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-revisegit 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-revise)<a href="https://agentmods.dev/skills/zamana-inc/vajra/vajra-revise"><img src="https://agentmods.dev/badge/skills/zamana-inc/vajra/vajra-revise/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-revise"><img src="https://agentmods.dev/badge/skills/zamana-inc/vajra/vajra-revise.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 | $0.00039 | $0.00342 |
| Opus 5.5 | $0.00016 | $0.00137 |
| Sonnet 5.5 | $0.00008 | $0.00068 |
| Haiku 4.5 | $0.00004 | $0.00034 |
Grade A, and why
vajra-revise 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
Vajra Revise
This skill is for the PR revision stage after a human requested changes on GitHub.
Goals
- Read the compiled GitHub feedback in
.vajra/review-feedback.mdor.vajra/github-review-bundle.md. - Make targeted code changes on the existing PR branch.
- Re-run the validation needed to prove the feedback was addressed.
- Leave a concise revision summary for the PR update stage.
Inputs
.vajra/review-feedback.md.vajra/review-feedback.json.vajra/github-review-bundle.md.vajra/github-review-bundle.json.vajra/pr.json.vajra/plan.mdwhen it exists.vajra/implementation-summary.mdwhen it exists- The live workspace and diff
Output
Write .vajra/run/revision-summary.md with:
# Feedback Addressed
- each feedback item handled and what changed
# Validation
- exact commands run
- pass/fail result for each command
# Outstanding Concerns
- only real residual risks or follow-ups
Rules
- Stay scoped to the human feedback. Do not reopen unrelated work.
- Prefer the smallest diff that resolves the requested changes cleanly.
- If a feedback item is unclear or conflicts with the code, verify carefully and note the reasoning in the summary.
- Do not create a new PR in this stage.
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 · 50 lines · 39 tokens per session scan A f69354f0c5ca
vajra-revise is a skill published in the GitHub repository zamana-inc/vajra (58 stars, last pushed 2mo ago), licensed MIT. It adds 39 tokens to every session and 342 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.
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