LLM Mart Basic
@llm-mart · Joined Jun 2026
Use this skill when you need evidence-bounded entry criteria, evidence requirements, owners, and exception paths for a delivery or release gate; triggers include 质量门禁 and quality gate.
Use this skill when you need evidence-bounded quality-practice maturity dimensions, rubric anchors, evidence sufficiency, and improvement gaps; triggers include 质量成熟度 and quality maturity.
Use this skill when you need evidence-bounded quality metric definitions, calculation rules, data sources, freshness, and anti-gaming boundaries; triggers include 质量指标 and quality metric.
Use this skill when you need evidence-bounded quality and delivery metrics, denominators, attribution limits, gaming risk, and the Human-use boundary; triggers include 质量生产力 and quality productivity.
Use this skill when you need to identify and prioritize quality risks from product, change, and evidence inputs; triggers include quality risk analysis.
Use this skill when you need evidence-bounded grounding, relevance, completeness, citation support, abstention, and answer-level evidence in RAG outputs; triggers include RAG 质量 and RAG quality.
Use this skill when you need evidence-bounded query variants, chunking, filters, recall/precision proxies, ranking, freshness, and retrieval evidence; triggers include 检索结果 and retrieval result.
Use this skill when you need evidence-bounded recovery-testing analysis and validation preparation; triggers include 恢复测试 and recovery-testing.
SkillBill packages your engineering judgment into governed skills, then uses a durable Kotlin runtime to ensure agents actually execute that process consistentl…
End-to-end ML toolkit with 26 CLI commands. Use when training models, tuning hyperparameters, detecting data drift, generating HTML reports with charts, profiling datasets, detecting anomalies, forecasting time series, checking fairness, or serving models as REST APIs. Prefer ove
Wrap a public HTTP API (Open-Meteo weather as the demo) with credential handling, error normalisation, and a single retry on transient network failures. Demonstrates the production-shaped baseline for any "skill that calls an external service" — env-based secrets, structured erro
Read a CSV file from disk, compute per-column min/mean/max for every numeric column, emit the result as JSON. Stdlib-only Python; no pandas, no numpy. Demonstrates the simplest possible "give me a file path, get back structured analysis" skill — a deliberate baseline for any skil
Summarise a chunk of text down to roughly `length` words using the agent's configured LLM provider. Input shape `{ text: string, length?: number }` on stdin, JSON; output shape `{ summary: string }` on stdout, JSON. Minimal: ~50 lines, no streaming, no retries — a deliberate base
Unified operational manual for AI agents driving the Chrono AI service stack — NyxID (identity, services, orgs, OAuth clients, proxy) AND Ornn (skill lifecycle — search, pull, install, execute, build, upload, share). One skill, two halves, one identity bootstrap, one set of failu
The manual an AI agent loads to operate Ornn — the model-agnostic skill-lifecycle API (an npm-style registry + CLI for agent skills) — via the NyxID CLI (`nyxid proxy request ornn-api …`). Load and follow this skill WHENEVER the user asks to do anything with Ornn skills or skills
Operational manual for AI agents using the Ornn skill-lifecycle API via direct HTTPS with a NyxID bearer token (`curl -H "Authorization: Bearer $TOKEN" …`). Once loaded, the host agent can search / pull / execute / build / upload / share skills end-to-end. Authoritative contract
Use this whenever you need to know what is actually in a database, warehouse, or DuckDB file before you trust it: ranked inventory of what exists, column profiles, PII detection, grain and data-quality problems, verified join inference, Mermaid ER diagrams, guarded ad-hoc SQL pro
Use this to keep a dbt project and its semantic layer correct as the warehouse and the business change, including a semantic layer that is native Apache Ossie documents rather than dbt. It detects drift on four axes and proposes the fix: schema drift (source columns and tables ad
Use this to author and change a dbt project or a semantic layer: bootstrap a project in a repo that has none (`transform init`), write or refactor model SQL from staging to marts, add tests and docs in schema.yml, manage dependencies, and define or update the semantic layer, whet
Imported from haoming-luo/agentfem/docs/agents.
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.
/fest-commit
fest-commit
Commit changes with festival traceability metadata
/fest-create
fest-create
Create a new festival, phase, sequence, or task
/fest-list
fest-list
List all festivals with their status and completion percentage
/fest-next
fest-next
Get the next actionable festival task with full context
/fest-show
fest-show
Show festival progression (in-progress tasks, roadmap, and dependency view)
/fest-status
fest-status
Show festival progress and current status
/fest-understand
fest-understand
Learn about the Festival Methodology (concepts, structure, rules, and workflows)
/fest-validate
fest-validate
Validate festival structure and find issues
/festival-plan
festival-plan
Turn one sentence of intent into a structured plan, sized correctly and planned through the loop
/MODE_SYNTAX
MODE SYNTAX
Canonical reference for invoking `agentii-investment-intelligence` slash commands across Claude Code, OpenCode, Goose, Codex, OpenClaw, and Claude Cowork. Frozen at v1.0 per the mode-addressability syntax + Round 4 Q12.
/operational-kpi
Operational kpi
Operational KPI dashboard — headcount trends, utilization rates, backlog/book-to-bill
/revenue-decomp
Revenue decomp
Revenue decomposition — segment breakdown, geographic split, product-line waterfall
/unit-economics
Unit economics
Unit economics analysis — CAC/LTV estimation, churn inference, gross margin per unit
/what-if
What if
What-if scenario analysis — scenario tree construction (bear/base/bull), sensitivity to macro variables
/business-model
Business model
Business model classification and structural analysis — product/service/platform, distribution channels, revenue composition, market sizing
/competitive
Competitive
Competitive landscape analysis — peer positioning, market-share dynamics, moat assessment
/earnings-sentiment
Earnings sentiment
Earnings sentiment analysis — analyst estimates vs. guidance, sentiment trends, surprise history
/growth-strategy
Growth strategy
Growth strategy analysis — organic/inorganic growth decomposition, pipeline analysis, execution tracking
/recent-quarter
Recent quarter
Recent quarter performance analysis — quarterly P&L, margin drivers, EPS, sequential momentum
/risk
Risk
Risk analysis — regulatory, competitive, macro, and technology risk assessment
Implementation of Podlite markup language
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