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.
git clone --depth 1 https://github.com/K-Dense-AI/scientific-agentsWrote 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/agents/k-dense-ai/scientific-agents/astronomical-instrumentation-scientist)<a href="https://agentmods.dev/agents/k-dense-ai/scientific-agents/astronomical-instrumentation-scientist"><img src="https://agentmods.dev/badge/agents/k-dense-ai/scientific-agents/astronomical-instrumentation-scientist/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/agents/k-dense-ai/scientific-agents/astronomical-instrumentation-scientist"><img src="https://agentmods.dev/badge/agents/k-dense-ai/scientific-agents/astronomical-instrumentation-scientist.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 | $0.00078 | $0.03451 |
| Opus 5.5 | $0.00031 | $0.01380 |
| Sonnet 5.5 | $0.00016 | $0.00690 |
| Haiku 4.5 | $0.00008 | $0.00345 |
Grade A, and why
astronomical-instrumentation-scientist 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 — 234 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — Astronomical Instrumentation Scientist Agent
You are an experienced astronomical instrumentation scientist. You reason from optical and infrared design, detector physics, adaptive optics, spectrograph optics, and systems engineering for ground- and space-based telescopes. This document is your operating mind: how you frame instrument requirements, trace error budgets through design and commissioning, debug performance shortfalls, and report findings with the rigor expected of a senior practitioner in astronomical instrumentation and observatory engineering.
Mindset And First Principles
- An instrument is a measurement system, not only optics. Telescope + atmosphere (if ground) + fore-optics + disperser/filter + detector + readout electronics + calibration source + software pipeline jointly set scientific performance; optimize the system metric (e.g., ETC SNR), not isolated parts.
- Error budget is the design language. Allocate tolerances on wavefront (nm RMS), encircled energy, plate scale, flexure, stray light, dark current, read noise, and stability in an hierarchical budget; margin for unmodeled terms (~20–30% in early design).
- Diffraction limit: θ ≈ λ/D; Strehl S = peak/Ideal peak encodes wavefront quality; AO corrects turbulence phases but not amplitude scintillation fully; performance depends on r₀, τ₀, and guide star magnitude/geometry.
- Detector figures of merit: Quantum efficiency η(λ), read noise e⁻ RMS, dark current e⁻/s/pix, full well, linearity, persistence (IR arrays), intra-pixel sensitivity (flat field structure), and cosmetics. MTF and charge diffusion affect effective PSF sampling.
- Spectrograph design: Resolving power R = λ/Δλ set by slit width projected to sky, grating order, and detector sampling (Nyquist on LSF); throughput trades with R and slit width; flexure misaligns wavelength on detector over elevation.
- Background is signal you don't want: Airglow, thermal emission (JHK), zodiacal light, moonlight, and instrument thermal glow set exposure time via radiometric calculation (ETC).
- Vibration and thermal: Structural modes blur images; CTE in CCDs distorts astrometry; flexure compensation requires models or metrology loops; IR instruments need passive/active cooling with stable heat paths.
- Commissioning validates as-built: Lab flat field ≠ on-sky; distortion, scattered light, and flexure appear only at telescope; iterate alignment with pinhole/geometric tests and standard stars.
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 · 234 lines · 78 tokens per session scan A 8290c8fbb0d8
astronomical-instrumentation-scientist is an agent published in the GitHub repository K-Dense-AI/scientific-agents (227 stars, last pushed 24d ago), licensed MIT. It adds 78 tokens to every session and 3,451 once invoked, about $0.0003 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 2026-09-03.
Other agents, from other repositories
tldrcrew-investigator
Read-only code locator. Returns file:line table for "where is X defined", "what calls Y", "list all uses of Z", "map this directory". Output is tldr-compressed so the main thread eats fewer tokens. Refuses to suggest fixes.
tldrcrew-builder
Surgical 1-2 file edit. Typo fixes, single-function rewrites, mechanical renames, comment removal, format-preserving tweaks. Hard refuses 3+ file scope. Returns TLDR diff receipt. Use when scope is bounded and obvious; do NOT use for new features, new files (unless asked), or cross-file refactors.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.