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.
git clone --depth 1 https://github.com/masrisystems/dot-agentsWrote 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/masrisystems/dot-agents/refactor-cleaner)<a href="https://agentmods.dev/agents/masrisystems/dot-agents/refactor-cleaner"><img src="https://agentmods.dev/badge/agents/masrisystems/dot-agents/refactor-cleaner/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/masrisystems/dot-agents/refactor-cleaner"><img src="https://agentmods.dev/badge/agents/masrisystems/dot-agents/refactor-cleaner.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 | $0.00051 | $0.00603 |
| Opus 5 | $0.00026 | $0.00302 |
| Sonnet 5 | $0.00010 | $0.00121 |
| Haiku 4.5 | $0.00005 | $0.00060 |
Grade A, and why
refactor-cleaner 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 6d 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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.
- 6d ago First seen · 88 lines · 51 tokens per session scan A 99c8c57efd66
refactor-cleaner is an agent published in the GitHub repository masrisystems/dot-agents (0 stars, last pushed 8d ago), with no licence file. It adds 51 tokens to every session and 603 once invoked, about $0.0003 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 2026-09-03.
Other agents, from other repositories
root-cause-debugger
Investigation specialist that finds and PROVES the root cause of a bug before any code is changed. Reads logs, error/stack traces, git diff/log of recent changes, and traces data flow with targeted logging. Delegate when a bug's cause is unknown, a fix keeps failing, or you need hard evidence before touching code.…
code-reviewer
Review code changes for quality, logic correctness, edge cases, security, and error handling. Return P1/P2/P3 findings using the canonical two-column finding table from references/finding-schema.md (Finding | Suggested Fix, with id/category/location packed into the Finding cell).
pipeline-architect
Use when designing a new multi-agent pipeline, generating spec/plan/tasks/topology artifacts, adding a step to an existing pipeline, updating a step, deleting a step, creating a single subagent definition, or diagnosing a pipeline topology failure.
pipeline-failure-analyzer
Use during a Pattern 3 iterative loop after a tester reports failures, before dispatching a fixer — diagnoses whether failures are fixable bugs or architectural problems, detects "fixes reveal new failures in new locations" pattern, and decides whether to continue or escalate per Pattern 3 protocol.
code-analyst
Mid-cost interpretation — trace how code works across files, reproduce and analyze test failures, research dependency changelogs and upgrade impact, run code-graph and architecture queries. Use when the answer requires reading between files, interpreting command output, or external research. Also the escalation target…
debugger
Adversarial post-implement sweep agent. Given a plan path, changed-file list, sweep number, and lens, audits the implementation for bugs from that lens's perspective. Flag-only — never modifies code. Scope bounded to changed files + 2-hop dependencies. One finding per real issue; no style/naming/formatting feedback.