Files
TJWaterAgent/.opencode/tools/skill_manager.ts
T

68 lines
2.2 KiB
TypeScript

import { tool } from "@opencode-ai/plugin";
const internalBaseUrl =
process.env.TJWATER_AGENT_INTERNAL_BASE_URL ?? "http://127.0.0.1:8787";
const internalToken = process.env.TJWATER_AGENT_INTERNAL_TOKEN ?? "";
export default tool({
description:
"维护已验证、可复用、非敏感的 workflow 或方法模式。支持 list、write_skill、remove_skill、append_pattern、remove_pattern、write_reference、remove_reference、write_script、remove_script。",
args: {
action: tool.schema
.enum([
"list",
"write_skill",
"remove_skill",
"append_pattern",
"remove_pattern",
"write_reference",
"remove_reference",
"write_script",
"remove_script",
])
.describe("Skill maintenance operation."),
reason: tool.schema
.string()
.describe("Why this skill maintenance action is justified for future reuse."),
skill_path: tool.schema
.string()
.describe(
"Target skill directory path relative to .opencode/skills. Use 'workflow' for the workflow index, or '__root__' for the root skills index.",
),
pattern: tool.schema.string().optional().describe("Pattern text used by append_pattern."),
target_id: tool.schema
.string()
.optional()
.describe("Stable learned pattern id used by remove_pattern."),
file_path: tool.schema
.string()
.optional()
.describe("Asset file path. For references use references/*.md; for scripts use scripts/*.py."),
content: tool.schema
.string()
.optional()
.describe("Content used by write_skill, write_reference, or write_script."),
},
async execute(args, context) {
const response = await fetch(
`${internalBaseUrl}/internal/tools/skill-manager`,
{
method: "POST",
headers: {
"Content-Type": "application/json",
"x-agent-internal-token": internalToken,
},
body: JSON.stringify({
...args,
session_id: context.sessionID,
}),
},
);
const text = await response.text();
if (!response.ok) {
throw new Error(text);
}
return text;
},
});