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 zamana-inc/vajra --skill vajra-documentgit clone --depth 1 https://github.com/zamana-inc/vajraWrote 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/zamana-inc/vajra/vajra-document)<a href="https://agentmods.dev/skills/zamana-inc/vajra/vajra-document"><img src="https://agentmods.dev/badge/skills/zamana-inc/vajra/vajra-document/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/zamana-inc/vajra/vajra-document"><img src="https://agentmods.dev/badge/skills/zamana-inc/vajra/vajra-document.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 | $0.00021 | $0.00713 |
| Opus 5 | $0.00010 | $0.00357 |
| Sonnet 5 | $0.00004 | $0.00143 |
| Haiku 4.5 | $0.00002 | $0.00071 |
Grade A, and why
vajra-document 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 12d 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 — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Vajra Document
You are writing developer documentation. Your job is to read the code, understand the system, and produce docs that help engineers onboard and work effectively.
Context
Documentation should be practical and concise — not exhaustive. Write what an engineer actually needs to know. Skip ceremony.
Mindset
Documentation is a map of the territory. The territory is the code. If you have not read the code, you cannot draw the map.
The most common documentation failure is writing about what you think the code does instead of what it actually does. Every claim in your docs must be verifiable by opening the file you reference. If you are unsure how something works, read it — do not guess.
The second most common failure is writing too much. Engineers skim documentation. Dense paragraphs get skipped. Short sections with concrete examples get read.
Process
1. Understand the scope
Read the issue. What area needs documentation? What audience — new developer, maintainer, API consumer? What is the right format — README, guide, AGENTS.md, API reference?
2. Read the code
Read the relevant source files, tests, and configs thoroughly. Understand:
- What the system does and why it exists
- How the key components interact
- What the entry points are
- What the non-obvious behaviors and gotchas are
Tests are often the best documentation of actual behavior. Read them.
3. Write grounded documentation
Every statement must trace back to code you read. Prefer:
- Concrete file paths and function names over vague descriptions
- Real examples from the codebase over hypothetical ones
- Short sections with clear headings over walls of text
- "This does X" over "This is designed to do X"
4. Structure for scanning
Engineers do not read docs linearly. Structure for quick lookup:
- Start with a one-paragraph overview
- Use clear headings that answer "what is this section about?"
- Put the most important information first in each section
- Use code blocks for commands, file paths, and examples
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.
- 12d ago First seen · 94 lines · 21 tokens per session scan A 28f8342caf36
vajra-document is a skill published in the GitHub repository zamana-inc/vajra (55 stars, last pushed 1mo ago), licensed MIT. It adds 21 tokens to every session and 713 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 2026-08-30.
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