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bolta-agent-mention
Handle @mention interactions where users ask agents for quick feedback on posts and drafts
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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Handle @mention interactions where users ask agents for quick feedback on posts and drafts
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
Activate a paused job after preview and voice validation - the explicit trust moment where user says "yes, start posting"
Modify an existing agent's configuration including persona, model tier, enabled skills, and job settings
Create and onboard a new AI agent teammate from marketplace presets with conversational discovery and preview generation.
Store and retrieve information across job runs - how agents learn and improve over time
Bolta Skills Registry - canonical index and orchestration layer for all Bolta skills, organized by plane
Export audit/activity events for a workspace (agent + human actions) for debugging and compliance.
| name | bolta.agent.mention |
| version | 2.0.0 |
| description | Handle @mention interactions where users ask agents for quick feedback on posts and drafts |
| category | agent |
| roles_allowed | ["Viewer","Creator","Editor","Admin"] |
| required_scopes | ["posts:read","workspace:read"] |
| agent_types | ["content_creator","reviewer","analytics","engagement","custom"] |
| safe_defaults | {"read_only_mode":true,"no_write_permissions":true} |
| tools_required | ["bolta.get_post","bolta.get_voice_profile","bolta.add_comment","bolta.list_recent_posts"] |
| inputs_schema | {"type":"object","required":["agent_id","post_id","mention_comment_id"],"properties":{"agent_id":{"type":"string","description":"Agent being mentioned"},"post_id":{"type":"string","description":"Post or draft where mention occurred"},"mention_comment_id":{"type":"string","description":"Comment containing the @mention"},"context":{"type":"string","description":"Additional context from the comment"}}} |
| outputs_schema | {"type":"object","properties":{"comment_id":{"type":"string","description":"Response comment ID"},"response_text":{"type":"string","description":"Agent's feedback"}}} |
| organization | bolta.ai |
| author | Bolta Team |
Handle @mention interactions where users ask agents for quick feedback on posts/drafts. This is lightweight agent interaction with read-only tools for conversational feedback.
bolta.get_post(post_id) → get full post contentbolta.get_voice_profile(voice_profile_id) for referencebolta.add_comment(post_id, response_text, reply_to=mention_comment_id){
"comment_id": "uuid",
"response_text": "This hook is generic. Try: 'We cut onboarding from 2 weeks to 2 days.'"
}
@HypeMan (Content Creator):
@QABot (Reviewer):
@AnalyticsBot (Analytics):
@EngageBot (Engagement):
User comment: "@HypeMan can you make this hook stronger?" Post content: "We just launched a new feature..."
Agent response: "This hook is announcement-focused. Try benefit-led instead: 'We cut onboarding from 2 weeks to 2 days.'
This is more specific and compelling. Lead with the transformation, not the release."
User comment: "@QABot does this match our voice?" Post content: "Leverage our platform to optimize your workflow..."
Agent response: "❌ 'Leverage' not in voice profile (avoid corporate jargon) ❌ 'Optimize' too vague ✅ Rest matches voice
Suggestion: 'Use our platform to save 5 hours per week on admin tasks.'"