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 Bidiche49/claude-conf --skill factorizegit clone --depth 1 https://github.com/Bidiche49/claude-confWrote 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/bidiche49/claude-conf/factorize)<a href="https://agentmods.dev/skills/bidiche49/claude-conf/factorize"><img src="https://agentmods.dev/badge/skills/bidiche49/claude-conf/factorize/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/bidiche49/claude-conf/factorize"><img src="https://agentmods.dev/badge/skills/bidiche49/claude-conf/factorize.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 | $0.00012 | $0.01947 |
| Opus 5.5 | $0.00005 | $0.00779 |
| Sonnet 5.5 | $0.00002 | $0.00389 |
| Haiku 4.5 | $0.00001 | $0.00195 |
Grade A, and why
factorize 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.
How it starts
The opening of the file, as written. The whole thing — 208 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Scan the codebase to detect duplicated code, repeated patterns, and factorization opportunities. Unlike /simplify (which refines recently changed code), this command performs a project-wide analysis.
Modes:
/factorize— full scan, all source files/factorize src/services— scoped to a specific directory/factorize --dry-run— report only, no code changes/factorize --scope small— override auto-detected project size
Step 1 — Context
-
Read
CLAUDE.mdto understand:- Stack (language, framework, conventions)
- Project structure (where source lives, what's generated/vendored)
- Naming conventions and existing abstractions
-
Detect project size:
- Count source files (exclude tests, config, generated, vendor, node_modules)
- Small (< 30 files): 1 analysis agent
- Medium (30-100 files): 2 agents (split by directory)
- Large (> 100 files): 3 agents (split by layer/concern)
-
Present the plan:
FACTORIZE — [project name] Stack: [detected] Scope: [full / directory] Size: [X source files] → [small/medium/large] Agents: [1-3] Mode: [analysis + refactor / dry-run (report only)] Proceed? [Y/n]
Step 2 — Detection phase
Launch agents in parallel (subagent_type: feature-dev:code-explorer).
Each agent receives its assigned files and this mission:
You are analyzing [project name] ([stack]) for factorization opportunities.
Your assigned files: [list].
Scan for these patterns:
1. **DUPLICATED CODE** — identical or near-identical blocks (>5 lines) that appear in 2+ files.
Report: both locations, the duplicated block, and a suggested shared function/module name.
2. **REPEATED PATTERNS** — same logical pattern implemented differently across files
(e.g., 3 different ways to validate input, 4 similar API call wrappers).
Report: all occurrences, the common pattern, and a suggested unified approach.
3. **MISSED ABSTRACTIONS** — operations that could benefit from a shared utility
(e.g., repeated string transformations, common data reshaping, recurring error handling).
Report: occurrences and suggested abstraction.
4. **COPY-PASTE DRIFT** — code that was clearly copied then modified slightly,
creating divergence that will cause bugs (one copy gets fixed, others don't).
Report: all copies, the differences, and which version is likely "correct".
For each finding, report:
- **Type**: DUPLICATION / PATTERN / ABSTRACTION / DRIFT
- **Impact**: HIGH (>3 occurrences or >20 lines each) / MEDIUM (2-3 occurrences) / LOW (minor)
- **Locations**: file:line for each occurrence
- **Code snippets**: the duplicated/similar blocks (abbreviated if >15 lines)
- **Suggestion**: concrete refactoring approach (function name, module location, signature)
Do NOT report:
- Similar test setup code (tests are allowed to be repetitive for readability)
- Framework boilerplate that cannot be abstracted (e.g., route definitions)
- Config files or generated code
- Differences that are intentional (check comments, commit messages)
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 · 208 lines · 12 tokens per session scan A 4093a50b03b9
factorize is a skill published in the GitHub repository Bidiche49/claude-conf (2 stars, last pushed 5mo ago), licensed MIT. It adds 12 tokens to every session and 1,947 once invoked, about $0.0000 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.
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