SpatialAI_MCP: Instructions file for Codex

AGENTS.md

SpatialAI_MCP AGENTS.md is an instructions file for Codex, OpenCode from Rebell-Leader/SpatialAI_MCP. It costs 1,373 tokens per session, scanned A, original, Apache-2.0.

Project instructions for an OpenProblems co-pilot focused on spatial transcriptomics, a method for measuring gene activity at locations within tissue. They describe the project, its available tools, domain rules, and coding standards.

In plain words
What is it for?
Use them when working on the MCP server, skill installer, or spatial-transcriptomics validation and analysis workflows in this repository.
Why use it?
They give coding agents the project's ground truth, including which tools exist and that the analysis server is read-only.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md. Also seen: mentions CLAUDE.md; mentions Claude Code; mentions AGENTS.md.

This is Rebell-Leader/SpatialAI_MCP's own configuration. It tells Codex and OpenCode how to work on SpatialAI_MCP itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything SpatialAI_MCP configures →

Reuse

Borrowing it

Nothing to install: this file belongs to Rebell-Leader/SpatialAI_MCP. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/Rebell-Leader/SpatialAI_MCP/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/Rebell-Leader/SpatialAI_MCP

Made for: Codex, OpenCode.

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README.md
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Per session 1,373 This file is loaded in full into every session.
When invoked 1,373 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.01373 $0.01373
Opus 5 $0.00687 $0.00687
Sonnet 5 $0.00275 $0.00275
Haiku 4.5 $0.00137 $0.00137

Measured 7d ago against content hash 946ffac560a4, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

SpatialAI_MCP 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 7d 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.

AGENTS.md · 106 lines

How it starts

The opening of the file, as written. The whole thing — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md — OpenProblems Spatial Transcriptomics Co-pilot

Canonical, provider-neutral instructions for any AI coding agent working in this repository (Claude Code, OpenAI Codex, Cursor, GitHub Copilot, and others). This is the single source of truth. Tool-specific files (CLAUDE.md, .cursor/rules/, .github/copilot-instructions.md) are generated from this file and the skills/ directory by installer/ — do not edit them by hand.

What this project is

A co-pilot for computational biologists working on the OpenProblems spatial transcriptomics benchmarks. It ships two things:

  1. An MCP server (src/openproblems_mcp/) — domain-aware validation and analysis tools for spatial data and bioinformatics workflows, exposed over the Model Context Protocol so any MCP-capable agent can call them.
  2. A provider-agnostic skill installer (skills/, context/, installer/) — author rules/skills/context once here, then project them into whichever agent the user runs.

Ground truth: which MCP tools actually exist

Only call tools that are registered. As of now the server is read-only analysis — it validates and inspects, it does not execute pipelines.

Available now: health_check, list_tools_status, get_server_info, validate_spatial_data, validate_multiple_spatial_files, analyze_spatial_metadata, check_spatial_data_compatibility, extract_bioinformatics_metadata, analyze_workflow_configuration, assess_data_quality, analyze_workflow_dependencies.

Roadmap — NOT implemented, do not call: run_nextflow_workflow, run_viash_component, build_docker_image, run_nf_test, analyze_nextflow_log, create_spatial_component, setup_spatial_environment, and the OpenProblems build/benchmark/submission tools. For these actions, drive the user's local nextflow / viash / docker CLIs directly via the terminal instead, and say so plainly.

Domain rules (spatial transcriptomics)

Read the full file on GitHub · 106 lines

Changes

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.

  1. 7d ago First seen · 106 lines · 1,373 tokens per session scan A 946ffac560a4

Subscribe to this mod's changes

SpatialAI_MCP AGENTS.md is an instructions file published in the GitHub repository Rebell-Leader/SpatialAI_MCP (4 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 1,373 tokens to every session, about $0.0069 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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