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 jayvee/aigon --skill aigon-feature-code-reviewgit clone --depth 1 https://github.com/jayvee/aigonWrote 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/jayvee/aigon/aigon-feature-code-review)<a href="https://agentmods.dev/skills/jayvee/aigon/aigon-feature-code-review"><img src="https://agentmods.dev/badge/skills/jayvee/aigon/aigon-feature-code-review/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/jayvee/aigon/aigon-feature-code-review"><img src="https://agentmods.dev/badge/skills/jayvee/aigon/aigon-feature-code-review.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 | $0.00020 | $0.02355 |
| Opus 5.5 | $0.00008 | $0.00942 |
| Sonnet 5.5 | $0.00004 | $0.00471 |
| Haiku 4.5 | $0.00002 | $0.00235 |
Grade A, and why
aigon-feature-code-review 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 2mo 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 — 212 lines — stays where its author put it; the contents beside it link to each section on GitHub.
aigon-feature-code-review
Perform a code review on another agent's implementation, making targeted fixes where needed. Use a different model than the implementer for best results.
You are doing a write-capable review pass, not a read-only review report. Ignore any default "code review means findings-only" behavior for this task; this command is specifically a review-with-fixes workflow.
Your default action is:
- identify a concrete issue
- patch it in the feature worktree
- commit it with
fix(review): ... - leave only residual issues in notes
Do not stop at describing a fix if you can safely make it yourself. A findings-only review is valid only when:
- the implementation is genuinely clean
- the remaining issue requires a broader architectural or product decision
- the issue is ambiguous and the correct behavior is not clear from the spec
- you are blocked by missing context or infrastructure you cannot safely change
Argument Resolution
If no ID is provided or doesn't match an active feature, run aigon feature-list --active, filter to matches, and ask the user.
Step 1: Gather all context (one tool call)
Run this entire block in a single shell execution — do not split it up. It fetches branch info, the full diff, and the implementation log in one shot so you can review immediately without extra round-trips.
You MUST commit review changes to the FEATURE WORKTREE, never to main.
BRANCH=$(git branch --show-current)
FEATURE_BRANCH=$(git branch --list 'feature-$1-*' | head -1 | tr -d ' *')
WORKTREE=$(git worktree list | grep "feature-$1" | awk '{print $1}')
echo "=== WORKSPACE ==="
echo "Current: $BRANCH Feature: $FEATURE_BRANCH Worktree: $WORKTREE"
echo "=== DIFF ==="
git diff "main...${FEATURE_BRANCH:-HEAD}"
echo "=== IMPLEMENTATION LOG ==="
cat docs/specs/features/logs/feature-$1-*-log.md 2>/dev/null || echo "(no log found)"
aigon agent-status reviewing
The spec body was printed inline by the launching CLI — use that copy for acceptance criteria.
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.
- 2mo ago First seen · 212 lines · 20 tokens per session scan A 930a43348cdf
aigon-feature-code-review is a skill published in the GitHub repository jayvee/aigon (27 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 20 tokens to every session and 2,355 once invoked, about $0.0001 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.
aigon-feature-code-review compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| aigon-feature-code-reviewjayvee/aigon | Skill | 27 | 1mo ago | Apache-2.0 | A | 20 | Claude Code, Codex |
| gh-find-prsHmbown/CodeWhale | Skill | 41k | 4d ago | MIT | A | 27 | Claude Code, Codex |
| gh-compile-issuesHmbown/CodeWhale | Skill | 41k | 4d ago | MIT | A | 39 | Claude Code, Codex |
| reviewHmbown/CodeWhale | Skill | 41k | 4d ago | MIT | A | 73 | Claude Code, Codex |
| review-teammvschwarz/openrig | Skill | 8.8k | today | Apache-2.0 | A | 17 | Claude Code, Codex |
| cw-sliceHmbown/Codewhale | Skill | 41k | 1mo ago | MIT | A | 47 | Claude Code, Codex |
| simplifyHmbown/CodeWhale | Skill | 41k | 4d ago | MIT | A | 24 | Claude Code, Codex |