LLM Mart Basic
@llm-mart · Joined Jun 2026
Produce a research report from the vault: scope the question against existing pages, name the gaps, and write findings with citations, disagreements and limits. Use this skill when the user asks for a research report, a deep write-up on a topic, or wants to understand a subject t
Produce a periodic review of a second-brain vault: what was added, which topics are growing, what contradicts what, which questions are still open, and what is worth reading next. Use this skill whenever the user asks for a weekly or monthly review, asks what changed in their vau
Clean a raw transcript before ingestion: punctuate, paragraph, label speakers, fix mistranscribed technical terms, and split long recordings by topic. Use this skill when the user drops an auto-generated transcript, subtitle file, podcast or lecture transcript, meeting recording
Draft from the vault: outline from concept pages, keep citations to the user's own sources, and surface where their material disagrees. Use this skill when the user wants to write an article, post, essay or newsletter based on what they have collected, or asks what they could wri
Use this skill when selecting and reporting verification for Skill changes; triggers include Skill change verification, quality gates, and evidence levels.
Use this skill when designing, running, interpreting, or reporting Agent Skill evaluations, selecting cases or judges, and analyzing trigger, benchmark, or regression evidence; triggers include Skill evaluation and evaluation design.
Use this skill when reviewing the contract completeness of Skills, Prompts, metadata, or QA documentation; triggers include Skill prose review, Prompt review, and contract audit.
Use this skill when auditing or trimming process residue from Skills, Prompts, comments, or docs; triggers include process prose cleanup, review residue, and current-state rewriting.
Use this skill when reviewing a complete Skill package for architecture, scope, triggers, independent installation, bilingual consistency, Eval readiness, and evidence boundaries; triggers include Skill quality review and package review.
Use this skill when you need to review acceptance criteria for ambiguity, missing rules, and verifiability; triggers include acceptance criteria review.
Use this skill when you need to design accessibility testing against WCAG, keyboard navigation, and assistive technology scenarios; triggers include accessibility testing and a11y testing.
Use this skill when you need evidence-bounded failure classification, retry/fallback/escalation, state consistency, user notice, and recovery evidence; triggers include Agent 故障恢复 and Agent failure recovery.
Use this skill when you need evidence-bounded checkpoints, heartbeats, resume, cancellation, duplicate submission, timeouts, and resource lifecycle; triggers include 长运行 Agent and long-running Agent.
Use this skill when you need evidence-bounded loop state, plan/action/observation cycles, stop conditions, budgets, repetition, and trace evidence; triggers include Agent 循环 and Agent loop.
Use this skill when you need evidence-bounded memory write/read/update/delete, retention, contamination, isolation, provenance, and forgetting behavior; triggers include Agent 记忆 and Agent memory.
Use this skill when you need evidence-bounded Agent identity, tool/resource scope, approval, denial, escalation, and side-effect boundaries; triggers include Agent 权限 and Agent permission.
Use this skill when you need to test AI agent tool-call contracts, authorization, failures, and side-effect boundaries; triggers include agent tool testing.
Use this skill when you need to test AI agent goals, state, planning, recovery, and safety boundaries; triggers include ai agent testing.
Use this skill when you need AI-assisted testing workflows such as test data generation, root-cause analysis, and prioritization; triggers include AI-assisted testing and AI for QA.
Use this skill when you need to test an AI-enabled product feature for behavior, safety, and user-impact boundaries; triggers include AI feature testing.
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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