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 instructions/nudt-sawlab/pilot/agents-mdgit clone --depth 1 https://github.com/nudt-sawlab/PiLoTWrote 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/nudt-sawlab/pilot/agents-md)<a href="https://agentmods.dev/instructions/nudt-sawlab/pilot/agents-md"><img src="https://agentmods.dev/badge/instructions/nudt-sawlab/pilot/agents-md.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 | $0.01239 | $0.01239 |
| Opus 5 | $0.00620 | $0.00620 |
| Sonnet 5 | $0.00248 | $0.00248 |
| Haiku 4.5 | $0.00124 | $0.00124 |
Grade A, and why
PiLoT AGENTS.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 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 — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — PiLoT agent guide
Instructions for AI coding assistants (Cursor, Claude Code, Codex, Windsurf, …) working in this repository.
What this repo does
PiLoT localizes a UAV camera from a query image + a geo-referenced 3D map.
Two processes run in parallel (main.py):
- Render worker — renders color + depth from the current pose estimate.
- Localization worker — refines pose via dense feature alignment (PixLoc).
Closed loop: localization output → next render pose → next frame.
Repo layout
main.py # entry point, dual-process orchestration
configs/demos/ # official YAML configs (start here)
pixloc/localization/ # refiner, feature extraction
pixloc/pixlib/models/ # learned optimizer (CUDA)
pixloc/utils/citygs/ # CityGaussian renderer
pixloc/utils/gs3d/ # vanilla 3DGS PLY renderer
pixloc/utils/osg/ # legacy OSG / 3D Tiles renderer
scripts/ # run & download helpers
data_demo/ # demo data (not in git; download from HF)
DirectAbsoluteCostCuda/ # build pose optimizer CUDA ext
Install (conda env: pilot)
Prerequisites: Linux, NVIDIA GPU, CUDA, conda.
git clone https://github.com/Choyaa/PiLoT.git && cd PiLoT
# CityGaussian (SMBU renderer) — also accepts ../CityGaussian if already cloned
git clone https://github.com/DekuLiuTesla/CityGaussian.git third_party/CityGaussian
cd third_party/CityGaussian
conda env create -f environment.yml -n pilot
conda activate pilot
cd ../..
pip install -r requirements.txt
cd DirectAbsoluteCostCuda && CUDA_HOME=/usr/local/cuda python setup_build.py install && cd ..
# Feicuiwan PLY renderer only:
pip install git+https://github.com/graphdeco-inria/diff-gaussian-rasterization.git
pip install git+https://github.com/graphdeco-inria/gaussian-splatting.git#subdirectory=submodules/simple-knn
Verify:
python -c "import direct_abs_cost_cuda, torch; print('ok', torch.__version__)"
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 · 134 lines · 1,239 tokens per session scan A f346a5e4dc2b
PiLoT AGENTS.md is an instructions file published in the GitHub repository nudt-sawlab/PiLoT (112 stars, last pushed 2mo ago), licensed MIT. It adds 1,239 tokens to every session, about $0.0062 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.
Other instructions, from other repositories
co-mathematician CLAUDE.md
Instructions for VeryMath/co-mathematician, covering claude.md, repository contract, required flow, claude code operating notes and harness commands.
SutroYaro GEMINI.md
Instructions for cybertronai/SutroYaro, covering gemini.md - sutro group research workspace, project context, read these first, core concepts and current best methods.
mcp-pubmed-server-pancrpal CLAUDE.md
Instructions for PancrePal-xiaoyibao/mcp-pubmed-server-pancrpal, covering claude.md, project overview, commands, architecture and mcp tools (8 total).
braina GEMINI.md
Instructions for brainets/braina, covering project: braina (brain interaction analysis), 1. project context & purpose, 2. commands, verify environment (all core dependencies) and run the verification test suite for frites + hoi.
cdxml-toolkit-community AGENTS.md
AGENTS.md instructions for ZiChenWang114514/cdxml-toolkit-community, a project described as: Community CDXML toolkit and MCP server.
research-automation CLAUDE.md
Instructions for lucafusarbassini/research-automation, covering ricet - research automation framework, project overview, claude-flow mcp, workflow habits and file organization.