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 agentmods add commands/goal-t/goaltree/startgit clone --depth 1 https://github.com/GOAL-T/goaltreeWrote 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/commands/goal-t/goaltree/start)<a href="https://agentmods.dev/commands/goal-t/goaltree/start"><img src="https://agentmods.dev/badge/commands/goal-t/goaltree/start.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00023 | $0.00386 |
| Opus 5 | $0.00012 | $0.00193 |
| Sonnet 5 | $0.00005 | $0.00077 |
| Haiku 4.5 | $0.00002 | $0.00039 |
Grade A, and why
start 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 3d 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.
What it actually says
Build a GoalT goal tree for the current project.
- Figure out the absolute path of the project root (the current working directory, unless told otherwise).
- Explore the codebase before inventing any structure: read the README if one exists, the package manifest (package.json / pyproject.toml / etc.), the top-level folder layout, and -- if present -- database migration files or a schema definition (e.g. a
supabase/migrationsfolder, a Prisma schema, a Django models file). - From what you actually find, identify the project's real functional areas (e.g. authentication, payments, a specific feature area) -- don't guess generic categories that don't match this codebase.
- Call
create_treewith a root_label describing the project andproject_rootset to the absolute path from step 1. - Call
add_goalfor each functional area you identified, writing a genuine one-or-two-sentence description of what it does in this specific codebase. Where you can confidently identify the files that implement it, pass them asrelated_files(paths relative to project_root). Where relevant backend artifacts exist (database tables, edge functions, API routes), pass them asrelated_backend. - If some goals genuinely depend on or serve more than one parent area, give them multiple parents -- don't force everything into a single-parent tree if the real structure isn't like that.
- Once the tree is built, call
open_dashboardand tell the user it's ready, briefly summarizing what you found.
Do not fabricate files or backend artifacts you haven't actually seen -- it's fine, and expected, for some goals to have no related_files yet if you're not confident about the mapping. Leave those empty rather than guessing.
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.
- 3d ago First seen · 16 lines · 23 tokens per session scan A f971d8db3705
start is a command published in the GitHub repository GOAL-T/goaltree (0 stars, last pushed 21d ago), licensed Apache-2.0. It adds 23 tokens to every session and 386 once invoked, about $0.0001 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 2026-08-31.
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