web-research

web-research is a skill for Codex from alfredxw/denova. It costs 37 tokens per session (1,018 once invoked), scanned A, original, Apache-2.0.

A workflow for researching current public-web information through searches and fetched source pages. It verifies important claims and produces an answer supported by sources.

In plain words
What is it for?
Use it for comparisons, fact-checking, current public information, and multi-source research where the answer should show evidence.
Why use it?
It reduces the chance of relying on outdated, incomplete, or unsupported information when the question needs up-to-date facts.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Good fit Use it for comparisons, fact-checking, current public information, and multi-source research where the answer should show evidence.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/alfredxw/denova/web-research
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 alfredxw/denova --skill web-research
Clone the repo
git clone --depth 1 https://github.com/alfredxw/denova

Made for: 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 web-research

README.md
[![agentmods](https://agentmods.dev/badge/skills/alfredxw/denova/web-research.svg)](https://agentmods.dev/skills/alfredxw/denova/web-research)
Your own site
<a href="https://agentmods.dev/skills/alfredxw/denova/web-research"><img src="https://agentmods.dev/badge/skills/alfredxw/denova/web-research.svg" alt="Measured on agentmods" height="20"></a>
Per session 37 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,018 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 $0.00037 $0.01018
Opus 5 $0.00018 $0.00509
Sonnet 5 $0.00007 $0.00204
Haiku 4.5 $0.00004 $0.00102

Measured 9d ago against content hash 75ba1dbe8639, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

web-research 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.

skills/web-research/SKILL.md · 53 lines

How it starts

The opening of the file, as written. The whole thing — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Web Research

Turn an open-ended question into a bounded, evidence-backed answer. Use search results to discover sources, fetch the promising pages, verify the important claims, and cite what actually supports the answer.

Do not use this workflow for a stable fact already known with high confidence or a simple transformation of text the user already supplied. If either required web tool is unavailable, state that limitation instead of pretending to have researched the web.

Workflow

  1. Define the research target.

    • Identify the decision or question, relevant region, time window, and what would count as sufficient evidence.
    • Resolve ambiguity with a reasonable stated assumption when possible. Ask only when different interpretations would materially change the result.
    • For vague terms such as “best,” “popular,” or “safe,” translate the term into observable criteria before searching.
  2. Plan distinct search angles.

    • Start with 2–4 meaningfully different queries, not repeated paraphrases. Cover the direct question, likely primary sources, an independent verification angle, and recency or criticism when relevant.
    • Put distinctive subjects, organizations, products, or domains early in each query. Avoid generic prefixes that can dominate matching, especially for Chinese current-events or trend searches.
    • Use time_range when freshness matters, but treat it as a best-effort filter and verify dates on fetched pages.
  3. Discover candidate sources with web_search.

    • Read warnings on every response. Partial provider failure does not invalidate good results, but it reduces coverage and may justify one focused follow-up query or a configured SearXNG source.
    • Treat search snippets as discovery hints, never as evidence for a final claim.
    • Prefer primary sources for first-party facts, official data, specifications, laws, and original research. Add independent sources for interpretation, criticism, comparisons, or disputed claims.
    • Avoid counting mirrors, syndications, or several pages repeating one press release as independent evidence.

Read the full file on GitHub · 53 lines

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. 9d ago First seen · 53 lines · 37 tokens per session scan A 75ba1dbe8639

Subscribe to this mod's changes

web-research is a skill published in the GitHub repository alfredxw/denova (696 stars, last pushed yesterday), licensed Apache-2.0. It adds 37 tokens to every session and 1,018 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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