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 sergeyklay/.agents --skill compare-itgit clone --depth 1 https://github.com/sergeyklay/.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/skills/sergeyklay/.agents/compare-it)<a href="https://agentmods.dev/skills/sergeyklay/.agents/compare-it"><img src="https://agentmods.dev/badge/skills/sergeyklay/.agents/compare-it/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/sergeyklay/.agents/compare-it"><img src="https://agentmods.dev/badge/skills/sergeyklay/.agents/compare-it.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00114 | $0.02627 |
| Opus 5 | $0.00057 | $0.01314 |
| Sonnet 5 | $0.00023 | $0.00525 |
| Haiku 4.5 | $0.00011 | $0.00263 |
Grade A, and why
compare-it 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 9d 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 — 244 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tool comparison evaluation
Produce publication-grade architectural comparison documents that evaluate two solutions against weighted criteria derived from organizational requirements. The output follows a 12-section structure with quantified scoring, bidirectional gap analysis, Mermaid architecture diagrams, cost projections, risk matrices, and reversal conditions for every recommendation.
Workflow
Phase 1: Research both solutions
Gather enough context to write authoritative profiles. Research is front-loaded. Weak research produces weak evaluations.
Research checklist:
- Identify Solution A and Solution B
- For each solution, collect: type, maturity, vendor/maintainer, mechanism, output format, integrations, generation time
- Find official documentation, product pages, blog posts, press coverage
- Identify pricing model and tiers
- Find academic research relevant to the comparison domain
- Identify the organization's current usage and existing investments
- Document limitations of the research (no hands-on testing, beta status, etc.)
Source priority:
- Official documentation and technical specs
- Academic research papers (arXiv, conference proceedings)
- Press coverage and analyst reports
- Community discussions and case studies
Phase 2: Define evaluation framework
Design criteria and weights before scoring. The framework must reflect the organization's priorities, not generic equal-weight distribution.
Framework checklist:
- Identify 6-10 evaluation criteria from organizational requirements
- Assign percentage weights that sum to exactly 100%
- Write a one-sentence rationale for each weight
- Define the 1-5 scoring scale with semantic anchors
- Verify the highest-weighted criteria reflect the organization's primary constraints
See evaluation methodology for scoring frameworks, weight calibration, and sensitivity analysis techniques.
Phase 3: Write the document
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 244 lines · 114 tokens per session scan A 3275eac2bdd5
compare-it is a skill published in the GitHub repository sergeyklay/.agents (5 stars, last pushed yesterday), licensed Apache-2.0. It adds 114 tokens to every session and 2,627 once invoked, about $0.0006 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 2026-08-31.
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