Borrowing it
Nothing to install: this file belongs to mstr-sharma/strategy-automate. 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/mstr-sharma/strategy-automate/main/AGENTS.mdgit clone --depth 1 https://github.com/mstr-sharma/strategy-automateWrote 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/mstr-sharma/strategy-automate/agents-md)<a href="https://agentmods.dev/instructions/mstr-sharma/strategy-automate/agents-md"><img src="https://agentmods.dev/badge/instructions/mstr-sharma/strategy-automate/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 5.1 | $0.03183 | $0.03183 |
| Opus 5 | $0.01591 | $0.01591 |
| Sonnet 5 | $0.00637 | $0.00637 |
| Haiku 4.5 | $0.00318 | $0.00318 |
Grade A, and why
strategy-automate 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 6d 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 — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — canonical, LLM-agnostic entry point
You are operating inside the strategy-automate repo: a one-stop automation brain for Strategy (formerly MicroStrategy) that aims for complete platform automation wherever Strategy exposes an API, SDK, MCP, CLI, or reproducible hook. It covers Mosaic semantic models, the classic / legacy semantic layer, runtime analytics, cubes / datasets, platform admin, AI agents, and data validation.
This file is the canonical cross-tool entry point. Every LLM-specific shim at the repo root (CLAUDE.md, GEMINI.md, CODEX.md, GROK.md, OLLAMA.md, CURSOR.md, etc.) points here. If you are a model or tool not listed there, read this file + memory/MEMORY.md and proceed — nothing else is tool-specific.
Harness assumptions (apply across LLMs):
- The repo is plain Markdown + Python 3 (standard library +
requests). No Anthropic-specific, OpenAI-specific, or Google-specific SDK calls — every helper isrequestsagainst Strategy REST or subprocess tomstrio-py. SKILL.mdfrontmatter (name,description) follows Anthropic's skill convention, but any harness that reads Markdown with YAML frontmatter can use it. A skill-unaware LLM can read eachSKILL.mdas a normal instruction file.memory/MEMORY.mdis a flat index with one-line hooks; any LLM cangrepor keyword-match to find the relevant memory file on demand.- Shell helpers live in
skills/build-mosaic-model/scripts/. Invoke them via whatever tool-call mechanism your harness exposes (Bash, shell, execute_command, tool-use-bash, etc.). - Credentials come from env vars (
MSTR_BASE,MSTR_USER,MSTR_PASSWORD,MSTR_PROJECT_ID/MSTR_PROJECT_NAME,MSTR_DEST_FOLDER_ID) — seememory/reference_strategy_env.md. Never hardcode.
Git workflow
- Operator configures their own remotes and git identity locally (
git remote -v,git config user.email) — do not hardcode remote URLs or identities here. - Default pull/push targets
origin. Rungit pull --ff-onlybefore starting shared work andgit pushafter commit. - Before committing, run the relevant tests plus
git diff --check. - Never commit
.env,.claude/, credentials, SSH keys, tenant IDs, raw tenant payloads, personal names, corporate email addresses, local logs, or anything else enumerated inmemory/feedback_generalize_durable_artifacts.md.
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.
- 6d ago First seen · 122 lines · 3,183 tokens per session scan A cd61e3ca1707
strategy-automate AGENTS.md is an instructions file published in the GitHub repository mstr-sharma/strategy-automate (2 stars, last pushed 2d ago), licensed MIT. It adds 3,183 tokens to every session, about $0.0159 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.
Other instructions, from other repositories
vibe-coding-prompt-template backend.instructions.md
Instructions for KhazP/vibe-coding-prompt-template: Read AGENTS.md, agentdocs/techstack.md, and agentdocs/codepatterns.md.
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.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
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).
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
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.