LLM Mart Basic
@llm-mart · Joined Jun 2026
Use this skill when you need to select high-risk multi-factor combinations after factors, values, and constraints are explicit; triggers include 组合测试 and combinatorial test design.
Use this skill when you need to select evidence-backed browser, engine, device, and version coverage; triggers include 跨浏览器测试 and cross-browser testing.
Use this skill when an ERD, DDL, ORM schema, or migration plan needs an evidence-bounded database design review before implementation; triggers include database design review, migration readiness review, and schema quality audit.
Use this skill when you need to turn conditions, rules, actions, and outcomes into an auditable set of rule combinations; triggers include 决策表测试设计 and decision table test design.
Use this skill when you need evidence-bounded dependency-failure-testing analysis and validation preparation; triggers include 依赖故障测试 and dependency-failure-testing.
Use this skill when you need evidence-bounded disaster-recovery-testing analysis and validation preparation; triggers include 灾备测试 and disaster-recovery-testing.
Use this skill when you need to analyze distributed traces for call paths, latency, errors, and evidence gaps; triggers include distributed trace analysis.
Use this skill when you need to discover boundary, rare, limit, ordering, or combination scenarios from product and test evidence; triggers include edge case discovery.
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.
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.
Add remote HTTP or local stdio MCP servers to Claude Code, choose the right scope, protect credentials, verify the connection, and test with least privilege.
Skills teach Claude a repeatable method, connectors provide governed access to apps and live data, and plugins package related capabilities for installation and sharing.
Use an agent skill to package reusable know-how and workflow instructions. Use an MCP server when an agent needs live, governed access to external data or actions.
Custom commands and skills can both create a slash-invoked workflow in Claude Code. The important choice is how the workflow is discovered, shared, and permissioned.
A useful Claude skill solves one recurring engineering job, is easy to inspect, and saves more time than it creates in setup and review.
Claude skills can live in your Claude account, your local Claude Code setup, or a repository. Install them where the sessions that need them can load them.
Build a portable AI agent skill from one repeatable job: a precise description, concise instructions, focused resources, and tests that prove it works.
AI agent skills package instructions, scripts, references, and templates into portable folders an agent loads only when the task calls for them.
AI made publishing cheap, which is exactly the problem. What separates a page worth ranking from a competent summary of the first ten results.
A prompt that works once isn't a quality system. Five cases, an observable rubric, and a regression set will tell you whether a change helped.
One character of YAML, four pods that never started, and two safety nets I didn't know were holding. Every restart is an audit. Schedule them before they schedule you.
"Verify your work" isn't an instruction. It's a mood. Here's the version that's an instruction. Verify with a different mechanism than the one that made the claim.
A prompt that works once may still fail in production. A lightweight eval set gives you repeatable cases, a clear rubric, and a way to see whether a prompt change actually improved the workflow.
The best AI tool is not the one with the longest feature list. It is the one that solves a defined job reliably, fits the workflow, handles data appropriately, and remains useful after the novelty wears off.
Use AI to speed research without losing trust. Learn to find primary sources, verify claims, preserve uncertainty, and keep an auditable source trail.
Better prompts aren't magic wording. They're short briefs that hand the model a task, the context it can't infer, the limits, and a quality bar.
A green PR, a controller reporting success, and not one line of the new code running
/merge
Merge
hydra - Merge a worktree branch back into current branch
/parallel
Parallel
hydra - Start multiple agents in parallel across worktrees
/spawn
Spawn
hydra - Start an agent in an existing worktree
/status
Status
hydra - Show detailed status of one or all worktrees
/watch
Watch
hydra - Live monitoring of background agents with status table
/list
List
import - List all cached documentation
/search
Search
import - Search within cached documentation
/update
Update
import - Update cached documentation
/url-or-path
Url or path
import - Fetch URL (via Playwright if blocked) or copy local path to docs/
/highscore
limit:highscore
limit - Display all highscores for all plans
/local-cleanup
marketplace:local-cleanup
marketplace - Restore original plugin version from backup
/local-copy
marketplace:local-copy
marketplace - Install local plugin version for testing (backup original)
/CLAUDE
CLAUDE
<claude-mem-context>
/skmtc-retro-review
Skmtc retro review
Aggregate SKMTC friction log entries into a review — cluster patterns, classify interventions, calculate convergence metrics, produce an action plan
/CLAUDE
CLAUDE
<claude-mem-context>
/skmtc-retro
Skmtc retro
Run a SKMTC retrospective on the current session — capture friction and wins to the friction log
/stats
Stats
CoalMine measurement dashboard — canary activity this session + rule-freshness status across the project's rules home
/update
Update
CoalMine self-update — check for a newer CoalMine version and offer to apply it, or set how updates are handled
/stats
Stats
CoalMine measurement dashboard — canary activity this session + rule-freshness status across the project's rules home
/update
Update
CoalMine self-update — check for a newer CoalMine version and offer to apply it, or set how updates are handled
Make any song you can imagine
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