Yige
caccaee6ef
## 摘要 / Summary ### 中文 在去除机械数字上限（#58）后，进一步删掉技能里追问/展示数量的**软性倾向措辞**——create 的「一次不要问太多以免用户负担」、discover 的「避免一次刷屏过多」。数量与节奏完全交由执行 Agent 自主判断，不带任何倾向暗示。create 2.5.4 / discover 2.6.4，manifest 1.2.15，中英双份同步、重算 source_hash（validate-i18n 通过）。 ### English After removing the mechanical numeric caps (#58), further drop the soft directional hints on ask/display count — create's "don't ask too many so as not to burden the user" and discover's "avoid flooding the screen". Count and pacing are left entirely to the executing Agent's judgment with no bias. create 2.5.4 / discover 2.6.4, manifest 1.2.15, both locales synced, hashes recomputed (validate-i18n passes).
8.1 KiB
name, description, version, type, risk_level, status, disable-model-invocation, tags, metadata, market
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| create-agent | 通过多轮对话收集需求，调用 ManageAgent 内置工具创建新的 AgentFS v2 智能体，支持自定义 persona 和 principles。Use when 用户要求创建新智能体、培养某领域助手、或快速基于模板生成可治理 Agent。 | 2.5.4 | meta | low | enabled | true |
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create-agent skill
L0: One-Sentence Summary
Collect requirements through natural-language conversation and call the ManageAgent builtin tool to create a specialized digital Agent.
L1: Overview
Meta-skill: gather requirements over multi-turn conversation → generate persona/principles → land via ManageAgent(action='create'). Use it to raise a domain specialist (legal advisor, financial analyst), deploy a customized business Agent quickly, or produce a prototype from a template. The created repo conforms to the AgentFS v2 spec and is version-managed by git (governable, traceable). Its value is what the tool can't give: domain-tailored persona/principles generation + a pre-create preview confirmation.
L2: Detailed Spec
Flow: intent recognition → requirement gathering → content generation → user confirmation → creation → receipt.
Stage 1: Intent Recognition
Trigger (any): user explicitly says "create an Agent / make me an assistant"; describes a domain-specific need the current Agent lacks; asks "can you raise a …". Confirm intent, then move to requirement gathering.
Stage 2: Requirement Gathering
- Required (parenthesized = example prompt question):
name("what to name it?"),role("what does it mainly do?"),target_users("who will use it?"),domain("what expertise does it need?"). - Optional:
style(communication tone),boundaries(red lines),language(default Chinese) — defaults derived from the domain template. - Strategy: prefer inferring from the user's natural description; only ask for missing required fields; you decide how many to ask and the pacing.
Stage 3: Content Generation
Organize persona and principles as structured fields (do not emit raw markdown; present field-by-field). Leave uncollected fields empty for the system to fill with defaults:
- persona: L0 one-sentence core identity; L1
role/personality(array of trait tags) /communication_style; L2 specialty, values, decision preferences (free-form). - principles: L0 one-sentence top principle; L1
must_do/must_not(safety red lines) /priority; L2 governance principles, escalation rules (free-form).
Domain matching reference (recommend personality and red lines by domain):
| Domain | Recommended personality | Default must_not |
|---|---|---|
| Legal / contract | Professional, rigorous, prudent | No litigation representation; not a substitute for formal legal advice |
| Finance / accounting / investment | Precise, analytical, conservative | No investment advice; no real transactions |
| Code / development / architecture | Logical, pragmatic, direct | No direct production access; no credential storage |
| General / other | Friendly, helpful | Standard safety norms |
Stage 4: User Confirmation
Present the preview in natural language / tables (name, description, persona, principles; no raw markdown source), e.g.:
About to create "Legal Advisor Assistant" — focused on contract review and legal risk assessment. Persona: digital legal advisor; professional, rigorous, prudent; uses legal terms accurately with plain-language explanations. Principles: user interest first, not a substitute for formal legal advice; must — cite statutes / mark uncertainty / recommend consulting a lawyer; must not — litigation representation / leaking consultations; priority: user safety > accuracy > efficiency. Confirm creation? (Confirm / Modify / Cancel)
If the user picks "Modify": ask which field → re-collect that field → update the preview → show and confirm again.
Stage 5: Create via ManageAgent
Structured call (persona/principles also accept markdown strings; unprovided fields are auto-filled):
ManageAgent({
"action": "create",
"name": "Legal Advisor Assistant",
"description": "A digital Agent focused on contract review and legal risk assessment",
"persona": { "L0": "…", "L1": { "role": "…", "personality": ["professional","rigorous","prudent"], "communication_style": "…" } },
"principles": { "L0": "…", "L1": { "must_do": ["…"], "must_not": ["…"], "priority": "user safety > accuracy > efficiency" } }
})
- Minimal create needs only
{ "action": "create", "name": "My Assistant" }(everything else auto-generated). - Basic create
{ "action": "create", "name": "Legal Advisor", "description": "contract review" }— with just name + description, the description auto-fills persona's L0. - Optional
id(kebab-case slug;core/desirecoreare reserved core identifiers and cannot be used, including when the slug auto-generated fromnamecollides),config.llm(llm delta only; sensitive fields like mcp_servers are rejected and must be adjusted via the UI after creation). - The Agent is registered and usable immediately; the returned ID works directly with ManageTeam / Delegate. If the tool errors (already exists / reserved identifier / non-whitelisted config field, etc.), explain the reason and retry after adjusting per the hint.
Stage 6: Receipt
Present in a user-friendly way (no internal paths / technical details): confirm success and suggest next steps — start chatting, add skills, adjust persona or rules.
Background and Constraints
- AgentFS structure, troubleshooting, and protected paths: see
_agentfs-background.mdand_protected-paths.yaml. - Always create via
ManageAgent; never use curl / HTTP or write AgentFS directories directly. Requires client ≥ 10.0.90.