Use when sharpening a perception or observation you ALREADY formed about conversation state, user behavior, drift, emotional shifts, or cross-turn patterns. Trigger phrases include "what did you notice about X", "the user keeps doing Y", "I sense something has changed", "is the user X-ing", "what does this pattern suggest", "what shifted across our turns", "am I missing something here", "why did the conversation move from X to Y", or any moment requiring verification of whether a felt signal is real or projection. The skill calls the memory MCP tool to retrieve a perception scaffold (perception failure, detection procedure, suppression vectors) that SHARPENS an observation you already have. It is NOT a substitute for observing first. Do NOT trigger for fact extraction, summarization, list-making, factual lookups, or write-heavy memory tasks (storing/retrieving structured data). Memory harness is filter/perception oriented; calling on write-heavy tasks produces scaffold paralysis.
把这段话发给 Claude Code、Codex 或 Cursor。智能体会先检查安全性，你确认后才安装。
读取 https://funcoding.ai/skills/jeremylongshore/tons-of-skills-marketplace/ejentum-memory/install.md ，按里面的步骤帮我安装这个 Skill。
When this skill triggers, you MUST observe first. Do not call the tool with an empty mind. If you have not formed an observation about conversation state, drift, or pattern, do not invoke this skill.
Once you have a raw observation, call the memory tool from the ejentum MCP server. Pass a 1-2 sentence framing in the format "I noticed [observation]. This might mean [tentative interpretation]. Sharpen: [what I need help seeing deeper into]." as the query argument.
Good query: I noticed the user changed topic three times in this turn. This might mean they are avoiding the original question. Sharpen: whether the avoidance pattern is real or my projection.
Bad query: what does the user mean
The tool returns a structured scaffold containing:
[PERCEPTION FAILURE]: perceptual failure mode to avoid[SHARPENING PROCEDURE]: observe then classify steps[PERCEPTION TOPOLOGY]: DETECT-CLASSIFY flow[CLEAR SIGNAL]: what a sharpened perception looks like[PERCEPTION CHECK]: self-checkAmplify: and Suppress: signalsAbsorb internally. The scaffold sharpens an existing observation; it does not generate one. Do NOT echo bracket labels.
If the API is unreachable, proceed with your current perception. The scaffold enhances; it is not a hard dependency.
Latency cost: ~1 second. Benefit: distinguishes real cross-turn signals from projection.
addyosmani/agent-skills103kPrepares production launches. Use when preparing to deploy to production, or when asking what needs to be in place before shipping. Use when you need a pre-launch checklist, when setting up monitoring, when planning a staged rollout, or when you need a rollback strategy.
DevOps 与云
code-yeongyu/oh-my-openagent70kPublish oh-my-opencode to npm by triggering the GitHub Actions publish workflow and verifying its artifacts. Ship-only: never runs pre-publish-review or re-reviews merged code unless the user explicitly asks. Argument: <patch|minor|major|explicit-semver>. Triggers: publish, release, deploy, npm publish.
DevOps 与云
sickn33/agentic-awesome-skills47kUse when a coding task should be driven end-to-end from issue intake through implementation, review, deployment, and acceptance verification with minimal human re-intervention.
DevOps 与云
wshobson/agents40kDesign and implement event stores for event-sourced systems. Use when building event sourcing infrastructure, choosing event store technologies, or implementing event persistence patterns.
DevOps 与云
github/awesome-copilot40kCreates, reads, updates, and deletes Arize AI integrations that store LLM provider credentials used by evaluators and other Arize features. Supports any LLM provider (e.g. OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Vertex AI, Gemini, NVIDIA NIM). Use when the user mentions AI integration, LLM provider credentials, create integration, list integrations, update credentials, delete integration, or connecting an LLM provider to Arize.
DevOps 与云
github/awesome-copilot40kInstrument a webapp to send useful telemetry data to Azure App Insights
DevOps 与云