LLM Mart Basic
@llm-mart · Joined Jun 2026
Orient a developer making a WordPress plugin or theme
Register and translate a WordPress plugin's dynamic strings with WPML — option values, admin-entered labels, and other free-form text that is NOT a static gettext string. Register via do_action('wpml_register_single_string', $domain, $name, $value) and read back via apply_filters
Use when the user explicitly wants to discuss, brainstorm, compare options, or make a material preference decision, or when unclear intent needs guided clarification; do not use for clear execution or a single discoverable detail.
Use when a failure, regression, crash, flake, or unexpected result has an unknown cause that must be diagnosed before a safe fix; do not use when the cause and narrow fix are already clear.
Use when the user explicitly asks to persist until a verifiable result, fix until green, monitor through completion, or stay within a stated budget; do not infer persistence from difficulty.
Use when the user asks to add or refresh concise project-local Teamwork instructions in one named project; do not use to install global tools or create workflow records.
Use when the user asks for an implementation plan, task breakdown, checklist, roadmap, or handoff and the outcome and direction are already selected; do not use to choose the direction or execute changes.
Use when a broad or deep external investigation needs multiple source classes, claim-level evidence synthesis, or contradiction resolution; do not use for a narrow lookup or local code inspection.
Use when the user asks to review, audit, critique, or validate a stable code, document, plan, artifact, or claim; do not use to diagnose an unknown failure or create the initial candidate.
Use when the user asks to inspect, install, or refresh Teamwork-owned global surfaces; do not use as a prerequisite for another skill or to migrate project documents.
The Execution Trader's procedure for turning an approved ticket into one Hyperliquid action and reconciling it - the pre-send checklist, order construction rules, single-send discipline, unknown-result handling and the execution report. Use before and after every send, cancel, mo
What the desk does when something goes wrong on Hyperliquid - unknown send results, unexpected fills or positions, unprotected positions, stuck or orphaned orders, API outages, rate limiting, and suspected API wallet compromise. Contain first, reconcile from the exchange record,
How the desk watches markets and the account between trades using Grok Bot routines and WebSocket or polling watches - the desk brief, book checks, funding and price watches, alert conditions and what a watch may and may not do. Use when the user asks for briefings, alerts, "watc
How the HyperGrok trading desk works as a team of Grok Bots - roles, seats, shared workspace, evidence standard, approval model and handoff format. Use when setting up the desk, when a Bot is unsure who owns something, or when a request does not fit the normal trade lifecycle.
The Trade Reviewer's procedure for journaling desk activity and reviewing trades from the exchange record - process graded separately from outcome, execution costs measured, one repeatable finding per review, plus the weekly desk review. Use after any send, when a trade closes, o
How the Risk Manager writes the desk's risk limits with the user, sizes every proposed trade from live account state and Hyperliquid's real constraints, checks the book, and issues a PASS or REJECT with exact ticket fields. Use for setting up or changing limits, sizing any trade,
How the Strategist works with the user to turn their own trading idea into explicit rules, backtest it honestly on Hyperliquid candle and funding history, and paper-trade it on testnet through the desk lifecycle. Method only - the desk ships no strategies and makes no return clai
The end-to-end procedure for one trade on the HyperGrok desk - from an idea to a reviewed, journaled result - with the ticket format, who owns each stage, and what "done" looks like. Use whenever the user wants to open, adjust or close a position, or whenever any Bot is about to
Read a Hyperliquid account from the desk computer - positions and margin, spot balances, open orders including trigger details, fills, funding paid, ledger updates, order status by oid or cloid, historical orders, portfolio history, fee tier and rate-limit budget - with curl and
Less common Hyperliquid actions and their rules - dead-man's switch (scheduleCancel), TWAP orders, spot orders, expiresAfter and nonces, API wallet approval from code, sub-account and vault addressing, HIP-3 dexs, and what the desk deliberately does not do (transfers, withdrawals
Fourteen posts of being wrong in production, compressed to checkboxes
Healthy nodes, a quiet network, 300 restarts in three days, and a latency budget measured in milliseconds
Discovery worked. Ping worked. Every TCP connection timed out, and later the tunnel only worked when someone had a terminal open.
Every VM came back. The cluster did not. Declarative systems converge on config, and the datapath isn't config.
A surprising share of AI-in-the-terminal failures aren't the AI. They're zsh, and a version of bash from 2006.
A Claude Code plugin turns standalone project configuration into a namespaced, installable extension that teams and communities can update as one unit.
None of the safety came from the model. It came from six boring habits.
Skills package instructions and references. Subagents run work in a separate context and return results. They solve different problems and can be composed deliberately.
Six hours in, one step left, everything green, and the incident that didn't happen
CLAUDE.md carries persistent project context. Skills load reusable procedures when relevant. Separating stable facts from task-specific workflows keeps both easier to maintain.
Twenty minutes recovering secrets that never existed, and the one sentence from a human that ended it
An API request routing a model's tool call through an approval gate to a remote MCP server
31 config keys, two audits, and why the first one was wrong in both directions
The official MCP Registry stores standardized server metadata rather than package code. Publishers verify a namespace, describe installation or remote access, and submit immutable versions.
Everyone looks at the Dockerfile. The file that actually leaked the key was the project file.
Remote MCP authorization uses established OAuth standards, but secure integration still requires issuer validation, least-privilege scopes, protected token handling, and server-side enforcement.
"Copy it over and switch the reference" is two steps, and the outage lives in the one nobody checks
stdio fits local processes and prototypes. Streamable HTTP fits hosted services and shared integrations. The right choice follows where the capability runs and who must reach it.
The most important rule wasn't about what I could change. It was about what I was allowed to display.
Tools perform operations, resources expose readable context, and prompts provide reusable templates. Choosing the correct primitive makes an MCP server easier to understand and govern.
/doc-api
Doc api
Generate API documentation from code
/docs
Docs
Update or generate YAML documentation for SQL models with proper descriptions and tests
/e2e-setup
E2e setup
Configure end-to-end testing suite
/estimate-assistant
Estimate assistant
Generate accurate project time estimates
/explain-code
Explain code
Analyze and explain code functionality
/explain-issue-fix
Explain issue fix
Explain how tasks in an issue were implemented with detailed breakdown
/find
Find
Search and locate tasks across all orchestrations using various criteria.
/five
Five
Apply the Five Whys root cause analysis technique to systematically investigate issues
/fix-github-issue
Fix github issue
Analyze and fix a GitHub issue with comprehensive testing and verification
/fix-issue
Fix issue
Fix a specific issue or problem with the given identifier or description
/fix-pr
Fix pr
Fetch unresolved comments for current branch's PR and fix them
/future-scenario-generator
Future scenario generator
Generate and analyze future scenarios with plausibility scoring, trend integration, and uncertainty quantification.
/generate-api-documentation
Generate api documentation
Auto-generate API reference documentation
/generate-linear-worklog
Generate linear worklog
You are tasked with generating a technical work log comment for a Linear issue based on recent git commits.
/generate-test-cases
Generate test cases
Generate comprehensive test cases automatically
/generate-tests
Generate tests
Generate comprehensive test suite for $ARGUMENTS following project testing conventions and best practices.
/git-status
Git status
Show detailed git repository status
/hotfix-deploy
Hotfix deploy
Deploy critical hotfixes quickly
/husky
Husky
Verify repository is in working state by running CI checks and fixing issues
/implement-caching-strategy
Implement caching strategy
Design and implement caching solutions
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