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.
git clone --depth 1 https://github.com/d-oit/rust-2026-templateWrote 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/d-oit/rust-2026-template/generate-docs)<a href="https://agentmods.dev/commands/d-oit/rust-2026-template/generate-docs"><img src="https://agentmods.dev/badge/commands/d-oit/rust-2026-template/generate-docs/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/commands/d-oit/rust-2026-template/generate-docs"><img src="https://agentmods.dev/badge/commands/d-oit/rust-2026-template/generate-docs.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00000 | $0.00244 |
| Opus 5.5 | $0.00000 | $0.00098 |
| Sonnet 5.5 | $0.00000 | $0.00049 |
| Haiku 4.5 | $0.00000 | $0.00024 |
Grade A, and why
generate-docs 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.
What it actually says
Command: generate-docs
Description
Generates a Rust-scoped symbol inventory to assist agents in understanding the public API surface of the workspace.
Execution Protocol
- Workspace Discovery: Identify all workspace members defined in
Cargo.tomland located incrates/. - Symbol Extraction: For each crate, extract public symbols including:
structandenumdefinitionstraitdefinitions- Public functions (
pub fn) - Associated
///documentation comments
- Documentation Generation:
- Primary output:
docs/symbols/directory. - Create one file per crate:
docs/symbols/<crate_name>.md.
- Primary output:
- Machine Context: Trigger
bash scripts/generate-llms-txt.shto ensurellms.txtandllms-full.txtare up-to-date with any new documentation.
Guidelines
- This command is intended to complement
cargo doc, providing a more LLM-friendly, flat representation of the codebase. - Focus on the "what" (public interface) rather than the "how" (internal implementation).
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 · 21 lines · 0 tokens per session scan A caf4c3a41057
generate-docs is a command published in the GitHub repository d-oit/rust-2026-template (14 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 244 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 2026-08-31.
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