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/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/rules/mstr-sharma/strategy-automate/strategy-automation)<a href="https://agentmods.dev/rules/mstr-sharma/strategy-automate/strategy-automation"><img src="https://agentmods.dev/badge/rules/mstr-sharma/strategy-automate/strategy-automation/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/rules/mstr-sharma/strategy-automate/strategy-automation"><img src="https://agentmods.dev/badge/rules/mstr-sharma/strategy-automate/strategy-automation.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 | $0.00370 | $0.00370 |
| Opus 5.5 | $0.00148 | $0.00148 |
| Sonnet 5.5 | $0.00074 | $0.00074 |
| Haiku 4.5 | $0.00037 | $0.00037 |
Grade A, and why
strategy-automation 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 28d 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.
What it actually says
This workspace is the strategy-automate repo. Read AGENTS.md for the full agent brief. Highlights:
- Surfaces covered: Mosaic data models, classic / legacy semantic layer, runtime analytics, cubes/datasets, admin platform, AI agents, data validation.
- Platform goal: complete automation coverage wherever Strategy exposes an API, SDK, MCP, CLI, or reproducible hook. Classify gaps using
memory/reference_strategy_automation_coverage.md. - Skill surfaces and the strict precedence chain (classify → plan → execute → verify) are enumerated in
AGENTS.md→ "Cold-start routing" — that list is authoritative; do not rely on a copy here. - Durable knowledge indexed at
memory/MEMORY.md— load files on demand. - Tenant values come from env vars (
MSTR_BASE,MSTR_PROJECT_ID/MSTR_PROJECT_NAME,MSTR_DEST_FOLDER_ID); sign-in fromMSTR_AUTH_METHOD(MSTR_USER/MSTR_PASSWORD,MSTR_API_TOKEN, or browsersso). Never hardcode, and never pass secrets as flags. - Consumer-grade naming + paired-query validation are part of the ship bar. Validation is comparator-dependent; if no trusted comparator exists yet, mark it pending instead of calling the build shippable. See
memory/feedback_mosaic_ship_bar.mdandmemory/reference_strategy_data_validation.md. - MCP tools (
get_projects,get_models— older serversget_mosaic_models—get_semantics,query) configured separately through your Cursor MCP settings. This repo references them by name only.
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.
- 28d ago Changed · +36 tokens per session a22fc51fa453
- 2mo ago First seen · 15 lines · 334 tokens per session scan A d4801ee511e4
strategy-automation is a cursor rule published in the GitHub repository mstr-sharma/strategy-automate (2 stars, last pushed 5d ago), licensed MIT. It adds 370 tokens to every session, about $0.0015 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.
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