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 agentmods add skills/nishilbhave/codeprobe/codeprobe-code-smellsnpx skills add nishilbhave/codeprobe --skill codeprobe-code-smellsgit clone --depth 1 https://github.com/nishilbhave/codeprobeWhat 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 | $0.00077 | $0.02614 |
| Opus 5 | $0.00039 | $0.01307 |
| Sonnet 5 | $0.00015 | $0.00523 |
| Haiku 4.5 | $0.00008 | $0.00261 |
Grade A, and why
codeprobe-code-smells 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 2d 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.
How it starts
The opening of the file, as written. The whole thing — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Standalone Mode
If invoked directly (not via the orchestrator), you must first:
- Read
../codeprobe/shared-preamble.md(resolve relative to this SKILL.md's location — the siblingcodeprobeskill directory — not the user's project) for the output contract, execution modes, and constraints. - Load applicable reference files from
../codeprobe/references/(same resolution) based on the project's tech stack. - Default to
fullmode unless the user specifies otherwise.
Code Smells & Anti-Pattern Detector
Domain Scope
This sub-skill detects code smells and anti-patterns organized into these categories:
- Bloaters — Long Method, Large Class, Data Clumps, Primitive Obsession
- Object-Orientation Abusers — Feature Envy, Inappropriate Intimacy, Refused Bequest
- Change Preventers — Shotgun Surgery, Divergent Change
- Dispensables — Dead Code, Speculative Generality, Middle Man
- Couplers — Temporal Coupling
- Readability — Magic Numbers, Boolean Blindness, Deep Nesting
What It Does NOT Flag
- Generated code — Migrations, compiled output, vendor directories (
vendor/,node_modules/,dist/,build/,.next/), and auto-generated files (e.g., GraphQL codegen, Prisma client). - Test files with long setup methods — Test context is different; long
setUp()orbeforeEach()methods arranging test data are expected and acceptable. - Configuration files with many entries — A config file with 50 key-value pairs is not a "Large Class" smell.
- Data migration files — These are procedural by nature and often contain long methods.
- Third-party code checked into the repository (e.g., vendored libraries).
- Structural issues already flagged by
codeprobe-solidorcodeprobe-architecture— Large classes may also be flagged as SRP violations or god objects. This sub-skill should still detect and report them, but the orchestrator will deduplicate overlapping findings at the same location.
Detection Instructions
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.
- 2d ago First seen · 119 lines · 77 tokens per session scan A c39b8a517ad0
codeprobe-code-smells is a skill published in the GitHub repository nishilbhave/codeprobe (5 stars, last pushed 1mo ago), licensed MIT. It adds 77 tokens to every session and 2,614 once invoked, about $0.0004 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.
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