fresh-eyes-review

fresh-eyes-review is a skill for Claude Code from eai-org/agent-toolkit. It costs 32 tokens per session (918 once invoked), scanned A, original, MIT.

A code-review process that uses a separate, fresh reading of a change to find problems the author may overlook.

In plain words
What is it for?
Reviewing a branch, commit, diff, or recently completed work for regressions and correctness issues.
Why use it?
The person who wrote a change already knows its intended design, which can make mistakes look correct. A fresh review checks the actual change without relying on the author's reasoning.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter. Also seen: mentions subagents.

Part of the agent-toolkit plugin — 24 skills shipped together

Good fit Reviewing a branch, commit, diff, or recently completed work for regressions and correctness issues.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/eai-org/agent-toolkit/fresh-eyes-review
Install

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.

Any agent
npx skills add eai-org/agent-toolkit --skill fresh-eyes-review
Clone the repo
git clone --depth 1 https://github.com/eai-org/agent-toolkit

Made for: Claude Code.

Or install agent-toolkit, the plugin that ships this one along with the rest of its 24 skills.

Wrote 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.

agentmods badge for fresh-eyes-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/eai-org/agent-toolkit/fresh-eyes-review/github.svg)](https://agentmods.dev/skills/eai-org/agent-toolkit/fresh-eyes-review)
Your own site
<a href="https://agentmods.dev/skills/eai-org/agent-toolkit/fresh-eyes-review"><img src="https://agentmods.dev/badge/skills/eai-org/agent-toolkit/fresh-eyes-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.

agentmods 80×15 button for fresh-eyes-review

Your own site · 80×15
<a href="https://agentmods.dev/skills/eai-org/agent-toolkit/fresh-eyes-review"><img src="https://agentmods.dev/badge/skills/eai-org/agent-toolkit/fresh-eyes-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 32 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 918 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00032 $0.00918
Opus 5 $0.00016 $0.00459
Sonnet 5 $0.00006 $0.00184
Haiku 4.5 $0.00003 $0.00092

Measured 11d ago against content hash 5e6541545941, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

fresh-eyes-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 11d 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.

skills/fresh-eyes-review/SKILL.md · 59 lines

How it starts

The opening of the file, as written. The whole thing — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Fresh-eyes review

A context that produced a change reads its intent, not its text, so same-context review misses what a fresh reader would catch. The fix is procedural: a reviewer whose context holds only the artifacts.

Workflow

  1. Resolve the inputs. The changeset: whatever the invocation names — a branch, a commit, a diff range, a draft vs its original. Given none, infer it from the session — usually the work just finished, committed or not; no VCS required. With no session context to draw on, fall back to the current git diff; when that too yields nothing, ask the user what to review. Pin the changeset as concretely as the environment allows — a diff or commit range where one exists, otherwise the touched files, with their prior state when reconstructable. Alongside it, a short statement of what the change is supposed to achieve, when one exists (the task as stated, a PR or ticket description); when this session authored the change, never include the session's own reasoning, plan, or messages — leaked rationale recreates the blindness the fresh context exists to remove. Done when changeset and intent are pinned down and free of authoring context.
  2. Confirm the prompt. Assemble the reviewer prompt — changeset, intent, the mandate and exclusions below, and any further reviewer instructions the invocation supplies (e.g. what to report back). When the invocation supplied changeset, intent, and mandate explicitly (e.g. a driving skill), nothing was inferred, so skip the confirmation and proceed. Otherwise show the prompt to the user verbatim and wait for approval; fold any doubt about an inferred changeset into the proposal rather than asking separately. Text emitted before a tool call may not be displayed, so never show the prompt and then ask via a question tool in the same turn — end the turn with the prompt and a plain-text ask, or embed the prompt in the question tool. Done when the user has approved the prompt, as shown or amended — or the explicit-inputs skip applied.
  3. Spawn one fresh-context reviewer (a subagent or equivalent isolated session) with the prompt, free to read any surrounding project material — except the paths the prompt lists as excluded: any exclusions the invocation supplies, plus, when this session authored the change, session-authored files that are not part of it (plans, notes, scratch), since a fresh context cannot tell them apart. Its mandate, unless the invocation redirects it (e.g. security only): regressions and correctness, including contradictions with surrounding code, rules, or docs — though matching surrounding code is not correctness: verify any pattern the change extends or mirrors is itself sound, since completing a broken rollout inherits its breakage; ambiguities a reader without context would trip on; and, when an intent statement was given, whether the change does what it says. Tough but grounded, aimed at mistakes that matter: every finding names its location and a concrete failure scenario; style nits, speculation, and padding are out of scope, and zero findings is a valid outcome. Out of scope bounds what is reported, never what is investigated: a pre-existing anomaly in the mechanism the change touches is a reason to audit it. If the harness cannot isolate a context, fall back to an adversarial pass over the same inputs in the main session. Done when an isolated reviewer has returned its findings, or the fallback pass ran and its result is flagged as same-context (weaker).
  4. Report back. Relay every finding intact — location and failure scenario included — plus whatever else the reviewer was instructed to return; add the session's own assessment when useful, but never silently drop or soften a finding. What to do with the findings is the caller's decision, not this skill's. Done when every reviewer finding appears in the report.

Read the full file on GitHub · 59 lines

Changes

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.

  1. 11d ago First seen · 59 lines · 32 tokens per session scan A 5e6541545941

Subscribe to this mod's changes

fresh-eyes-review is a skill published in the GitHub repository eai-org/agent-toolkit (46 stars, last pushed today), licensed MIT. It adds 32 tokens to every session and 918 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.

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