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research-summarizer

research-summarizer is a skill for Claude Code, Codex from oxbshw/LLM-Agents-Ecosystem-Handbook. It costs 26 tokens per session (550 once invoked), scanned A, original, MIT.

A method for researching a topic across several web sources and writing a cited briefing. It distinguishes multi-source research from summarising a single page.

In plain words
What is it for?
Use it for literature reviews, technology briefings, market overviews, and other neutral reports that need several sources and references.
Why use it?
It reduces the work of planning research, comparing findings, and checking that each claim has a usable citation.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

not rated 558repo 4mo ago A scan SkillSpector: pass 26 tokens original MIT

Good fit Use it for literature reviews, technology briefings, market overviews, and other neutral reports that need several sources and references.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/oxbshw/llm-agents-ecosystem-handbook/research-summarizer
View source ↗ oxbshw/LLM-Agents-Ecosystem-Handbook
Install

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.

Any agent
npx skills add oxbshw/LLM-Agents-Ecosystem-Handbook --skill research-summarizer
Clone the repo
git clone --depth 1 https://github.com/oxbshw/LLM-Agents-Ecosystem-Handbook

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for research-summarizer

README.md
[![agentmods](https://agentmods.dev/badge/skills/oxbshw/llm-agents-ecosystem-handbook/research-summarizer/github.svg)](https://agentmods.dev/skills/oxbshw/llm-agents-ecosystem-handbook/research-summarizer)
Your own site
<a href="https://agentmods.dev/skills/oxbshw/llm-agents-ecosystem-handbook/research-summarizer"><img src="https://agentmods.dev/badge/skills/oxbshw/llm-agents-ecosystem-handbook/research-summarizer/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.

agentmods 80×15 button for research-summarizer

Your own site · 80×15
<a href="https://agentmods.dev/skills/oxbshw/llm-agents-ecosystem-handbook/research-summarizer"><img src="https://agentmods.dev/badge/skills/oxbshw/llm-agents-ecosystem-handbook/research-summarizer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 26 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 550 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00026 $0.00550
Opus 5.5 $0.00010 $0.00220
Sonnet 5.5 $0.00005 $0.00110
Haiku 4.5 $0.00003 $0.00055

Measured 2mo ago against content hash a8ea6545162a, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

research-summarizer 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 2mo 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.

skills/examples/research-summarizer/SKILL.md · 54 lines

What it actually says

Research Summarizer

When to use

  • User asks "research X" / "what's the state of Y" / "summarize the literature on Z"
  • The answer requires multiple sources, not one
  • The user expects citations

When NOT to use

  • Single-source summarization (use a plain summarize tool)
  • Code search (use repo-auditor or grep)
  • Opinion / recommendation requests (this skill produces neutral briefings)

Inputs

Name Type Required Notes
topic string yes the question to research
depth "shallow" | "deep" no default "shallow" (5–7 sources); "deep" → 10–15
audience string no shapes vocabulary level (e.g., "executive", "engineer")

Outputs

A Markdown file briefing.md following the structure in references/report-template.md.

Workflow

  1. Plan: produce 3–7 sub-questions covering breadth and depth
  2. Search + fetch: for each sub-question, run web_search then fetch_url for top 2–3 hits
  3. Cluster: group findings by claim; load references/clustering-rules.md
  4. Draft: fill references/report-template.md — every claim needs a [n] citation
  5. Validate: every citation resolves; no domain dominates (≥ 3 distinct domains for shallow, ≥ 5 for deep)
  6. Self-review against success criteria below

References

Success criteria

  • ≥ 5 sources for shallow, ≥ 10 for deep
  • ≥ 3 distinct domains
  • 0 unsourced claims (or all flagged (unsourced))
  • Open Questions section populated

Failure modes

  • Fewer sources available than required → return partial result, flag at top
  • All sources from one domain → reject, retry plan with broader scope
  • Network error → fail loudly, don't fabricate

Examples

  • See references/examples/ (TBD) for one shallow and one deep run
Files

What ships with it

1 file 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.

Changes

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.

  1. 2mo ago First seen · 54 lines · 26 tokens per session scan A a8ea6545162a

Subscribe to this mod's changes

research-summarizer is a skill published in the GitHub repository oxbshw/LLM-Agents-Ecosystem-Handbook (558 stars, last pushed 4mo ago), licensed MIT. It adds 26 tokens to every session and 550 once invoked, about $0.0001 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 2026-08-30.

ResearchWriting and docsaiai-agentai-agentsfine-tuningfinetuning-llmsfreamework
Related

research-summarizer compared with skills from other repositories

research-summarizer next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
research-summarizeroxbshw/LLM-Agents-Ecosystem-HandbookSkill5584mo agoMITA26Claude Code, Codex
fine-tuning-serving-openpiOrchestra-Research/AI-Research-SKILLsSkill14k26d agoMITA87Claude Code
fine-tuning-openvla-oftOrchestra-Research/AI-Research-SKILLsSkill14k26d agoMITA103Claude Code
together-ai-inferencesynthetic-sciences/openscienceSkill4.3k2d agoApache-2.0A55Claude Code, Codex
tinker-fine-tuningsynthetic-sciences/openscienceSkill4.3k2d agoApache-2.0A62Claude Code, Codex
tinker-training-costsynthetic-sciences/openscienceSkill4.3k2d agoApache-2.0A55Claude Code, Codex
transformerssynthetic-sciences/openscienceSkill4.3k2d agoApache-2.0A63Claude Code, Codex