Borrowing it
Nothing to install: this file belongs to dungnotnull/water-rescue-drone-design-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/water-rescue-drone-design-agent-skill/main/CLAUDE.mdgit clone --depth 1 https://github.com/dungnotnull/water-rescue-drone-design-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/water-rescue-drone-design-agent-skill/claude-md)<a href="https://agentmods.dev/instructions/dungnotnull/water-rescue-drone-design-agent-skill/claude-md"><img src="https://agentmods.dev/badge/instructions/dungnotnull/water-rescue-drone-design-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/water-rescue-drone-design-agent-skill/claude-md"><img src="https://agentmods.dev/badge/instructions/dungnotnull/water-rescue-drone-design-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 | $0.01333 | $0.01333 |
| Opus 5 | $0.00666 | $0.00666 |
| Sonnet 5 | $0.00267 | $0.00267 |
| Haiku 4.5 | $0.00133 | $0.00133 |
Grade A, and why
water-rescue-drone-design-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 10d 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 — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md — Skill 244: water-rescue-drone-design
Skill Identity
- Skill Name:
water-rescue-drone-design - Tagline: Water-Rescue Drone Design & Testing — Search-and-Rescue Drone Engineering for Water evidence-backed analysis harness.
- Current Phase: Phase 5 — Integration & Polish (PRODUCTION READY v1.1.0)
- Folder:
D:\972026\244-water-rescue-drone-design\
Problem This Skill Solves
This skill provides a structured, evidence-backed analytical workflow for Search-and-Rescue Drone Engineering for Water. It gathers authoritative real-time and reference data, applies recognized domain methods (energy budget, search theory, reliability/certification), cross-references academic research, and delivers actionable outputs that are fully evidenced, risk/limitation- disclosed, and traceable to authoritative sources — continuously self-improving through an automated knowledge crawl pipeline.
Two Coordinated Layers
- Prompt layer —
skills/*.md(this skill's specification) +SECOND-KNOWLEDGE-BRAIN.md. - Code layer —
water_rescue_drone/(the runnable Python harness). Both layers must agree;tools/validate_project.pyenforces this.
Harness Flow Summary
/water-rescue-drone-design invoked (or: python -m water_rescue_drone "<query>")
|
|-- Step 1: sub-gather-requirements -> Requirements
|-- Step 2: sub-evidence-collector -> EvidenceItem[]
|-- Step 3: sub-core-analysis -> CoreAnalysis (G1-G4 data)
|-- Step 4: sub-knowledge-updater -> KnowledgeCitation[] + gaps
|-- Step 5: sub-advisor -> AdvisorConclusion (verdict)
`-- Step 6: main (quality gate) -> verify U1-U6 + G1-G4, render report
Implementation: water_rescue_drone/agent.py::WaterRescueDroneAgent.
Sub-Skills
| skills/sub-gather-requirements.md | Clarify object/scope/timeframe/inputs/language before fetching. |
| skills/sub-evidence-collector.md | Fetch authoritative real-time + reference data. |
| skills/sub-core-analysis.md | Design payload/sensors/endurance/path/reliability. |
| skills/sub-knowledge-updater.md | Surface academic citations with tiers + flag gaps. |
| skills/sub-advisor.md | Synthesize risk-disclosed conclusion + evidence chain. |
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.
- 10d ago First seen · 134 lines · 1,333 tokens per session scan A ae93264f742e
water-rescue-drone-design-agent-skill CLAUDE.md is an instructions file published in the GitHub repository dungnotnull/water-rescue-drone-design-agent-skill (5 stars, last pushed 1mo ago), licensed MIT. It adds 1,333 tokens to every session, about $0.0067 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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