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 pbakaus/agent-reviews --skill resolve-human-reviewsgit clone --depth 1 https://github.com/pbakaus/agent-reviewsWrote 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/pbakaus/agent-reviews/resolve-human-reviews)<a href="https://agentmods.dev/skills/pbakaus/agent-reviews/resolve-human-reviews"><img src="https://agentmods.dev/badge/skills/pbakaus/agent-reviews/resolve-human-reviews/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/pbakaus/agent-reviews/resolve-human-reviews"><img src="https://agentmods.dev/badge/skills/pbakaus/agent-reviews/resolve-human-reviews.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 8 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 6 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 17 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 25 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 95 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 99 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 103 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 121 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium Output Handling · line 29 Output size or generation rate is not bounded. Unbounded output enables denial-of-service through resource exhaustion, log flooding, or context-window stuffing.Fix: Set explicit limits on output length, generation count, and rate. Use max_tokens and truncation to prevent unbounded output.
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 | $0.00038 | $0.01879 |
| Opus 5 | $0.00019 | $0.00940 |
| Sonnet 5 | $0.00008 | $0.00376 |
| Haiku 4.5 | $0.00004 | $0.00188 |
Grade A, and why
resolve-human-reviews 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 today.
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 — 179 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Automatically resolve human review comments on the current PR. Fetches unanswered human feedback, evaluates each comment, applies fixes where appropriate, and replies to every comment with the outcome.
Prerequisites
All commands below use npx agent-reviews. If the project uses a different package manager, substitute the appropriate runner (e.g., pnpm dlx agent-reviews for pnpm, yarn dlx agent-reviews for Yarn, bunx agent-reviews for Bun). Honor the user's package manager preference throughout.
Cloud environments only (e.g., Codespaces, remote agents): verify git author identity so CI checks can map commits to the user. Run git config --global --get user.email and if empty or a placeholder, set it manually. Skip this check in local environments.
Phase 1: FETCH & FIX (synchronous)
Step 1: Fetch All Human Comments (Expanded)
Run npx agent-reviews --humans-only --unanswered --expanded
The CLI auto-detects the current branch, finds the associated PR, and authenticates via gh CLI or environment variables. If anything fails (no token, no PR, CLI not installed), it exits with a clear error message.
This shows only unanswered human comments with full detail: complete comment body (no truncation), diff hunk (code context), and all replies. Each comment shows its ID in brackets (e.g., [12345678]).
If zero comments are returned, print "No unanswered human comments found" and skip to Phase 2.
Step 3: Process Each Unanswered Comment
For each comment from the expanded output:
A. Evaluate the Feedback
Read the referenced code and the reviewer's comment. Human reviewers are generally more accurate and context-aware than bots. Treat their feedback with appropriate weight. Determine:
- ACTIONABLE - The reviewer identified a real issue or requested a concrete change
- DISCUSSION - The comment raises a valid point but the right approach is unclear
- ALREADY ADDRESSED - The concern has already been fixed or is no longer relevant
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.
- today Changed · +2 lines 11f2e70ba285
- 11d ago First seen · 177 lines · 38 tokens per session scan A e783924839bf
resolve-human-reviews is a skill published in the GitHub repository pbakaus/agent-reviews (268 stars, last pushed today), licensed MIT. It adds 38 tokens to every session and 1,879 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…