feat(neo): guide skill lifecycle tool workflow

Add explicit Neo lifecycle instructions to the main agent prompt so
skill creation and updates follow payload -> candidate -> promotion
instead of direct local folder writes.

Clarify lifecycle tool descriptions and parameter semantics, including
skill_key/source_execution_ids usage and stable release sync_to_local
behavior, to reduce ambiguity and improve consistent skill publishing.

Author: RC-CHN

astrbot/core/astr_main_agent.py

@@ -840,6 +840,18 @@ def _apply_sandbox_tools(
             "Example: use `baidu_homepage.png` instead of `/workspace/baidu_homepage.png`.\n"
         )
 
+        req.system_prompt += (
+            "\n[Neo Skill Lifecycle Workflow]\n"
+            "When user asks to create/update a reusable skill in Neo mode, use lifecycle tools instead of directly writing local skill folders.\n"
+            "Preferred sequence:\n"
+            "1) Use `astrbot_create_skill_payload` to store canonical payload content and get `payload_ref`.\n"
+            "2) Use `astrbot_create_skill_candidate` with `skill_key` + `source_execution_ids` (and optional `payload_ref`) to create a candidate.\n"
+            "3) Use `astrbot_promote_skill_candidate` to release: `stage=canary` for trial; `stage=stable` for production.\n"
+            "For stable release, set `sync_to_local=true` to sync `payload.skill_markdown` into local `SKILL.md`.\n"
+            "Do not treat ad-hoc generated files as reusable Neo skills unless they are captured via payload/candidate/release.\n"
+            "To update an existing skill, create a new payload/candidate and promote a new release version; avoid patching old local folders directly.\n"
+        )
+
         # Determine sandbox capabilities from an already-booted session.
         # If no session exists yet (first request), capabilities is None
         # and we register all tools conservatively.

astrbot/core/computer/tools/neo_skills.py

@@ -155,15 +155,19 @@ async def call(
 @dataclass
 class CreateSkillPayloadTool(NeoSkillToolBase):
     name: str = "astrbot_create_skill_payload"
-    description: str = "Create a generic skill payload and return payload_ref."
+    description: str = (
+        "Step 1/3 for Neo skill authoring: create immutable payload content and return payload_ref. "
+        "Use this to store skill_markdown and structured metadata; do NOT write local skill folders directly."
+    )
     parameters: dict = field(
         default_factory=lambda: {
             "type": "object",
             "properties": {
                 "payload": {
                     "anyOf": [{"type": "object"}, {"type": "array"}],
                     "description": (
-                        "Skill payload JSON. Recommended fields: skill_markdown, commands, meta."
+                        "Skill payload JSON. Typical schema: {skill_markdown, inputs, outputs, meta}. "
+                        "This only stores content and returns payload_ref; it does not create a candidate or release."
                     ),
                 },
                 "kind": {
@@ -221,18 +225,31 @@ async def call(
 @dataclass
 class CreateSkillCandidateTool(NeoSkillToolBase):
     name: str = "astrbot_create_skill_candidate"
-    description: str = "Create a skill candidate from source execution IDs."
+    description: str = (
+        "Step 2/3 for Neo skill authoring: create a candidate by binding execution evidence "
+        "(source_execution_ids) with skill identity (skill_key) and optional payload_ref."
+    )
     parameters: dict = field(
         default_factory=lambda: {
             "type": "object",
             "properties": {
-                "skill_key": {"type": "string"},
+                "skill_key": {
+                    "type": "string",
+                    "description": "Stable logical identifier, e.g. image-collage-9grid.",
+                },
                 "source_execution_ids": {
                     "type": "array",
                     "items": {"type": "string"},
+                    "description": "Execution evidence IDs captured from sandbox history.",
+                },
+                "scenario_key": {
+                    "type": "string",
+                    "description": "Optional scenario namespace for grouping candidates.",
+                },
+                "payload_ref": {
+                    "type": "string",
+                    "description": "Optional payload reference created by astrbot_create_skill_payload.",
                 },
-                "scenario_key": {"type": "string"},
-                "payload_ref": {"type": "string"},
             },
             "required": ["skill_key", "source_execution_ids"],
         }
@@ -338,7 +355,10 @@ async def call(
 @dataclass
 class PromoteSkillCandidateTool(NeoSkillToolBase):
     name: str = "astrbot_promote_skill_candidate"
-    description: str = "Promote one candidate to release stage (canary/stable)."
+    description: str = (
+        "Step 3/3 for Neo skill authoring: promote candidate to canary/stable release. "
+        "If stage=stable and sync_to_local=true, payload.skill_markdown is synced to local SKILL.md automatically."
+    )
     parameters: dict = field(
         default_factory=lambda: {
             "type": "object",
@@ -351,7 +371,10 @@ class PromoteSkillCandidateTool(NeoSkillToolBase):
                 },
                 "sync_to_local": {
                     "type": "boolean",
-                    "description": "When stage is stable, sync payload.skill_markdown to local SKILL.md.",
+                    "description": (
+                        "Only used with stage=stable. true means sync payload.skill_markdown to local SKILL.md; "
+                        "false means release remains Neo-side only."
+                    ),
                     "default": True,
                 },
             },