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strategy-automation

strategy-automation is a skill for Claude Code, Codex from mstr-sharma/strategy-automate. It costs 100 tokens per session (3,387 once invoked), scanned A, original, MIT.

An automation helper for Strategy, formerly called MicroStrategy, a platform for building reports, dashboards, and governed business data models. It turns natural-language requests into work across Strategy’s available interfaces.

In plain words
What is it for?
Use it to inspect or change data models, reports, dashboards, datasets, security settings, users, subscriptions, migrations, monitoring, and other Strategy platform tasks.
Why use it?
It reduces the need to manually navigate Strategy administration and data tools or write each API request yourself. When no supported connection exists, it reports that gap instead of guessing.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is python3 skills/build-mosaic-model/scripts/build_mosaic.py openapi-search "<term>" --context 2.

not rated 2repo 6d ago A scan 100 tokens original MIT

Good fit Use it to inspect or change data models, reports, dashboards, datasets, security settings, users, subscriptions, migrations, monitoring, and other Strategy platform tasks.

Compare 6 skills from other repositories ↓
View source ↗ mstr-sharma/strategy-automate
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/mstr-sharma/strategy-automate
agentmods
npx agentmods add skills/mstr-sharma/strategy-automate/strategy-automation

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for strategy-automation

README.md
[![agentmods](https://agentmods.dev/badge/skills/mstr-sharma/strategy-automate/strategy-automation/github.svg)](https://agentmods.dev/skills/mstr-sharma/strategy-automate/strategy-automation)
Your own site
<a href="https://agentmods.dev/skills/mstr-sharma/strategy-automate/strategy-automation"><img src="https://agentmods.dev/badge/skills/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.

agentmods 80×15 button for strategy-automation

Your own site · 80×15
<a href="https://agentmods.dev/skills/mstr-sharma/strategy-automate/strategy-automation"><img src="https://agentmods.dev/badge/skills/mstr-sharma/strategy-automate/strategy-automation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 100 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,387 The whole file, excluding the scripts and references it only reads on demand.
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 $0.00100 $0.03387
Opus 5 $0.00050 $0.01693
Sonnet 5 $0.00020 $0.00677
Haiku 4.5 $0.00010 $0.00339

Measured 11d ago against content hash 24a9a635f7a6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

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 11d 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.

skills/strategy-automation/SKILL.md · 115 lines

How it starts

The opening of the file, as written. The whole thing — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Strategy Automation

Use this skill when the user asks to automate, inspect, build, modify, secure, publish, query, migrate, monitor, or administer anything in Strategy / MicroStrategy. The coverage goal is platform-wide automation wherever Strategy exposes an API, SDK, MCP, CLI, or reproducible hook; when no hook is verified, state the gap instead of improvising.

First Move

  1. Read $REPO/memory/MEMORY.md.
  2. Identify the task family in $REPO/memory/reference_strategy_automation_playbook.md.
  3. Read $REPO/memory/reference_strategy_automation_coverage.md for broad or audit-style requests, then classify coverage as wrapped helper, generic REST hook, specialized hook, captured fallback, or known gap.
  4. Decide the product surface before choosing endpoints: classic project semantic layer/admin, Mosaic data model, runtime analytics, Push Data dataset, cube family, platform admin, or AI/agents. Read reference_strategy_surface_matrix.md for ambiguous attributes, metrics, prompts, filters, ACLs/object security, security filters, cubes, datasets, reports, dashboards, documents, users/groups, agents, or project-level requests.
  5. Use live {Library}/api/openapi.yaml through the helper when endpoint details matter. Add ?visibility=all when the Swagger UI shows more detail than the default spec. A local openapi.yaml may be generated for temporary caching, but it is not part of the lean repo.
  6. Use credentials from environment (MSTR_PASSWORD) or user-provided secure runtime values. Never write secrets to memory, skills, config, or logs.

Skill precedence (one-way — no loops)

This skill is the NLQ classifier. After classifying the surface, it hands off downward and does NOT take back control:

strategy-automation (this skill — classify)
  ├─► strategy-data-modeling (plan, Kimball-first)    ← all modeling work routes here
  │     └─► skills/build-mosaic-model/SKILL.md (build-mosaic-model)
  │           └─► strategy-validation (verify)
  ├─► skills/build-mosaic-model/SKILL.md directly                         ← only for post-build admin edits on known-good plans
  ├─► strategy-validation directly                    ← for data-correctness checks on an existing model
  └─► REST / mstrio-py / MCP                          ← for admin/runtime/non-modeling work

Read the full file on GitHub · 115 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. 11d ago First seen · 115 lines · 100 tokens per session scan A 24a9a635f7a6

Subscribe to this mod's changes

strategy-automation is a skill published in the GitHub repository mstr-sharma/strategy-automate (2 stars, last pushed 6d ago), licensed MIT. It adds 100 tokens to every session and 3,387 once invoked, about $0.0005 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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