systemprompt-agent 0.20.0

Agent-to-Agent (A2A) protocol for systemprompt.io AI governance: streaming, JSON-RPC models, task lifecycle, .well-known discovery, and governed agent orchestration.
Documentation 
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//! Lightweight directory record summarising an agent for listing surfaces.

use crate::models::a2a::{AgentCard, AgentSkill};
use serde::{Deserialize, Serialize};
use systemprompt_identifiers::AgentId;
use systemprompt_models::services::PluginComponentRef;

#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct AgentInfo {
    pub agent_id: AgentId,
    pub card: AgentCard,
    pub enabled: bool,
    pub skills: Option<Vec<AgentSkill>>,
    pub mcp_servers: Option<PluginComponentRef>,
}

impl AgentInfo {
    pub const fn from_repository_data(agent_id: AgentId, card: AgentCard, enabled: bool) -> Self {
        Self {
            agent_id,
            card,
            enabled,
            skills: None,
            mcp_servers: None,
        }
    }

    pub const fn from_card(agent_id: AgentId, card: AgentCard, enabled: bool) -> Self {
        Self {
            agent_id,
            card,
            enabled,
            skills: None,
            mcp_servers: None,
        }
    }

    pub fn id(&self) -> &str {
        self.agent_id.as_str()
    }

    pub fn name(&self) -> &str {
        &self.card.name
    }

    pub fn endpoint(&self) -> &str {
        self.card.url().unwrap_or("")
    }

    pub fn version(&self) -> &str {
        &self.card.version
    }

    pub fn with_skills(mut self, skills: Vec<AgentSkill>) -> Self {
        self.skills = Some(skills);
        self
    }

    pub fn with_mcp_servers(mut self, servers: PluginComponentRef) -> Self {
        self.mcp_servers = Some(servers);
        self
    }

    pub fn skills_count(&self) -> usize {
        self.skills.as_ref().map_or(0, Vec::len)
    }

    pub fn mcp_count(&self) -> usize {
        self.mcp_servers.as_ref().map_or(0, |r| r.include.len())
    }
}