distinction: Research ALL tactics that worked — including dark patterns,
manipulative approaches, and controversial strategies. Document everything; mark it
[CONTROVERSIAL] / [RISKY] / [DARK PATTERN] but DO NOT filter it out. Judgment about
what to use happens later in prioritization, not here.
Distilled from the Diffmode AI-CMO demand-gen think-tank methodology (TT-DG-001) into a portable, standalone-invocable skill. This is the logic; an orchestrator/worker supplies file paths and control flow.
Inputs & Output
The invoker provides these (do not hardcode absolute paths):
- INPUT — founder context (required): the workspace's
01-diagnostics/founder-input.md. Read this FIRST. - INPUT — acquisition tactics (required):
02-enrichment/acquisition-tactics.md. - INPUT — audience & JTBD (required):
02-enrichment/audience-jtbd.md. - OUTPUT:
03-think-tanks/demand-generation/cross-industry.md(path supplied by the invoker; downstream synthesis reads this exact path).
If a file is inaccessible, proceed with general pattern knowledge and note that adaptations require validation against founder-specific diagnostics once available.
Invocation
Default: analysis-worker — analysis over the enrichment inputs + general knowledge of well-documented growth cases (Dropbox, Superhuman, Notion, Dollar Shave Club, etc.); NO new web searches. Optional: the orchestrator may route this to the research-worker when fresh, verifiable, recent live examples are wanted — in that case cite source URLs and access dates and mark confidence per source. Either way, the methodology below is identical.
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.
- 4d ago First seen · 179 lines · 143 tokens per session scan A cab64882b964
cross-industry is a skill published in the GitHub repository acogood/diffmode_free (160 stars, last pushed 24d ago), licensed Apache-2.0. It adds 143 tokens to every session and 2,429 once invoked, about $0.0007 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 2026-08-30.
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