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 P47Phoenix/Claude-Plugins --skill comparativegit clone --depth 1 https://github.com/P47Phoenix/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/skills/p47phoenix/claude-plugins/comparative)<a href="https://agentmods.dev/skills/p47phoenix/claude-plugins/comparative"><img src="https://agentmods.dev/badge/skills/p47phoenix/claude-plugins/comparative/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/p47phoenix/claude-plugins/comparative"><img src="https://agentmods.dev/badge/skills/p47phoenix/claude-plugins/comparative.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 | $0.00078 | $0.01372 |
| Opus 5.5 | $0.00031 | $0.00549 |
| Sonnet 5.5 | $0.00016 | $0.00274 |
| Haiku 4.5 | $0.00008 | $0.00137 |
Grade A, and why
research-types-comparative 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 1mo 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 — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Comparative Research Sub-Skill
Router-dispatched paradigm sub-skill for Comparative research. Not directly model-invocable; the research-agent parent loads this sub-skill only when Phase 1 detection classifies the question as Comparative.
When This Sub-Skill Loads
The parent router dispatches here when the input question contains signals like:
- "Compare X and Y"
- "Which is better"
- "Alternatives to X"
- "Options for X"
- "X vs. Y"
- "Trade-offs between"
- "Choose between"
Disambiguation rule (from research-agent/references/research-type-patterns.md):
"Compare X to understand Y" where understanding Y is the goal → Exploratory, not Comparative. Comparison is a method, not the purpose. Only route to Comparative when the user is choosing between identifiable options.
Framework Selection
| Framework | Use When |
|---|---|
| PICO | Comparing interventions on a measurable outcome (e.g., "Redis vs Memcached for session storage on latency") |
| None | Multi-criteria comparison with no single dominant outcome; use Decision Matrix with weighted criteria |
SPICE applies if the comparison is experiential ("from the perspective of senior engineers, async vs sync code review"). PECO is rare — exposure-comparison maps better to Evaluative.
Output Pattern: Decision Matrix
Use this pattern verbatim for the Findings section (parent skill's Phase 6 Synthesis output):
## Research Type: Comparative
## Framework: [None / PICO]
## Options Being Compared
[A], [B], [C]
## Evaluation Criteria (defined before gathering)
| Criterion | Weight | Rationale |
|-----------|--------|-----------|
| ... | x% | ... |
## Decision Matrix
| Criterion | Weight | Option A | Option B | Option C | Evidence [citations] |
|-----------|--------|----------|----------|----------|----------------------|
| ... | x% | [score] | [score] | [score] | [S1], [S2] |
## Dimension Deep-Dives
[For each high-weight criterion: detailed comparison with supporting evidence]
## SWOT per Option (when strategic context applies)
**Option A:** Strengths / Weaknesses / Opportunities / Threats
## Qualitative Comparative Analysis
Necessary conditions for success: [...]
Sufficient conditions for success: [...]
## Recommendation
**Recommended:** [Option X]
**Rationale:** [Why this best fits stated needs - with citations]
**Risk trade-offs:** [What is given up]
**Conditions where this changes:** [Edge cases that favor a different option]
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.
- 1mo ago First seen · 115 lines · 78 tokens per session scan A 85a7005ca0db
research-types-comparative is a skill published in the GitHub repository P47Phoenix/Claude-Plugins (2 stars, last pushed 2d ago), licensed MIT. It adds 78 tokens to every session and 1,372 once invoked, about $0.0003 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 2026-08-31.
Other skills, from other repositories
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…