Borrowing it
Nothing to install: this file belongs to dungnotnull/spatial-navigation-memory-coach-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/spatial-navigation-memory-coach-agent-skill/main/CLAUDE.mdgit clone --depth 1 https://github.com/dungnotnull/spatial-navigation-memory-coach-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/spatial-navigation-memory-coach-agent-skill/claude-md)<a href="https://agentmods.dev/instructions/dungnotnull/spatial-navigation-memory-coach-agent-skill/claude-md"><img src="https://agentmods.dev/badge/instructions/dungnotnull/spatial-navigation-memory-coach-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/spatial-navigation-memory-coach-agent-skill/claude-md"><img src="https://agentmods.dev/badge/instructions/dungnotnull/spatial-navigation-memory-coach-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 | $0.01487 | $0.01487 |
| Opus 5.5 | $0.00595 | $0.00595 |
| Sonnet 5.5 | $0.00297 | $0.00297 |
| Haiku 4.5 | $0.00149 | $0.00149 |
Grade A, and why
spatial-navigation-memory-coach-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 1mo 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 — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md - Skill 181: spatial-navigation-memory-coach
Skill Identity
- Skill Name:
spatial-navigation-memory-coach - Tagline: Spatial Navigation & Memory Coach for People Prone to Getting Lost - Spatial Cognition & Navigation Memory Training analysis & decision-support harness.
- Current Phase: Phase 5 - Integration & Polish - PRODUCTION READY v1.0.0
- Folder:
181-spatial-navigation-memory-coach/
Problem This Skill Solves
This skill provides a structured, evidence-backed analytical workflow for Spatial Cognition & Navigation Memory Training. It gathers authoritative real-time and reference data, applies recognized domain methods, 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.
Harness Flow Summary
/spatial-navigation-memory-coach invoked
|
+- Step 1: sub-gather-requirements -> Clarify the object of analysis, constraints, timeframe, available inputs, target audience, and language before any data fetching.
+- Step 2: sub-evidence-collector -> Fetch authoritative real-time and reference data for the object: current status/parameters, authoritative documents/standards, and recent developments from domain and academic sources.
+- Step 3: sub-core-analysis -> Design a personalized spatial-navigation and memory training program for people prone to getting lost, grounded in hippocampal/visuospatial research and real-world navigation drills.
+- Step 4: sub-knowledge-updater -> Query SECOND-KNOWLEDGE-BRAIN.md for authoritative academic and professional evidence; surface citations with tier labels and flag gaps for the crawl pipeline.
+- Step 5: sub-advisor -> Synthesize all prior analysis into a risk-disclosed conclusion with a full evidence chain and recommended actions.
+- Step 6: main (quality gate) -> verify evidence hierarchy, disclosure, 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.
- 1mo ago First seen · 135 lines · 1,487 tokens per session scan A 8b901aa722a4
spatial-navigation-memory-coach-agent-skill CLAUDE.md is an instructions file published in the GitHub repository dungnotnull/spatial-navigation-memory-coach-agent-skill (5 stars, last pushed 3mo ago), licensed MIT. It adds 1,487 tokens to every session, about $0.0059 per session on Opus 5.5. 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.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
vscode model-prompts.instructions.md
Model-specific prompt authoring and registry guidelines.