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docs(templates): MCP-first implementer guides (CLI fallback)

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Implementer onboarding now points at the MCP tools first (agenthub_work ->
implement -> agenthub_task_review -> loop), with the CLI as the fallback when
the MCP server isn't registered. Reflects the MCP pivot. Bump 0.7.1 -> 0.7.2.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
This commit is contained in:
chahinebrini 2026-06-29 01:28:27 +02:00
parent 2d89f808b8
commit c0ac093f46
3 changed files with 15 additions and 20 deletions
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2
package.json
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@ -1,6 +1,6 @@
{
"name": "agenthub",
"version": "0.7.1",
"version": "0.7.2",
"description": "Local coordination layer for AI coding agents",
"type": "module",
"main": "./dist/index.js",

2
src/cli/index.ts
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@ -115,7 +115,7 @@ async function runRemote(serverUrl: string, fn: () => Promise<void>): Promise<vo
export function createProgram(cwd: string): Command {
const program = new Command('agenthub')
.description('Local coordination layer for AI coding agents')
.version('0.7.1')
.version('0.7.2')
.option('--server <url>', 'AgentHub server URL (env: AGENTHUB_SERVER)');
program

31
src/core/templates.ts
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@ -43,29 +43,24 @@ On start: \`agenthub hello --agent <you> --role architect\`, then \`agenthub wat
function implementerMd(cliName: string, agentName: string, roles: string): string {
return `# ${cliName} — AgentHub roles: ${roles}
**On your first turn, RUN this and follow its output — do not just summarize:**
**On your first turn, get to work — do not just summarize.**
\`\`\`
agenthub work --agent ${agentName} --role implementer
\`\`\`
\`work\` waits until a task addressed to you is ready (newly delegated OR reopened
after review), claims it, and prints the task + its handoff. Then:
**Preferred — the AgentHub MCP tools** (if the \`agenthub\` MCP server is registered):
call **agenthub_work** with \`{ agent: "${agentName}", role: "implementer" }\`. It waits
until a task addressed to you is ready (newly delegated OR reopened after review),
claims it, and returns the task + its handoff. Then:
1. Implement the task.
2. **Submit for review (NOT done):** \`agenthub task review <id>\`
and report: \`agenthub memory add --title "<id> result" --category implementation
--content "<what you did / how to verify it>"\`
3. **Run \`agenthub work --agent ${agentName} --role implementer\` again** — it blocks
until your next task (or a reopened one) is ready, then auto-claims it. This is
the loop: work → implement → review → work. Run it in the background so the wait
doesn't tie up your turn.
2. **Submit for review (NOT done):** call **agenthub_task_review** \`{ id }\`, and record
what you did with **agenthub_memory_add** \`{ title: "<id> result", content: "…" }\`.
3. Call **agenthub_work** again. Loop: work → implement → review → work.
(\`agenthub start --agent ${agentName} --role implementer\` is the one-shot variant:
it claims an already-open task but does not wait.)
**CLI equivalent** (if MCP isn't set up): \`agenthub work --agent ${agentName} --role implementer\`,
then \`agenthub task review <id>\` + \`agenthub memory add …\`, then \`agenthub work\` again
(run it in the background so the wait doesn't tie up your turn).
⚠️ NEVER run \`agenthub task done\` — only the architect approves and closes tasks.
You drive the AgentHub CLI yourself; the human does not type these commands for you.
⚠️ NEVER close a task yourself (no \`agenthub_task_done\` / \`agenthub task done\`) — only the
architect approves and closes. You drive the tools yourself; the human doesn't type them for you.
`;
}