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 | $0.00019 | $0.00171 |
| Sonnet 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 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.
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.
- 12d 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 (55 stars, last pushed 1mo ago), licensed MIT. It adds 39 tokens to every session and 342 once invoked, about $0.0002 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.
Other skills, from other repositories
autoreview
Pre-commit/ship code review: Codex default; optional Claude or Pi.
omh-code-review
This is a Hermes-native code-review workflow skill.
revdiff-plan
Review the last Codex assistant message (plan, analysis, or proposal) with inline annotations in a TUI overlay. Extracts the most recent response from Codex rollout files and opens it in revdiff for review and annotation. Activates on "revdiff-plan", "review plan with revdiff", "annotate plan", "review last response"…
code-reviewer
Code review specialist focused on patterns, bugs, security, and performance.
full-repo-review
Comprehensive four-wave review of all repo source files, producing a prioritized issue backlog.
agent-teams-simplify-and-harden
Implementation + audit loop using parallel agent teams with structured simplify, harden, and document passes. Spawns implementation agents to do the work, then audit agents to find complexity, security gaps, and spec deviations, then loops until code compiles cleanly, all tests pass, and auditors find zero issues or…