Borrowing it
Nothing to install: this file belongs to zkysar1/Claude-Mind. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/zkysar1/Claude-Mind/main/.claude/skills/fresh-eyes-code/SKILL.mdgit clone --depth 1 https://github.com/zkysar1/Claude-MindWrote 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/zkysar1/claude-mind/fresh-eyes-code)<a href="https://agentmods.dev/skills/zkysar1/claude-mind/fresh-eyes-code"><img src="https://agentmods.dev/badge/skills/zkysar1/claude-mind/fresh-eyes-code/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/zkysar1/claude-mind/fresh-eyes-code"><img src="https://agentmods.dev/badge/skills/zkysar1/claude-mind/fresh-eyes-code.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, 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 analysis-evasion · line 1 Suspicious Unicode normalization or mixed-script contentFix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
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 | $0.00187 | $0.05748 |
| Opus 5 | $0.00093 | $0.02874 |
| Sonnet 5 | $0.00037 | $0.01150 |
| Haiku 4.5 | $0.00019 | $0.00575 |
Grade A, and why
fresh-eyes-code scanned grade A with 1 finding 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 9d 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.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
- Does every `subprocess.run(...)` check `returncode` or use `check=True`? How it starts
The opening of the file, as written. The whole thing — 435 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/fresh-eyes-code — On-Demand Adversarial Code Review
Review a specific set of files as if seeing them for the first time, with an explicit mandate to find bugs, not confirm correctness. The author-at-write-time perspective is the worst possible one for catching structural defects — this skill schedules the mode-flip and produces a findings report regardless of outcome.
Inputs
/fresh-eyes-code <path>[ <path>...] — Review explicit paths
/fresh-eyes-code --goal <goal-id> — Review files touched by goal's experience trace
/fresh-eyes-code --since <timestamp> — Review files git-changed since <timestamp>
/fresh-eyes-code --since <timestamp> --author <agent> — Only that agent's changes (β use-case)
All sub-commands produce the same review format and findings output.
Step 0: Load Conventions
Bash: load-conventions.sh board experience journal reasoning-guardrails
Read only the paths returned. If output is empty, all conventions already loaded — proceed to next step.
Phase 1: Assemble Target Set
IF explicit paths provided:
raw_list = list of paths (validate each exists via ls)
ELIF --goal <goal-id>:
Bash: bash core/scripts/experience-read.sh --goal <goal-id>
raw_list = file paths from experience.content_path + any referenced scripts/md
ELIF --since <timestamp> [--author <agent>]:
# Canonical query — single source of truth. The script handles the
# git-identity intersection via team-state.yaml recent_completions +
# agents/<agent>/experience.jsonl when --author is passed. See
# cross-agent-recent-changes.sh for semantics; do not re-describe the
# intersection here.
IF --author <agent>:
Bash: bash core/scripts/cross-agent-recent-changes.sh --agent <agent> --since <timestamp>
ELSE:
Bash: bash core/scripts/cross-agent-recent-changes.sh --since <timestamp>
raw_list = newline-separated stdout
# Bash-enforce the 20-file cap. Prose caps drift; a pipe does not. The cap
# preserves assembled order (recency for --since, experience order for --goal,
# argv order for explicit paths) because upstream producers already emit in
# that order — do NOT sort here.
target_files = printf '%s\n' "$raw_list" | sed '/^$/d' | head -20
skipped_count = (count of raw_list) - (count of target_files)
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.
- 9d ago First seen · 435 lines · 187 tokens per session scan A a52040568b73
fresh-eyes-code is a skill published in the GitHub repository zkysar1/Claude-Mind (5 stars, last pushed yesterday), licensed MIT. It adds 187 tokens to every session and 5,748 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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