LLM Mart Basic
@llm-mart · Joined Jun 2026
Design an auditable playbook when no narrower one fits: a large migration, an ambitious multi-part change, or work a human reviews after stepping away. Scales rigor to the task, runs a hypothesis loop, and logs decisions via show-me-your-work. Use for /figure-it-out, 'figure it o
Find failing PR checks, inspect logs or external check links, and apply focused fixes
Resolve merge conflicts non-interactively, validate build and tests, and finalize conflict resolution
Fetch and summarize review comments from the active pull request
Periodic pass that keeps a project's verification skill and feature map honest: parallel source readers per feature, one live session driving every feature, at most one PR of proven corrections. Use for /maintain-verification-skill or "audit the verify skill".
Prepare PRs for review by cleaning noisy history, improving PR descriptions, and adding reviewer guidance without changing code behavior. Use for "make this easy to review", "tidy this PR", "clean up commits", or "annotate the diff".
Spawn the comment-sicko subagent, fix accepted findings, and offer encodings for claimed constraints.
poteto's agent style for concise, detailed responses, deliberate subagents, unslopped prose, simple code, and verified work. Use for poteto, /poteto-mode, or requests to work in this style.
Apply when repeated fixes sharing an assumption fail. State the assumption and choose an observation that can challenge it before trying another fix that depends on it.
Apply when wiring validation, error handling, or framework adapters. Concentrate guards at system boundaries (CLI, config, network, external APIs); trust internal types and keep business logic in pure functions.
Apply to any non-trivial work, not just bulk work: edits, migrations, analyses, checks. Build the tool that does it or proves it (codemod, script, generator, or a skill your subagents follow) instead of working by hand. The tool is the artifact a reviewer can rerun.
Apply when you catch yourself writing the same instruction a second time, or notice a recurring correction. Encode the rule as a lint, metadata flag, runtime check, or script instead of more text.
Apply when facing a novel UI interaction or architectural decision with no precedent in the codebase. Build 2-3 competing prototypes and compare side by side before committing.
Apply when product, UX, or feature-scope tradeoffs come up. Choose user delight over implementation convenience; ship fewer polished features over more rough ones.
Apply when debugging. Trace each symptom to its root cause and fix it there; reproduce first, ask why until you reach it, resist nil-check guards that silence crashes.
Apply before writing logic: choosing core types and data structures, sequencing scaffold-vs-feature work, asking what concurrent actors share. Get the data structures right so downstream code becomes obvious.
Apply when context is filling up: large outputs, long files, repeated reads, fan-out planning. Route bulk to subagents; keep summaries in the main thread, not raw payloads.
Apply when refactoring, evaluating diff size, or tempted to add abstractions, layers, or signal threading. Bias toward deletion and the smallest change that solves the problem.
Apply when designing commands, lifecycle steps, or processing loops that run amid crashes, restarts, and retries. Converge to the same end state regardless of partial prior runs.
Apply when introducing a new internal API while old callers still exist. Migrate callers and delete the old API in the same wave instead of preserving compatibility layers.
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.
/org-health-check
Org health check
Full health check for one Proofpoint Essentials customer org
/search-org
Search org
Resolve a Proofpoint Essentials customer org by name or domain and show its details
/check-threats
Check threats
View recent TAP threat events including blocked messages, delivered threats, and click activity
/decode-url
Decode url
Decode a Proofpoint URL Defense rewritten URL back to the original URL
/investigate-threat
Investigate threat
Deep-dive threat investigation with forensics, campaign context, and remediation options
/release-quarantine
Release quarantine
Release one or more quarantined messages to their intended recipients
/search-quarantine
Search quarantine
Search quarantined messages in Proofpoint by sender, recipient, subject, or reason
/vap-report
Vap report
Get the Very Attacked People (VAP) report showing the most targeted users
/month-end-recon
Month end recon
Run the full billing-drift sweep for a billing period, formatted as a month-end reconciliation report
/renewals
Renewals
List upcoming contract and subscription renewals within a window, sorted by date
/true-up
True up
Run the license true-up reconciliation for one client or the whole portfolio
/search-tickets
Search tickets
Search Freshdesk tickets with the Freshdesk query language — filter by status, priority, agent, group, type, tag, and date — and return a ranked, readable result list
/ticket-summary
Ticket summary
Summarize a single Freshdesk ticket and its full conversation thread — the request, what has happened, current SLA state, and the recommended next action
/add-action
Add action
Add an action (note, update, or response) to an existing HaloPSA ticket
/contract-status
Contract status
Check contract status, service entitlements, and billing information for a client
/create-ticket
Create ticket
Create a new service ticket in HaloPSA
/kb-search
Kb search
Search the HaloPSA knowledge base for articles and solutions
/search-assets
Search assets
Search for configuration items/assets by name, serial number, type, or client
/search-clients
Search clients
Search for HaloPSA clients by name, domain, or other attributes
/search-tickets
Search tickets
Search for tickets in HaloPSA by various criteria
Okou connects to the tools your team already uses and does the work — across marketing, sales, engineering, and operations, under your control.
4 views 0 likesAn open-source Digital Worker platform for reliable execution, continuous co-evolution, and building Enterprise AI assets.
5 views 0 likesA curated list of AI Agent evolution, memory systems, multi-agent architectures, and self-improvement projects. | evomap.ai
4 views 0 likesA governance harness for AI coding.
3 views 0 likesDeepSeek Harness 手机版:可直接安装的 Android APK,AI 免 Root 操作手机(Shizuku/root 可选),文件编辑只需所有文件访问权限,前台保活 + AI 通知
1 views 0 likesLocal-first, governed AI agent runtime for Python — embed it in your app, or run it as a CLI or ACP server. Permissions, MCP, memory and audit replay built in.
2 views 0 likesOrbi — the factory that builds and operates AI software factories. GitHub Issues in, releases and runnable system out
3 views 0 likesOpen-source AI agent harness in native Rust — GUI, CLI, headless, and webapp from one binary. Multi-provider, MCP, skills, plugins, agent teams.
1 views 0 likesThe SDK for browser agents. Interact, search, extract, and fetch any site reliably across the web
4 views 0 likesAgent-native shopping for extreme value: verifiable same-product price evidence, checkout, orders, delivery, and after-sales.
5 views 0 likesThe extensible power-user platform for Google Antigravity. Adds a native In-App Browser, animated Desktop Pets, revamped Gemini UI, and custom BYOK Gemini Pro k…
4 views 0 likesOpen-source, single-binary, self-hosted AI agent — your models and data stay on your machine. A coding agent on par with Claude Code and a personal assistant li…
4 views 0 likesYour pocket agent. Local-first AI agents on iOS and Android — real workspaces, tool execution with approvals, and your choice of model (DSH · Claude Code · Code…
3 views 0 likesBridge between QQ (SnowLuma OneBot v11) and DeepSeek Harness agents: social simulation, safe MCP tools, slang learning and more.
2 views 0 likesA 7×6 framework for agent architecture. 28 patterns, each placed at a coordinate, runnable Python code with verified engineering slices from Claude Code, Aider,…
2 views 0 likes针对 AI 自动化渗透 Agent 的新一代反制蜜罐,通过反向代理将API密饵载入真实业务、反向提示词注入等方式反制自动化渗透 Agent,实现多款主流通用Agent的反制上线控制。
2 views 0 likesOpen-source, local-first AI agent for coding and real work. BYOK models, MCP, skills, plugins, workflows, and private knowledge bases.
4 views 0 likesA free AI-agent toolbox for Android, 一站式安卓AI Agent工具箱
4 views 0 likesGoogle Workspace CLI — one command-line tool for Drive, Gmail, Calendar, Sheets, Docs, Chat, Admin, and more. Dynamically built from Google Discovery Service. I…
4 views 0 likesIndependent, unofficial CLI to edit CapCut and JianYing (剪映) projects — subtitles, timing, speed, volume, templates, cut long-form to shorts. No API needed, rea…
5 views 0 likes