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ed-ai-teammate
AI Teammate - manage connectors (PagerDuty, Slack, GitHub, ...), update teammates (agents) and view teammate activity.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
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AI Teammate - manage connectors (PagerDuty, Slack, GitHub, ...), update teammates (agents) and view teammate activity.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Pipelines - fleet management, config changes, version history, deployments and live capture.
Dashboards - create, update, inspect and validate metric dashboards from the CLI.
Cross-signal incident investigation workflow - from alert to root cause using events, patterns, logs, metrics, traces and pipeline history.
Metrics - discover metric names and run aggregation queries (timeseries and tables).
Monitors - create, manage, snooze and resolve Edge Delta monitors and alerts.
Primary Edge Delta CLI - edx commands, authentication, output formats and conventions.
| name | ed-ai-teammate |
| description | AI Teammate - manage connectors (PagerDuty, Slack, GitHub, ...), update teammates (agents) and view teammate activity. |
| metadata | {"version":"1.0.0","author":"edgedelta","repository":"https://github.com/edgedelta/agent-skills","tags":"edgedelta,ai,teammate,connectors","alwaysApply":"false"} |
The AI Teammate ingests signals from connected tools (PagerDuty, Slack, GitHub, ...) and acts on them. This skill manages those connectors and inspects teammate activity.
The edx CLI must be installed and authenticated. See the ed-edx skill.
edx ai connectors list # configured connectors
edx ai connectors specs # available connector types + required fields
edx ai connectors environments # where connectors can run
edx ai activity --lookback 24h # teammate activity metrics
edx ai agents list # AI Teammates (agents); alias: edx ai teammates
edx ai agents get <agent-id> # a single teammate's full definition
edx ai agents update prompts for confirmation unless --yes.
Use the --*-prompt flags — each takes an inline string or @file (@- for
stdin). The command reads the current teammate, backfills whichever prompt you
did not pass (the service requires both masterPrompt and userPrompt on every
update), and sends only the prompts. Model, temperature, tools and everything
else are left untouched, so you never deal with model-tuning validation:
edx ai agents update <id> --master-prompt @master.md --user-prompt @user.md
edx ai agents update <id> --master-prompt "You are a concise SRE assistant."
Like edx monitors update: fetch, edit the JSON, apply it back.
edx ai agents get <agent-id> > agent.json # edit fields under "data":
# model, toolConfigurations,
# connectors, priority, ...
edx ai agents update <agent-id> --file agent.json
The whole get envelope is accepted and unwrapped automatically. Only the
fields you include are changed; a field set to null is cleared. Use
-f/--file - to read from stdin. Note: re-sending the full object re-validates
model-tuning fields (model, modelTemperature) even if untouched — to change
only prompts prefer the flags above, or send just the prompt fields:
edx ai agents get <id> | jq '.data | {masterPrompt,userPrompt,toolingPrompt}' \
| edx ai agents update <id> --file - --yes
edx ai connectors specs --output json | jq '.[] | select(.type=="pagerduty")'
Build the request JSON per the spec (type, name, credentials/settings).
Apply it:
edx ai connectors update --file connector.json
Connector data flows through an ingestion pipeline that Edge Delta provisions
automatically; check it with edx pipelines list --keyword ai.
The delete request body identifies the connector (same shape as update):
edx ai connectors delete --file connector.json --yes
| Problem | Fix |
|---|---|
| Connector not ingesting | edx pipelines list --keyword ai then edx health problems |
| Unknown required fields | edx ai connectors specs is the source of truth |
| Credential errors | Re-apply with edx ai connectors update --file and fresh secrets |
| Teammate update rejected (4xx) | Re-fetch with edx ai agents get <id>, edit only the data fields, re-apply |