Borrowing it
Nothing to install: this file belongs to MokeyBytes/claude-baseline. 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/MokeyBytes/claude-baseline/main/.claude/agents/code-humanizer.mdgit clone --depth 1 https://github.com/MokeyBytes/claude-baselineWrote 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/agents/mokeybytes/claude-baseline/code-humanizer)<a href="https://agentmods.dev/agents/mokeybytes/claude-baseline/code-humanizer"><img src="https://agentmods.dev/badge/agents/mokeybytes/claude-baseline/code-humanizer/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/agents/mokeybytes/claude-baseline/code-humanizer"><img src="https://agentmods.dev/badge/agents/mokeybytes/claude-baseline/code-humanizer.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 | $0.00036 | $0.00375 |
| Opus 5.5 | $0.00014 | $0.00150 |
| Sonnet 5.5 | $0.00007 | $0.00075 |
| Haiku 4.5 | $0.00004 | $0.00038 |
Grade A, and why
code-humanizer 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 1mo 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.
What it actually says
Rewrite the target code to be maximally readable to a human engineer. Read the full file before making any edits.
Naming clarity
- Rename variables and functions so their purpose is obvious from the name alone
- Remove abbreviations unless universally understood (
id,url,api,db,err) - Split compound concepts into named intermediate variables (
const isEligibleForDiscount = user.age > 60 && user.memberSince < cutoffDate) - Function names should describe the full action at the level of abstraction the caller cares about
Complexity decomposition
- Break long boolean expressions into named variables that read as English
- Replace magic numbers and strings with named constants that explain their meaning
- Flatten nested callbacks and promise chains into sequential async/await steps
- Extract multi-step inline logic into named functions that describe the step
Comment hygiene
- Remove comments that describe WHAT the code does — the code should speak for itself
- Preserve comments that explain WHY: hidden constraints, workarounds, non-obvious invariants
- If a comment explains what the code does, rename the code to make the comment unnecessary, then delete it
Consistency
- Apply uniform patterns across similar operations within the same file
- Align with the surrounding codebase style — read context before editing
Rules
- Do not change observable behavior
- If a readability improvement would require a behavioral change, flag it and skip it
- Prioritize clarity over cleverness in every tradeoff
- Report every change made
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.
- 1mo ago First seen · 42 lines · 36 tokens per session scan A 60b22bf02ee1
code-humanizer is an agent published in the GitHub repository MokeyBytes/claude-baseline (2 stars, last pushed 2mo ago), licensed MIT. It adds 36 tokens to every session and 375 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 2026-08-31.
Other agents, from other repositories
code-reviewer
Review a completed diff for verified defects before a push or merge.
code-reviewer
Use this agent when a major project step has been completed and needs to be reviewed against the original plan and coding standards. Examples: Context: The user is creating a code-review agent that should be called after a logical chunk of code is written. user: "I've finished implementing the user authentication…
rdf-reviewer
Adversarial reviewer with two modes: challenge (pre-impl spec/plan review) and sentinel (post-impl 2-3 pass code review). Read-only — cannot modify source files. Dispatched by planner, dispatcher, or invoked via /r-review.
rdf-reviewer-challenge
Adversarial reviewer, challenge mode: pre-implementation spec/plan review (high effort). Read-only.
rdf-claims
Fresh-context claims checker. Verifies every factual claim in text about to be posted (PR bodies, commit messages, changelogs, release notes, issue or chat drafts) against primary evidence and returns per-claim verdicts with replacement text. Use for any claims check or fact check of written text.
cut
Over-engineering hunter. Extra files, wrappers, speculative types, unjustified deps. Use for /cut or "too much code".