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 adamlinscott/claude-skills --skill fresh-eyesgit clone --depth 1 https://github.com/adamlinscott/claude-skillsWrote 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/adamlinscott/claude-skills/fresh-eyes)<a href="https://agentmods.dev/skills/adamlinscott/claude-skills/fresh-eyes"><img src="https://agentmods.dev/badge/skills/adamlinscott/claude-skills/fresh-eyes/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/adamlinscott/claude-skills/fresh-eyes"><img src="https://agentmods.dev/badge/skills/adamlinscott/claude-skills/fresh-eyes.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00122 | $0.02634 |
| Opus 5 | $0.00061 | $0.01317 |
| Sonnet 5 | $0.00024 | $0.00527 |
| Haiku 4.5 | $0.00012 | $0.00263 |
Grade A, and why
fresh-eyes 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 — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
fresh-eyes
Audit a finished diff with fresh eyes. The mechanism is double-blind reconciliation: a subagent that never saw the conversation reads the diff blind and reports what it thinks the change does. The main context — which holds the real intent — compares that blind read against what the work was meant to do. The divergence is the signal.
Not only a bug-hunt. The primary lens is completeness and intent — did the change do
what it was meant to, fully. Catching bugs and oversights is a secondary byproduct of
that check, welcome but not the goal. For a dedicated correctness sweep, use
/code-review or /codex review instead.
Why this is not the verification pass you were told to delete. Current prompting guidance says to strip explicit verification instructions — "double-check your answer", "add a final verification step", "use a subagent to verify" — because the model already self-checks and the instruction compounds into wasted passes. That is correct, and it does not describe this skill. Those instructions ask the same context to look at its own work again, which is the pass that adds nothing. This skill's value is not the second look; it is that the second reader has never seen the conversation, so it cannot inherit the premise the first reader was working from. That is a different instrument, and no amount of self-checking substitutes for it. Keep the isolation; it is the whole mechanism. What the guidance does bite on here is quantity — see the fan-out guardrail below.
Know what this instrument cannot see. It measures the gap between two readings, so it is blind to any error the two share. If the intent itself is wrong, a faithful implementation of it produces zero divergence — the strongest possible pass. Agreement is therefore evidence that the code expresses the intent, never evidence that the intent was right. Steps 1, 3 and 4 exist to attack that blind spot directly; do not water them down.
Workflow
Run these steps in order. Do not skip step 1 — it is the integrity gate.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · +31 lines · +4 tokens per session c92dc2cf485e
- 11d ago First seen · 143 lines · 118 tokens per session scan A fcb132efb377
fresh-eyes is a skill published in the GitHub repository adamlinscott/claude-skills (3 stars, last pushed yesterday), licensed MIT. It adds 122 tokens to every session and 2,634 once invoked, about $0.0006 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 2026-08-31.
Other skills, from other repositories
review
Use in the Review phase before claiming any Java/Spring task is complete, fixed, or passing. Spawns the auditor subagents that check the implementation against every applicable skill, rule, and memory item, runs the test suite for fresh evidence, and re-spawns for at most two fix rounds before reporting what survives.…
cleanup-audit
Audit codebase for dead code, unused exports, orphaned files, and stale manifests.
link-check
Verify @file references in AIWG skills and agents against the linking contract — per-file or corpus-wide, with optional auto-fix.
pr-triage
4-phase PR backlog management with audit, deep code review, validated comments, and optional worktree setup. Use when triaging pull requests, catching up on pending code reviews, or managing a backlog of open PRs. Args: 'all' to review all, PR numbers to focus (e.g. '42 57'), 'en'/'fr' for language, no arg = audit…
audit-agents-skills
Audit Claude Code agents, skills, and commands for quality and production readiness. Use when evaluating skill quality, checking production readiness scores, or comparing agents against best-practice templates.
design-patterns
Detect, suggest, and evaluate GoF design patterns in TypeScript/JavaScript codebases. Use when refactoring code, applying singleton/factory/observer/strategy patterns, reviewing pattern quality, or finding stack-native alternatives for React, Angular, NestJS, and Vue.