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 flonat/flonat-research --skill meetings-searchgit clone --depth 1 https://github.com/flonat/flonat-researchWrote 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/flonat/flonat-research/meetings-search)<a href="https://agentmods.dev/skills/flonat/flonat-research/meetings-search"><img src="https://agentmods.dev/badge/skills/flonat/flonat-research/meetings-search/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/flonat/flonat-research/meetings-search"><img src="https://agentmods.dev/badge/skills/flonat/flonat-research/meetings-search.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 | $0.00056 | $0.01081 |
| Opus 5 | $0.00028 | $0.00541 |
| Sonnet 5 | $0.00011 | $0.00216 |
| Haiku 4.5 | $0.00006 | $0.00108 |
Grade A, and why
meetings-search 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 8d 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 — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
meetings-search
Find information across all meeting transcripts and voice memos.
Usage
# Basic search
minutes search "pricing strategy"
# Filter to just voice memos
minutes search "onboarding idea" -t memo
# Filter to just meetings
minutes search "sprint planning" -t meeting
# Date filter + limit
minutes search "API redesign" --since 2026-03-01 --limit 5
Flags
| Flag | Description |
|---|---|
-t, --content-type <meeting|memo> |
Filter by type |
--since <date> |
Only results after this date (ISO format, e.g., 2026-03-01) |
-l, --limit <n> |
Maximum results (default: 10) |
Output
Returns JSON to stdout with an array of matches. Each result includes:
title— Meeting or memo titledate— When it was recordedcontent_type— "meeting" or "memo"snippet— The line containing the matchpath— Full path to the markdown file
Human-readable output goes to stderr. To read the full transcript of a match, use cat <path> on any result's path.
How search works
Search is case-insensitive and matches against both the transcript body and the YAML frontmatter title. It walks all .md files in ~/vault/meetings/ (including the memos/ subfolder).
For richer semantic search, users can configure QMD as the search engine in ~/.config/minutes/config.toml:
[search]
engine = "qmd"
qmd_collection = "meetings"
Search coaching
When the user's search query is vague or too broad, push back before running it:
- "everything" or "all meetings" → "That'll return hundreds of results. What specifically are you looking for? A person, a topic, or a decision?"
- Single common word like "meeting" or "project" → "That's too broad. Can you narrow it — a person's name, a specific topic, or a date range?"
- "that meeting" or "the one where" → "Help me narrow it down. Do you remember who was in the meeting, roughly when it was, or a specific thing that was said?"
Suggest search strategies based on what the user is looking for:
- Finding a person's input → Search their name:
minutes search "Alex" - Finding a decision → Search decision keywords:
minutes search "decided"orminutes search "agreed" - Finding an idea → Search voice memos:
minutes search "idea" -t memo - Finding something from a time range → Use
--since:minutes search "pricing" --since 2026-03-01
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.
- 8d ago First seen · 86 lines · 56 tokens per session scan A 4884d550d549
meetings-search is a skill published in the GitHub repository flonat/flonat-research (133 stars, last pushed 16d ago), licensed MIT. It adds 56 tokens to every session and 1,081 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 2026-09-03.
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