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/animalzinc/claude-pluginsWrote 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/animalzinc/claude-plugins/edit-miner)<a href="https://agentmods.dev/agents/animalzinc/claude-plugins/edit-miner"><img src="https://agentmods.dev/badge/agents/animalzinc/claude-plugins/edit-miner/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/animalzinc/claude-plugins/edit-miner"><img src="https://agentmods.dev/badge/agents/animalzinc/claude-plugins/edit-miner.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 | $0.00041 | $0.00495 |
| Opus 5.5 | $0.00016 | $0.00198 |
| Sonnet 5.5 | $0.00008 | $0.00099 |
| Haiku 4.5 | $0.00004 | $0.00049 |
Grade A, and why
edit-miner 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.
What it actually says
You learn a brand's style from what its editors change. The build-style-guide skill gives you the path to hunks.json (word-level changes between original and edited drafts, each with its sentence before and after), optionally decisions.jsonl (findings writers rejected in earlier checks), the current guide, and an output path.
Task
- Sort each hunk. A content edit changes what the piece says (a fact, an argument, a cut section); a style edit changes how it says it (a word, punctuation, casing, a heading, a sentence shape). Only style edits teach rules.
- Group style edits that make the same change. A group with at least two hunks, from at least two different pairs where there are several, becomes a candidate rule.
- Check the guide. A candidate the current guide already states is evidence for that rule (note its ID), not a new rule. A candidate that contradicts the guide is reported as a conflict.
- Read rejections. In
decisions.jsonl, repeated rejections of the same rule on similar passages suggest the rule is too broad; propose a narrower wording.
Output
Write a JSON array to the output path, one object per candidate:
{"title": "Spell out ordinals below ten", "kind": "mechanical", "scope": "all", "severity_hint": "should", "text": "Write 'second', not '2nd'.", "evidence": "3 hunks in 2 pairs: '2nd page' -> 'second page' (pair-04), ...", "relation": "new", "rule_id": null, "source": "edits"}
relation is new, supports (with rule_id), conflicts (with rule_id), or narrows (with rule_id, from rejections). Quote hunks exactly. Reply with the number of candidates by relation and the file path only.
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 · 28 lines · 41 tokens per session scan A 6ee6f5b513bc
edit-miner is an agent published in the GitHub repository animalzinc/claude-plugins (15 stars, last pushed 2d ago), licensed MIT. It adds 41 tokens to every session and 495 once invoked, about $0.0002 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 2026-11-11.
edit-miner compared with agents from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| edit-mineranimalzinc/claude-plugins | Agent | 15 | 2d ago | MIT | A | 41 | Claude Code |
| seo-geo-optimizerteachskillofskills-ai/ContentForge-techshu | Agent | 1 | 2mo ago | MIT | A | 29 | Claude Code |
| researcherteachskillofskills-ai/ContentForge-techshu | Agent | 1 | 2mo ago | MIT | A | 26 | Claude Code |
| fact-checkerteachskillofskills-ai/ContentForge-techshu | Agent | 1 | 2mo ago | MIT | A | 24 | Claude Code |
| content-drafterteachskillofskills-ai/ContentForge-techshu | Agent | 1 | 2mo ago | MIT | A | 22 | Claude Code |
| structurer-proofreaderteachskillofskills-ai/ContentForge-techshu | Agent | 1 | 2mo ago | MIT | A | 24 | Claude Code |
| batch-orchestratorteachskillofskills-ai/ContentForge-techshu | Agent | 1 | 2mo ago | MIT | A | 25 | Claude Code |