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/commands/animalzinc/claude-plugins/rank-insights)<a href="https://agentmods.dev/commands/animalzinc/claude-plugins/rank-insights"><img src="https://agentmods.dev/badge/commands/animalzinc/claude-plugins/rank-insights/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/commands/animalzinc/claude-plugins/rank-insights"><img src="https://agentmods.dev/badge/commands/animalzinc/claude-plugins/rank-insights.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 | $0.00000 | $0.01346 |
| Opus 5 | $0.00000 | $0.00673 |
| Sonnet 5 | $0.00000 | $0.00269 |
| Haiku 4.5 | $0.00000 | $0.00135 |
Grade A, and why
rank-insights 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 10d 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 — 253 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Re-Rank Insights
Re-rank insights from a previous analysis using different criteria (frequency, impact, relevance, or custom).
Step 1: Load Previous Analysis
Read the analysis file ($1):
- Parse all themes/insights from the file
- Extract frequency data
- Note any existing rankings
Report to user:
## 📊 Analysis Loaded
**File:** $1
**Themes found:** [number]
**Current ranking:** [Current criteria if specified]
**Available themes:**
1. [Theme name] - Currently ranked #1
2. [Theme name] - Currently ranked #2
[etc.]
How would you like to re-rank these insights?
Step 2: Select Ranking Criteria
Present options to user:
## 🎯 Ranking Criteria Options
Choose how to rank insights:
1. **Frequency** - Most mentioned themes first
- Best for: Understanding what came up most often
- Data available: ✅
2. **Impact** - Highest impact/severity first
- Best for: Prioritizing what to act on
- Requires: Manual input or impact assessment
3. **Relevance to ICP** - Best fit with ideal customer profile
- Best for: Focusing on target audience needs
- Requires: ICP document for comparison
4. **Business Value** - Revenue/strategic opportunity size
- Best for: ROI-focused prioritization
- Requires: Business context assessment
5. **Ease of Implementation** - Quick wins first
- Best for: Tactical planning
- Requires: Feasibility assessment
6. **Custom** - Provide your own criteria
- Example: "Rank by technical complexity" or "Rank by customer segment"
Which criteria would you like to use? [1-6 or describe custom]
Wait for user selection.
Step 3: Apply Ranking Criteria
Based on user's choice:
If Frequency (Option 1):
- Simply re-sort themes by mention count
- No additional analysis needed
If Impact (Option 2):
Use the insight-ranker agent to:
- Review each theme
- Assess potential impact (pain point severity, opportunity size)
- Rank accordingly
If Relevance to ICP (Option 3):
Ask for ICP document:
Please provide path to your ICP document, or I'll look for:
- icp.md
- ideal-customer-profile.md
- customer-profile.md
in the analysis directory
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.
- 10d ago First seen · 253 lines · 0 tokens per session scan A f96735a66e27
rank-insights is a command published in the GitHub repository animalzinc/claude-plugins (15 stars, last pushed 2d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,346 tokens. 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 2026-08-30.
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