LLM Mart Basic
@llm-mart · Joined Jun 2026
Build and modernize WPF applications on .NET with correct XAML, data binding, commands, threading, styling, and Windows desktop migration decisions.
Write, run, or repair .NET tests that use xUnit. Use when a repo uses `xunit`, `xunit.v3`, `[Fact]`, `[Theory]`, or `xunit.runner.visualstudio`, and you need the right CLI, package, and runner guidance for xUnit on VSTest or Microsoft.Testing.Platform.
Use when writing, reviewing, or refactoring C/C++ code, especially on 32-bit ARM embedded targets. NOT for formatting-only changes, simple file reads, non-embedded C/C++ (desktop/server), or C#/Java despite the 'C' in the name.
Use when debugging embedded firmware issues — analyzing crash logs, investigating state machine lockups, tracing sensor/signal anomalies, or performing structured root-cause analysis after a crash has been located. For fault-register and stack-frame triage, load hardfault-triage
Use when writing or reviewing embedded C firmware, FreeRTOS tasks, ISR handlers, NVM/flash storage, or sensor driver state machines. NOT for documentation-only RTOS references, conceptual RTOS discussions, or bare-metal projects without an RTOS or sensor subsystem.
Use when reviewing design documents, architecture specs, technical proposals, or plans that make claims about API names, file paths, enum values, counts, or mechanism feasibility — a lightweight claim-by-claim check against the codebase with evidence. Built into embedded-workbenc
Use when triaging processor exception crashes — HardFault, MemManage, BusFault, UsageFault, data/prefetch abort, illegal instruction, or watchdog timeout. Covers fault-register interpretation, stack-frame extraction, PC-to-source resolution, and root-cause classification.
Use when building, flashing, or packaging firmware with Keil MDK (UV4 CLI, ARMCLANG), analyzing .map files for ROM/RAM optimization and memory budget, or diagnosing Keil-specific build failures. NOT for non-Keil build systems (Makefile, CMake, IAR, GCC-only). For crash triage see
Use when reviewing or fixing async protocols, retries, ACK/NACK handling, pending flags, timeout logic, or state-machine lockups in embedded firmware. NOT for generic network protocol design (TCP/HTTP/MQTT) unless targeting embedded firmware stack.
Use when developing Go applications, implementing job schedulers or cron (netresearch/go-cron, ofelia), Docker API integrations, LDAP/AD clients, building resilient services with retry logic, setting up Go test suites (unit/integration/fuzz/mutation), or running golangci-lint.
Deep strategic research engine — decomposes questions into parallel research threads, spawns multiple agents, and synthesizes into actionable strategic analysis
Quick capture of raw thoughts with intelligent domain classification and competitive intelligence extraction
Run one task through the V-model verification loop: CP-2 plan → CP-3 build → CP-3v component verify → CP-4 integration verify (full lane) → CP-5 acceptance. The worker never grades its own homework; evidence rows trace back to AC-n. Opt-in: invoke with /closed-loop or by asking f
Deep-dive 7-day analysis across all data sources for weekly reviews, board prep, and strategic planning
Autonomous content pipeline - scout announcements in your field, triage by trend momentum and personal angle, produce posts/blogs/videos in your voice with ledger-based dedup, hard volume caps, and screenshot-verified publishing
Create user stories with duplicate checking across any project tracker (Linear, GitHub Issues, Jira)
Generate personalized news intelligence with verified sources (7-day freshness requirement)
A passive daily work journal that Claude keeps FOR you so you never have to write it yourself. Append short entries after meaningful work (what was done, what you focused on, artifacts touched) to 01-daily/journal/YYYY-MM-DD.md. Run a guided reflection at night or in the morning.
Pick the right way to represent a dataset so a reader gets the finding in three seconds — a catalog of 20+ chart and diagram forms with when-to-use and failure modes, plus the encoding decisions that make any of them readable (takeaway headline, direct labels, kill the axis, high
Generate meaning-carrying editorial data-illustrations in the monotykamary / Linear aesthetic (near-black grayscale, Inter display + mono labels, hairline framed figures) with a single coral accent. This is a GENERATIVE GUIDE, not a template gallery: it teaches the "claim -> geom
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.
Use MCP Inspector to connect to local or remote servers, inspect capabilities, call tools, read resources, test prompts, and diagnose failures before release.
Build an MCP server in TypeScript with focused tools, validated schemas, local and remote transports, Inspector tests, and production security controls.
/standup
Standup
Daily standup: all 8 departments report on the current project in parallel
/analyze-misfires
analyze-misfires
Identify skills injected where not needed, propose regex and description tightening
/announce
announce
Draft X/Twitter announcement post (or thread) for the latest plugin release
/audit-plugin
audit-plugin
Deep quality audit of all skills, agents, and commands for inconsistencies, gaps, duplication, and token waste
/diagnose-negatives
diagnose-negatives
Analyze negative-signal sessions for a skill, identify failure patterns, propose and apply fixes
/eval-skills
eval-skills
Eval all skills with sufficient data, rank by procedure-following score, identify candidates for optimization
/evolve-skill
evolve-skill
Propose a skill revision and compare fresh executions under a frozen rubric
/prune-sync-log
prune-sync-log
Prune stale entries from the whetstone sync decision log
/release
release
Bump version, commit, push, mirror to ai-skills, and update local plugin
/skillopt
skillopt
Run the SkillOpt process-skill optimizer (offline, local). Default prints the exact bare-terminal command (safe); --run executes it in-session (hardened + checkpointed).
/sync-from-repos
sync-from-repos
Analyze reference repos and recommend skill/agent/command improvements based on cross-repo patterns
/triage-prs
triage-prs
Triage all open PRs with parallel agents, label, group, and review one-by-one
/write-skill
write-skill
Author a new skill from scratch with paired trigger fixtures and full validation. Use when adding a skill that has no upstream skills.sh source (discipline, meta, or internal-pattern skills).
/ia-adr
ia-adr
Create Architecture Decision Records with format selection and lifecycle management
/ia-agent-native-audit
ia-agent-native-audit
Score each of the 5 agent-native principles (parity, granularity, composability, emergent capability, improvement-over-time) against a codebase and report gaps
/ia-brainstorm
ia-brainstorm
Explore requirements and approaches through collaborative dialogue before planning implementation
/ia-changelog
ia-changelog
Create engaging changelogs for recent merges to main branch
/ia-deepen-plan
ia-deepen-plan
Expand each section of a plan via parallel research agents that add framework specifics, library conventions, and concrete implementation steps
/ia-document-release
ia-document-release
Post-ship documentation sync. Reads all project docs, cross-references the diff, updates README/ARCHITECTURE/CONTRIBUTING/CLAUDE.md to match what shipped, polishes CHANGELOG voice, and optionally bumps the version.
/ia-feature-video
ia-feature-video
Record a video walkthrough of a feature and add it to the PR description
Make any song you can imagine
38 views 0 likesLeading AI-powered video generation platform that specializes in creating hyper-realistic talking avatars
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33 views 0 likesGeneral-purpose agent in one static Go binary. ReAct loop, ACP server for IDEs, OpenAI-compatible REST API with embedded web UI, Telegram gateway, cron schedule…
18 views 0 likesAutonomous agent framework with structured memory, safety hooks, and loop management. Built by the agent that runs on it.
19 views 0 likesTSP自托管、零运维的 A 股「选股 + 监控 + 回测」量化工作台 | 基于 TickFlow 数据源 | LLM能力驱使策略定制+个股分析+复盘 | 自由接入第三方数据源与个性化扩展数据 | 个人开源 ,非TickFlow官方项目
14 views 0 likesCurated, verified Agent Skills powered by ModelStudio.
17 views 0 likesRun Claude Code, Codex, Antigravity, Cursor Agent and OpenCode as one runtime — persistent sessions, multi-agent councils, an OpenAI-compatible endpoint, an MCP…
16 views 0 likespi had nothing (nothing), so I made something (something) — sorry mariozechner-senpai, I went ahead and lovingly soiled your pure pi for you. opinionated fork o…
13 views 0 likesA persistent workspace for development work that self-improves and continues beyond one session.
32 views 0 likesOpen-source memory and context for user-aware agents: scoped memory, provenance, retrieval quality, correction, boundaries, evals, and MCP/HTTP access.
19 views 0 likes📚 A zero-dependency, git-backed micro-lesson library for AI Agents to asynchronously share and search verified debugging experience. Python stdlib only. | http…
28 views 0 likesDeterministic, local-first memory and guardrails for AI coding agents with no LLM in the hot path.
30 views 0 likesDeterministic spec-orchestration for local LLMs in the pi coding agent — drives prompts through refine→research→grill→compose→critique, with bundled web/docs/fe…
19 views 0 likesNative Safari browser automation for AI agents. 97 tools via AppleScript — zero overhead, keeps logins, runs silently in background. Drop-in alternative to Chro…
31 views 0 likesAgent OS: keep specialist agents in a hub, spin up a temporary orchestrator per task. Local-first, works with any model.
14 views 0 likesGit for agent memory. Branches, diffs, PRs, and rollback for what your agents know.
31 views 0 likesMulti-Provider AI Gateway - No personal logs by design. Model autodiscovery, Failover groups, High availability, Android companion app, and more - "Because we h…
15 views 0 likesProduction-grade MCP server for MikroTik RouterOS with secure AI-native network automation.
27 views 0 likes