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 oxbshw/LLM-Agents-Ecosystem-Handbook --skill research-summarizergit clone --depth 1 https://github.com/oxbshw/LLM-Agents-Ecosystem-HandbookWrote 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/oxbshw/llm-agents-ecosystem-handbook/research-summarizer)<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.
<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>- 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 | $0.00026 | $0.00550 |
| Opus 5 | $0.00013 | $0.00275 |
| Sonnet 5 | $0.00005 | $0.00110 |
| Haiku 4.5 | $0.00003 | $0.00055 |
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 12d 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.
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-auditoror 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
- Plan: produce 3–7 sub-questions covering breadth and depth
- Search + fetch: for each sub-question, run
web_searchthenfetch_urlfor top 2–3 hits - Cluster: group findings by claim; load
references/clustering-rules.md - Draft: fill
references/report-template.md— every claim needs a[n]citation - Validate: every citation resolves; no domain dominates (≥ 3 distinct domains for shallow, ≥ 5 for deep)
- Self-review against success criteria below
References
references/report-template.md— the output structure- (add
clustering-rules.md,domain-allowlist.mdas the skill matures)
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
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.
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.
- 12d ago First seen · 54 lines · 26 tokens per session scan A a8ea6545162a
research-summarizer is a skill published in the GitHub repository oxbshw/LLM-Agents-Ecosystem-Handbook (546 stars, last pushed 2mo ago), licensed MIT. It adds 26 tokens to every session and 550 once invoked, about $0.0001 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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