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 DevelopersGlobal/ai-agent-skills --skill research-and-summarizegit clone --depth 1 https://github.com/DevelopersGlobal/ai-agent-skillsWrote 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/developersglobal/ai-agent-skills/research-and-summarize)<a href="https://agentmods.dev/skills/developersglobal/ai-agent-skills/research-and-summarize"><img src="https://agentmods.dev/badge/skills/developersglobal/ai-agent-skills/research-and-summarize/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/developersglobal/ai-agent-skills/research-and-summarize"><img src="https://agentmods.dev/badge/skills/developersglobal/ai-agent-skills/research-and-summarize.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 | $0.00032 | $0.00643 |
| Opus 5 | $0.00016 | $0.00321 |
| Sonnet 5 | $0.00006 | $0.00129 |
| Haiku 4.5 | $0.00003 | $0.00064 |
Grade A, and why
research-and-summarize 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 11d 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 — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Overview
Information overload is the default state. This skill transforms any research task into a structured summary: headline insight first, context second, detail third, action last. Designed for decision-makers who need clarity, not comprehensiveness.
When to Use
- Summarizing technical documentation or papers
- Researching a technology choice
- Briefing a team on a topic
- Distilling a long document for a specific decision
Process
Step 1: Define the Research Question
- State the specific question being answered: "Should we use Kafka or RabbitMQ for our event pipeline?"
- State who the answer is for and what decision it enables.
- This scopes the research — don't gather information beyond what the decision needs.
Verify: Research question is specific enough to have a clear answer.
Step 2: Gather and Evaluate Sources
- Identify 3–5 high-quality, authoritative sources.
- For each source, note: recency, authority, potential bias.
- Cross-reference key claims across sources.
- Flag conflicting information — don't silently pick one side.
Verify: Key claims are supported by at least 2 independent sources.
Step 3: Write the Layered Summary
- Headline (1 sentence): The single most important insight.
- Key findings (3–5 bullets): Supporting evidence for the headline.
- Context and nuance (1–2 paragraphs): Caveats, tradeoffs, conditions under which the headline doesn't hold.
- What we don't know: Gaps in the available information.
- Recommended action: Given the findings, what should the reader do next?
Deliver: A structured summary with all 5 sections.
Step 4: Cite Sources
- Every factual claim is linked to a source.
- Include the date of each source (recency matters in fast-moving fields).
Verify: Every claim has a citation.
Common Rationalizations (and Rebuttals)
| Excuse | Rebuttal |
|---|---|
| "The topic is too complex to summarize" | The goal is to enable a decision, not to be comprehensive. Scope to the decision. |
| "I'll just share the links" | Links are not summaries. Distillation is the value. |
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.
- 11d ago First seen · 74 lines · 32 tokens per session scan A f8875ee1a2c4
research-and-summarize is a skill published in the GitHub repository DevelopersGlobal/ai-agent-skills (66 stars, last pushed 4mo ago), licensed MIT. It adds 32 tokens to every session and 643 once invoked, about $0.0002 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 2026-08-30.
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