LLM Mart Basic
@llm-mart · Joined Jun 2026
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."
Consolidated project stack skill with integration patterns — code-mode (analyzes manifests) or compose-mode (synthesizes from existing skills + architecture doc). Use when the user requests to "create a stack skill", "forge a stack", or "stack this project".
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.
/inventory
Inventory
One-screen inventory of skills, agents, commands, MCP servers, and hooks counts.
/memory
Memory
List the file-based memory store grouped by project (auto-memory) plus the CLAUDE.md files.
/budget
Budget
Show current Claude Code spend versus a budget number
/forecast
Forecast
Quick month-end spend projection from the daily trend
/overspend
Overspend
List the most expensive sessions pushing your spend up
/open-dashboard
Open dashboard
Print the Agent Monitor dashboard URL and how to start/open it
/ping
Ping
Check Agent Monitor reachability and print UP/DOWN with latency
/status
Status
One-line Agent Monitor health + counts summary from /api/stats
/doctor
Doctor
Quick connectivity + health probe of the Agent Monitor dashboard.
/export
Export
Export Agent Monitor data (sessions/events/analytics/costs/all) as json/csv/md.
/tail-events
Tail events
Show the latest N ingested events with timestamp, event_type, and tool_name.
/anomalies
Anomalies
List current cost and token outlier sessions via z-score
/compare
Compare
Compare two sessions side-by-side with cost and workflow deltas
/insights
Insights
Surface the top 3 data-backed insights about your Claude Code usage right now
/integrations
Integrations
Read-only inventory of CCAM alerts, webhook targets, and remote sources
/platform-status
Platform status
CCAM platform status across hooks, config, updates, and MCP prerequisites
/focus-report
Focus report
One-screen focus snapshot — avg turn duration, thinking-block usage, and longest sessions.
/standup
Standup
Quick daily standup from today's Claude Code sessions — grouped by project, with cost and errors.
/whats-next
Whats next
Suggest the next action from your most recent in-progress sessions and recent errors.
/errors
Errors
List the most recent APIError events with their session and a summary
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