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 first-tree-ai/first-tree --skill meeting-to-treegit clone --depth 1 https://github.com/first-tree-ai/first-treeWrote 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/first-tree-ai/first-tree/meeting-to-tree)<a href="https://agentmods.dev/skills/first-tree-ai/first-tree/meeting-to-tree"><img src="https://agentmods.dev/badge/skills/first-tree-ai/first-tree/meeting-to-tree/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/first-tree-ai/first-tree/meeting-to-tree"><img src="https://agentmods.dev/badge/skills/first-tree-ai/first-tree/meeting-to-tree.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 | $0.00000 | $0.01416 |
| Opus 5 | $0.00000 | $0.00708 |
| Sonnet 5 | $0.00000 | $0.00283 |
| Haiku 4.5 | $0.00000 | $0.00142 |
Grade A, and why
meeting-to-tree 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 10d 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 — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Meeting to Tree
Turn one logical meeting's exact source artifacts into reviewable Context Tree
updates. Use existing readers, First Tree member communication, and
first-tree-write; do not build a parallel reader, confirmation store, or Tree
writer.
Establish the meeting source
- Require at least one concrete meeting artifact and clear intent to update the Context Tree. If either is missing, ask for it and stop.
- Process one logical meeting at a time. When supplied artifacts may belong to different meetings, separate them using explicit source evidence or ask the user to group them.
- Use the environment's ordinary reader for each exact provider document, attachment, local file, or pasted record. For a Feishu source, use the available Feishu reader or CLI; keep provider authorization, download, OCR, parsing, completeness, and revision handling in that reader layer.
- Do not use a calendar, search for related meetings, scan a time window, or follow links embedded in a source to discover adjacent material.
- Preserve the user-declared or document-visible order. If order is unknown, do not infer that one artifact overrides another.
- If an artifact is unreadable or incomplete, identify the gap. When the gap could contain a correction or later decision, do not call the affected point settled.
- Use the exact source through the ordinary reader in the current task. If the reader already provides a transient local file, reuse it. Do not create or retain an additional raw copy solely for this Skill. Never write raw meeting content to the Context Tree, a source repository, or parallel persistent state.
Identify durable Tree candidates
Read the available artifacts in order and identify claims that may change durable team context:
- a decision or explicit non-choice and its surviving rationale;
- a constraint future work must respect;
- a durable ownership or responsibility change;
- a cross-domain relationship.
For every candidate:
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 10d ago First seen · 137 lines · 0 tokens per session scan A 3661f3328bed
meeting-to-tree is a skill published in the GitHub repository first-tree-ai/first-tree (142 stars, last pushed today), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 1,416 tokens. 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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