Borrowing it
Nothing to install: this file belongs to dungnotnull/Military-Strategy-Advisor-agent-skill. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/dungnotnull/Military-Strategy-Advisor-agent-skill/main/CLAUDE.mdgit clone --depth 1 https://github.com/dungnotnull/Military-Strategy-Advisor-agent-skillWrote 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/instructions/dungnotnull/military-strategy-advisor-agent-skill/claude-md)<a href="https://agentmods.dev/instructions/dungnotnull/military-strategy-advisor-agent-skill/claude-md"><img src="https://agentmods.dev/badge/instructions/dungnotnull/military-strategy-advisor-agent-skill/claude-md/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/instructions/dungnotnull/military-strategy-advisor-agent-skill/claude-md"><img src="https://agentmods.dev/badge/instructions/dungnotnull/military-strategy-advisor-agent-skill/claude-md.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 | $0.01803 | $0.01803 |
| Opus 5 | $0.00901 | $0.00901 |
| Sonnet 5 | $0.00361 | $0.00361 |
| Haiku 4.5 | $0.00180 | $0.00180 |
Grade A, and why
Military-Strategy-Advisor-agent-skill CLAUDE.md 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 — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md — Skill 310: military-strategy-advisor
Skill Identity
- Skill Name:
military-strategy-advisor - Tagline: Military Strategy & Tactics Analysis — Ancient wisdom to modern warfare decision-support harness.
- Current Phase: Phase 6 — Beta Release (Field Testing Required)
- Version: 1.0.0-beta
- Folder:
D:\972026\310-chien-luoc-quan-su\
Problem This Skill Solves
This skill provides a structured, evidence-backed analytical workflow for Military Strategy & Tactics Analysis. It synthesizes wisdom from ancient military classics (Sun Tzu's Art of War, Zhuge Liang's strategies) with modern military leadership principles (General Vo Nguyen Giap, Ho Chi Minh, Napoleon Bonaparte) to deliver actionable strategic recommendations that are fully evidenced, historically-contextualized, and traceable to authoritative sources.
Harness Flow Summary
/military-strategy-advisor invoked
│
├─ Step 1: sub-gather-requirements → Clarify the strategic scenario (conflict type, terrain, force balance, objectives, constraints) and language before analysis.
├─ Step 2: sub-context-collector → Fetch historical context, geographical data, and relevant military precedents for the scenario.
├─ Step 3: sub-ancient-wisdom-analysis → Analyze the scenario through ancient military classics (Sun Tzu, Zhuge Liang, Warring States period) to extract timeless strategic principles.
├─ Step 4: sub-modern-strategy-analysis → Apply modern military theory and leadership principles (guerrilla warfare, people's war, maneuver warfare) to the scenario.
├─ Step 5: sub-comparative-analysis → Cross-reference ancient and modern approaches, identify convergent strategies and time-tested adaptations.
├─ Step 6: sub-knowledge-updater → Query SECOND-KNOWLEDGE-BRAIN.md for authoritative military strategy evidence; surface citations with tier labels and flag gaps for the crawl pipeline.
├─ Step 7: sub-strategy-synthesizer → Synthesize all prior analysis into a risk-disclosed strategic recommendation with full evidence chain and alternative scenarios.
└─ Step 8: main (quality gate) → verify evidence hierarchy, disclosure, historical accuracy, output polish
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 · 129 lines · 1,803 tokens per session scan A e73a97ec12d1
Military-Strategy-Advisor-agent-skill CLAUDE.md is an instructions file published in the GitHub repository dungnotnull/Military-Strategy-Advisor-agent-skill (5 stars, last pushed 1mo ago), licensed MIT. It adds 1,803 tokens to every session, about $0.0090 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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