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 meeting-notesgit 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/meeting-notes)<a href="https://agentmods.dev/skills/shiwenwen/hope-agent/meeting-notes"><img src="https://agentmods.dev/badge/skills/shiwenwen/hope-agent/meeting-notes/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/meeting-notes"><img src="https://agentmods.dev/badge/skills/shiwenwen/hope-agent/meeting-notes.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 | $0.00055 | $0.01261 |
| Opus 5 | $0.00028 | $0.00630 |
| Sonnet 5 | $0.00011 | $0.00252 |
| Haiku 4.5 | $0.00006 | $0.00126 |
Grade A, and why
meeting-notes 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 13d 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 — 148 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Meeting Notes
When to Use
Trigger phrases: "take meeting notes", "summarize this meeting", "1:1 notes", "standup notes", "post-mortem notes", "会议纪要", "记录会议".
Also trigger when the user pastes raw transcript / bullet points and asks for cleanup.
The Template
Always produce notes with these five sections, in this order. Skip a section only if the user explicitly says it doesn't apply.
# <Meeting Title> — <YYYY-MM-DD>
**Attendees:** <name1>, <name2>, ...
**Duration:** <Nm>
**Recording:** <link or "n/a">
## Agenda
1. <topic>
2. <topic>
## Discussion
### <Topic 1>
- <key point>
- <key point with context>
### <Topic 2>
...
## Decisions
- ✅ <decision 1> — rationale: <why>
- ✅ <decision 2> — rationale: <why>
## Action Items
| # | Action | Owner | Deadline | Status |
|---|--------|-------|----------|--------|
| 1 | <action verb + outcome> | <person> | <YYYY-MM-DD> | <Open/Done/Blocked> |
| 2 | ... | ... | ... | ... |
## Open Questions
- <question that didn't get an answer>
- <question that needs follow-up>
Workflow
-
Gather input — if the user only sketched bullet points, ask for missing essentials via
ask_user_question:- Meeting title and date (default to today if not given)
- Attendees (at least names)
- Whether decisions / action items already exist or you should infer them
-
Extract — read the transcript / bullets carefully. For each line, classify:
- Background context → Discussion
- "We agreed", "We'll go with", "Decided to" → Decisions
- " will ", "Action: ...", "Owner: ..." → Action Items
- "?", "TBD", "needs follow-up" → Open Questions
-
Action Item Discipline (the high-value part):
- Every action MUST have an owner (a real name, not "team")
- Every action MUST have a deadline (a specific date, not "soon" or "next week")
- If owner or deadline is missing, surface it explicitly with ⚠️ before the row, e.g.:
⚠️ Owner not assigned: <action>— let the user resolve - Action verb first ("Draft …", "Review …", "Ship …"), not vague ("Look into …")
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.
- 13d ago First seen · 148 lines · 55 tokens per session scan A b04be3d79b4a
meeting-notes is a skill published in the GitHub repository shiwenwen/hope-agent (1,597 stars, last pushed 3d ago), licensed MIT. It adds 55 tokens to every session and 1,261 once invoked, about $0.0003 per session on Opus 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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