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 first-tree-writegit 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/first-tree-write)<a href="https://agentmods.dev/skills/first-tree-ai/first-tree/first-tree-write"><img src="https://agentmods.dev/badge/skills/first-tree-ai/first-tree/first-tree-write/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/first-tree-write"><img src="https://agentmods.dev/badge/skills/first-tree-ai/first-tree/first-tree-write.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 | $0.00062 | $0.00918 |
| Opus 5.5 | $0.00025 | $0.00367 |
| Sonnet 5.5 | $0.00012 | $0.00184 |
| Haiku 4.5 | $0.00006 | $0.00092 |
Grade A, and why
first-tree-write 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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
First Tree Write — Local Context
Purpose and authority
Reflect a concrete source artifact into the current Agent's private Local
Context. This payload is the managed Local variant of first-tree-write; its
public name and routing description intentionally match the Remote payload.
Local Context is not Team-approved truth and has no Git, forge, PR/MR, Reviewer, Audit, Seed, Cloud Tree IO, or Web workflow. Any current Chat, human decision, design document, PR/MR, Issue, meeting note, or other inspectable material can be a source. Never manufacture organization facts from model memory. The generated Context Tree Policy remains the content-model baseline.
Source gate and Double Test
Write only when the source establishes or changes a durable decision, constraint, ownership fact, or cross-domain relationship. It must both matter to future choices and remain true if the triggering implementation is rewritten. Implementation detail, refactors, request shapes, fixtures, build configuration, and one-off fixes stay in their source system.
If nothing passes, write nothing and explain why.
Workflow
-
Identify the exact source, smallest existing target, parent, relevant normal
soft_links, and ownership-adjacent member content. New top-level domains,ownerschanges, anddecisionLocksCodechanges still require explicit human-owner authority. -
Run:
<firstTreeInvocation> --json tree local resolve --ensure --intent writeUse only the returned
data.path. The guard accepts no caller path and rechecks runtime identity, fixed containment, limits, latch, and Server binding.repairOnly: truemeans the live Tree is invalid: repair existing mechanically provable content before any expansion. If correct business content cannot be determined from the files and source, stop and ask a human; do not delete or invent facts just to pass validation. -
Read the source and surrounding live Tree. Then edit the live root directly with native file tools. Do not create a lock, snapshot, candidate, fingerprint, worktree, journal, rollback state, approval diff, commit, or PR/MR. Local V0 accepts last-write-wins and moving reads.
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.
- 1mo ago First seen · 96 lines · 62 tokens per session scan A b85179178d3a
first-tree-write is a skill published in the GitHub repository first-tree-ai/first-tree (157 stars, last pushed 8d ago), licensed Apache-2.0. It adds 62 tokens to every session and 918 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.
Other skills, from other repositories
first-tree-sync
Audit and repair drift between merged code and the Context Tree in both directions — tree→code (does code still support tree facts?) and code→tree (does the tree register everything code now contains?). Use when the tree may be stale, wrong, outdated, or missing coverage for recent code changes; after a large merge…
first-tree-write
Write Context Tree updates from explicit source material — code PRs, design docs, meeting notes, raw text. Use when the user gives you a concrete source and wants the right durable tree change drafted, linked, and reviewed. This skill is source-driven and targeted; use first-tree-sync instead for broad drift audits…
first-tree
Canonical whitepaper and routing skill for First Tree. Explains what belongs in a Context Tree, how source or workspace roots, tree repos, and bindings relate, and how the current first-tree tree and first-tree github scan surfaces fit together. Use when you need shared First Tree concepts, need to choose between…
mnemon
Persistent memory CLI for LLM agents. Store facts, recall past knowledge, link related memories, manage lifecycle.
mnemon
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mnemon
Persistent memory for MiniMax Code. Recall durable context, store important facts and decisions, and link related memories with the mnemon CLI.