LLM Mart Basic
@llm-mart · Joined Jun 2026
Pre-pipeline aggregator that scans AI agent cache directories (.claude, .cursor, .antigravity, .openclaw) or any user-specified directory for experimentation logs, extracts insights and numeric results, and formats them as PaperOrchestra-ready inputs (idea.md + experimental_log.m
Step 3 of the PaperOrchestra pipeline (arXiv:2604.05018). Execute the literature search strategy from outline.json — discover candidate papers via web search, verify them through Semantic Scholar (Levenshtein > 70 fuzzy title match, temporal cutoff, dedup by paperId), cross-corro
Step 1 of the PaperOrchestra pipeline (arXiv:2604.05018). Convert (idea.md, experimental_log.md, template.tex, conference_guidelines.md) into a strict JSON outline containing a plotting plan, literature search plan (Intro + Related Work), and section-level writing plan with citat
Run the four paper-quality autoraters from PaperOrchestra (arXiv:2604.05018, App. F.3) — Citation F1 (P0/P1 partition + Precision/Recall/F1), Literature Review Quality (6-axis 0-100 with anti-inflation rules), SxS Overall Paper Quality (side-by-side), and SxS Literature Review Qu
Orchestrate the full PaperOrchestra (Song et al., 2026, arXiv:2604.05018) five-agent pipeline to turn unstructured research materials (idea, experimental log, LaTeX template, conference guidelines, optional figures) into a submission-ready LaTeX manuscript and compiled PDF. TRIGG
Reverse-engineer raw materials (Sparse idea, Dense idea, experimental log) from an existing AI research paper to build a benchmark case for evaluating paper-writing pipelines. Replicates the PaperWritingBench dataset construction procedure from arXiv:2604.05018 §3 / App. C. TRIGG
Step 2 of the PaperOrchestra pipeline (arXiv:2604.05018). Execute the visualization plan from outline.json — render plots and conceptual diagrams from experimental_log.md and idea.md, optionally refine via VLM critique loop, and produce context-aware captions. Runs in parallel wi
Step 4 of the PaperOrchestra pipeline (arXiv:2604.05018). ONE single multimodal LLM call that drafts the remaining paper sections (Abstract, Methodology, Experiments, Conclusion), extracts numeric values from experimental_log.md into LaTeX booktabs tables, splices the generated f
从游戏客户端(安装包/APK/IPA/EXE 或 dump.cs、lua、usmap、抓包等)反推服务端协议并复现可部署服务端。含阅读路径分派、原理层(primer:三要素/数据包协议/协议表/热更源码)、四阶段路线图(workflow-roadmap:静态分析→建工具+登录链→重定向→补包循环→清单迭代)、11 种反推方法选择器(含内联服务端路线)、接口清单提取器(tools/)、协议规格模板(protocol.spec.yaml)、wire 级定点改写(不等 schema 齐就能跑)、客户端地址来源清查、三轴状态与验收体系、发布运维清单、进度清单(T
Apply the Minimum Sufficient Work (MSW) principle through the MSW Kernel to scope, execute, verify, and stop agent work. State the requested outcome and smallest proof, admit a claim only when deleting it would leave the contract unmet or unproven, do and prove each necessary cla
Run an authorized task inside an Available Work Time (AWT) window with a shorter Closeout Grace Period (CGP), fixed deadlines, forecast checks, proportional convergence points, and a hard stop. Use when the user explicitly requests timeboxing, supplies an AWT/CGP pair, says AWT o
Apply the Minimum Sufficient Language (MSL) principle through the MSL Kernel to write anything a reader must act on. Bind the reader and what they already know, partition facts from the machinery that produced them, emit each admitted fact as an action, a verification, a judgment
Run the Codex Optimized Development, Evaluation, and Remediation (CODER) Loop with an orchestration-only coordinator, non-overlapping task-family owners, fresh independent reviewers, evidence-scoped remediation, and final coordinator acceptance. Discover and compose optional MSW,
Optimize ChatGPT Voice in the Codex desktop app into an ear-first control plane for free-form task coordination and opt-in workflows. Apply spoken synthesis, routing-only coordination, owning-task role contracts, project placement, explicit authority, safe speech, current-state v
Skill compilation specialist — the forge master. Use when the user asks to "talk to Ferris" or requests the "Skill Forge agent."
Initialize forge environment, detect tools, and set capability tier (Quick/Forge/Forge+/Deep). Use when the user requests to "set up" or "initialize the forge".
Discover what to skill in a large repo and produce recommended skill briefs. Use when the user requests to "analyze source for skills" or "discover skill opportunities."
Design a skill scope through guided discovery. Use when the user requests to "create a skill brief" or "brief a skill".
Compile a skill from a brief. Supports --batch for multiple briefs. Use when the user requests to "create a skill" or "compile a skill."
Fast skill from a package name or GitHub URL — no brief needed. Use when the user requests a "quick skill" or "skill from URL" or "skill from package."
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.
An MCP server exposes tools, resources, or prompts through a standard protocol so an AI application can discover and use external capabilities.
/reconcile-payout
Reconcile payout
Reconcile an Alternative Payments payout by listing its transactions and matching them against invoices and customers
/eol-report
Eol report
EOL/EOS risk report — devices, OS versions, and firmware approaching or past end-of-life/end-of-support, prioritized by criticality
/refresh-calendar
Refresh calendar
Forward-looking hardware refresh calendar for the given window — replace-now / plan-this-year / monitor tiers
/warranty-status
Warranty status
Warranty status snapshot — expired, expiring-soon, and unknown-coverage devices for one client or the whole portfolio
/create-monitor
Create monitor
Create a threshold-based monitor for an Atera agent
/create-ticket
Create ticket
Create a new service ticket in Atera
/get-kb-articles
Get kb articles
Search the Atera knowledge base for articles
/list-alerts
List alerts
List active RMM alerts from Atera
/log-time
Log time
Log work hours on an Atera ticket
/resolve-alert
Resolve alert
Resolve an RMM alert in Atera
/run-powershell
Run powershell
Execute a PowerShell script on an Atera agent
/search-agents
Search agents
Search for RMM agents in Atera by customer or machine name
/search-customers
Search customers
Search for Atera customers by name or criteria
/update-ticket
Update ticket
Update fields on an existing Atera ticket
/alert-triage
Alert triage
Triage open Auvik alerts, rank by severity, and recommend dismissals for known noise
/capacity-check
Capacity check
Scan Auvik interface statistics for saturated links and recurring congestion
/device-inventory
Device inventory
Inventory devices for an Auvik tenant with type, manage status, and lifecycle breakdown
/network-audit
Network audit
Audit a tenant's networks, interfaces, and saved configurations; flag drift and missing backups
/tenant-overview
Tenant overview
Single-tenant Auvik snapshot - devices, alerts, networks, billing usage
/phishing-results
Phishing results
Phishing-simulation results and click-rate trend for a given window
LLM-powered toolkit for skill analysis, AI interviews, resume scoring, and job structuring. Automates professional skill taxonomy and interview processes with a…
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17 views 0 likesFrom ticket to reviewed pull request. Free and open-source, on your machine.
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