Hope Agent is a cross-device personal AI assistant that remembers context, uses tools, and continues working toward goals through dynamically organized workflows. Individuals use it from desktop, web, server, or messaging environments to manage projects, knowledge, designs, and long-running tasks. The catalogue add-ons extend its agent workflows and capabilities.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add shiwenwen/hope-agent --skill ha-multi-agent-codinggit clone --depth 1 https://github.com/shiwenwen/hope-agentWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/shiwenwen/hope-agent/ha-multi-agent-coding)<a href="https://agentmods.dev/skills/shiwenwen/hope-agent/ha-multi-agent-coding"><img src="https://agentmods.dev/badge/skills/shiwenwen/hope-agent/ha-multi-agent-coding/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/shiwenwen/hope-agent/ha-multi-agent-coding"><img src="https://agentmods.dev/badge/skills/shiwenwen/hope-agent/ha-multi-agent-coding.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00045 | $0.00751 |
| Opus 5.5 | $0.00018 | $0.00300 |
| Sonnet 5.5 | $0.00009 | $0.00150 |
| Haiku 4.5 | $0.00005 | $0.00075 |
Grade A, and why
ha-multi-agent-coding scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Hope Multi-Agent Coding
Use multiple Agents when parallel evidence or implementation meaningfully outweighs coordination cost. Do not make delegation the default for complex-looking work.
Fan-Out Decision
Good candidates:
- Similar independent investigations across modules.
- Distinct review angles with a shared structured output.
- Independent implementations with non-overlapping ownership.
- A bounded set of alternatives that the main Agent will compare.
Keep work with one Agent when:
- The task is small or one search path is likely sufficient.
- Steps depend on prior results.
- Agents would edit the same files or shared generated state.
- A single broad investigation needs coherent context.
- Coordination, token, or merge cost exceeds expected parallel gain.
Define Each Child Contract
Provide:
- One concrete objective and bounded scope.
- Relevant context already known by the parent.
- Allowed and forbidden actions.
- File ownership or read-only isolation.
- Required output schema, evidence, and stop condition.
- Verification expected from the child.
Do not re-delegate the entire parent assignment to one child. Children do not own final user communication or Goal closure.
Isolation
- Prefer
shared_read_onlyfor research, discovery, and verification. - Use separate worktrees for independent writes.
- If writes cannot be isolated, serialize them or assign mutually exclusive file ownership.
- Permission mode, protected paths, approval surfaces, and tool restrictions remain runtime-enforced. A child prompt cannot grant access.
Bounded Execution
Set explicit limits for fan-out count, depth, turns, tokens, and time. Respect runtime queues and backpressure. Never recursively create Workflow runs or an unbounded Agent tree.
Progressive Control
The main Agent may choose based on task needs:
- Consume the first useful results and adapt (
waitAny/ checkpoint). - Query status without consuming output.
- Read one structured result, then steer or cancel remaining work.
- Add a follow-up child when new evidence changes the decomposition.
- Wait for all children only when a true barrier is required.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 97 lines · 45 tokens per session scan A 312520db42e3
ha-multi-agent-coding is a skill published in the GitHub repository shiwenwen/hope-agent (1,858 stars, last pushed today), licensed MIT. It adds 45 tokens to every session and 751 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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