LLM Mart Basic
@llm-mart · Joined Jun 2026
Use this skill when you need to partition inputs into evidence-backed valid, invalid, and unknown classes based on constraints, rules, and response differences; triggers include 等价类划分 and equivalence partitioning test design.
Use this skill when error taxonomy, retries, timeouts, fallback, or recovery design needs an evidence-bounded review before implementation; triggers include error handling design review, failure-path review, and recovery readiness review.
Use this skill when you need evidence-bounded failover-testing analysis and validation preparation; triggers include 故障切换测试 and failover-testing.
Use this skill when you need to investigate intermittent test failures from run history and evidence; triggers include flaky test analysis.
Use this skill when you need to design functional test plans or cases for business flows, UI, data, and integrations; triggers include functional testing and functional test cases.
Use this skill when you need evidence-bounded repeat inputs, version/model/prompt factors, invariants, variance evidence, and comparison boundaries; triggers include LLM 一致性 and LLM consistency.
Use this skill when you need to design LLM evaluation datasets, judges, metrics, and human-review boundaries; triggers include llm evaluation design.
Use this skill when you need evidence-bounded claim-to-source relations, unsupported assertions, abstention, uncertainty, and evidence review; triggers include LLM 幻觉 and LLM hallucination.
Use this skill when you need to test LLM behavior, failure modes, and evidence-based quality boundaries; triggers include llm testing.
Use this skill when you need to analyze logs into evidence, timelines, anomalies, and follow-up hypotheses; triggers include log analysis.
Use this skill when you need to plan manual or exploratory testing with charters, heuristics, and session records; triggers include manual testing and exploratory testing.
Use this skill when you need to derive test candidates from input transformations and expected relations when a direct oracle is limited; triggers include 变形测试 and metamorphic test design.
Use this skill when you need to identify, contextualize, and investigate metric anomalies from observability evidence; triggers include metrics anomaly analysis.
Use this skill when you need to design mobile test plans for iOS or Android covering functionality, compatibility, performance, network, and security; triggers include mobile testing and app testing.
Use this skill when you need to review mock fidelity, contract alignment, over-mocking, and drift evidence; triggers include Mock 质量评审 and mock quality review.
Use this skill when you need to derive test-path candidates from sourced behavior, state, or process models; triggers include 基于模型的测试 and model-based test design.
Use this skill when you need evidence-bounded delegation, coordination, shared state, conflicts, ownership, termination, and traceability; triggers include 多 Agent 协作 and multi-agent coordination.
Use this skill when you need to interpret mutation operators, killed and survived mutants, and evidence limits; triggers include 变异测试分析 and mutation testing analysis.
Use this skill when you need to discover invalid, denied, failed, degraded, or unsafe-recovery scenarios from product evidence; triggers include negative scenario discovery.
Use this skill when logging, metrics, tracing, alerting, or SLO design needs an evidence-bounded review before implementation; triggers include observability design review, telemetry readiness review, and alert actionability audit.
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.
Treat an AI agent skill as both an instruction package and a software dependency: inspect what it says, what it runs, what it can access, and how it updates.
/stale
Stale
Find concept pages nobody has touched
/tags
Tags
Audit the tag vocabulary
/timeline
Timeline
How my sources developed over time
/trace
Trace
Show which pages an answer used
/typed-links
Typed links
Add relation types where they matter
/weekly
Weekly
The weekly review
/build
Build
Implement an approved plan or issue in its own worktree, run the gate, open the pull request.
/close-out
Close out
Close a finished session: sweep for unfinished work, land and hand off, file the follow-ups, tell the sessions that depend on this one, then archive.
/handoff
Handoff
Write the repository handoff file for the next session, and record any durable learning.
/land
Land
Merge an approved pull request, clean up its worktree and branch, then check whether a release is due.
/plan
Plan
Turn a topic or issue into a plan the reviewer approves in the native plan pane.
/research
Research
Answer a research question with parallel read-only gatherers and one synthesized digest.
/review
Review
Review the branch's diff in two fresh contexts — scope against the spec, then quality — and report findings only.
/ia-refine-prompt
ia-refine-prompt
Transform a vague prompt into precise, structured AI instructions
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