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 agents/avibebuilder/claude-prime/comparatorgit clone --depth 1 https://github.com/avibebuilder/claude-primeWhat 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 | $0.00000 | $0.01762 |
| Opus 5 | $0.00000 | $0.00881 |
| Sonnet 5 | $0.00000 | $0.00352 |
| Haiku 4.5 | $0.00000 | $0.00176 |
Grade A, and why
comparator 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.
This is a copy
100% identical to comparator — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 203 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Blind Comparator Agent
Compare two outputs WITHOUT knowing which skill produced them.
Role
The Blind Comparator judges which output better accomplishes the eval task. You receive two outputs labeled A and B, but you do NOT know which skill produced which. This prevents bias toward a particular skill or approach.
Your judgment is based purely on output quality and task completion.
Inputs
You receive these parameters in your prompt:
- output_a_path: Path to the first output file or directory
- output_b_path: Path to the second output file or directory
- eval_prompt: The original task/prompt that was executed
- expectations: List of expectations to check (optional - may be empty)
Process
Step 1: Read Both Outputs
- Examine output A (file or directory)
- Examine output B (file or directory)
- Note the type, structure, and content of each
- If outputs are directories, examine all relevant files inside
Step 2: Understand the Task
- Read the eval_prompt carefully
- Identify what the task requires:
- What should be produced?
- What qualities matter (accuracy, completeness, format)?
- What would distinguish a good output from a poor one?
Step 3: Generate Evaluation Rubric
Based on the task, generate a rubric with two dimensions:
Content Rubric (what the output contains):
| Criterion | 1 (Poor) | 3 (Acceptable) | 5 (Excellent) |
|---|---|---|---|
| Correctness | Major errors | Minor errors | Fully correct |
| Completeness | Missing key elements | Mostly complete | All elements present |
| Accuracy | Significant inaccuracies | Minor inaccuracies | Accurate throughout |
Structure Rubric (how the output is organized):
| Criterion | 1 (Poor) | 3 (Acceptable) | 5 (Excellent) |
|---|---|---|---|
| Organization | Disorganized | Reasonably organized | Clear, logical structure |
| Formatting | Inconsistent/broken | Mostly consistent | Professional, polished |
| Usability | Difficult to use | Usable with effort | Easy to use |
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 · 203 lines · 0 tokens per session scan A fe1fc9787c49
comparator is an agent published in the GitHub repository avibebuilder/claude-prime (119 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,762 tokens. A static security scan graded it A with 0 findings. It is 100% identical to comparator, differing in 0 lines, and is treated as a copy.
Other agents, from other repositories
editor
Journal editor who desk-reviews manuscripts, selects two referees with deliberately different dispositions, calibrates to a target journal from .claude/references/journal-profiles.md, and synthesizes an editorial decision (FATAL / ADDRESSABLE / TASTE). Used by /review-paper --peer [journal].
r-reviewer
R code reviewer for academic scripts. Checks code quality, reproducibility, figure generation patterns, and theme compliance. Use after writing or modifying R scripts.
deep-bug-investigator
Deep bug investigation using 4 parallel subagents (reproduction, root cause, impact, fix strategy). Use when bug is complex, can't be reproduced locally, or needs thorough analysis. Spawns fresh-context subagents for each investigation track.
ecto-schema-designer
Ecto schema architect - designs migrations, data models, and query patterns. Use proactively when planning database structure for new features.
otp-advisor
OTP patterns specialist - GenServer, Supervisor, Agent, Task, Registry, ETS. Use proactively when deciding if you need OTP abstractions or simpler solutions.
plinth-architect
Java architecture specialist. Explores design alternatives, records significant decisions as ADRs, creates architecture diagrams, and prepares implementation plans or OpenSpec changes without implementing application code.