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 agentmods add skills/maxedapps/agent-skills/web-researchnpx skills add maxedapps/agent-skills --skill web-researchgit clone --depth 1 https://github.com/maxedapps/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/maxedapps/agent-skills/web-research)<a href="https://agentmods.dev/skills/maxedapps/agent-skills/web-research"><img src="https://agentmods.dev/badge/skills/maxedapps/agent-skills/web-research.svg" alt="Measured on agentmods" 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 | $0.00088 | $0.01280 |
| Opus 5 | $0.00044 | $0.00640 |
| Sonnet 5 | $0.00018 | $0.00256 |
| Haiku 4.5 | $0.00009 | $0.00128 |
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 4d 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 — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Web Research
Instruction priority
Follow explicit user constraints and higher-priority instructions. If the user narrows scope, forbids external tools, requests chat-only output, or changes this workflow, adapt and briefly note meaningful deviations.
Use the best currently available search, content-retrieval, repository, document, media, and browser capabilities. Tool names and schemas differ between runtimes: inspect the available tools instead of assuming a particular function name.
Core rules
- For substantive multi-source, conflicting, resumable, implementation-critical, or high-risk research, create or reuse
.progress/<research-slug>.mdearly for questions, context, search angles, sources, findings, conflicts, rejected evidence, open questions, and synthesis decisions. - Small direct lookups or source reads do not require a progress artifact. Preserve answer-critical sources and findings in the response.
- When progress notes exist, reread them before final responses, handoffs, compaction summaries, or user-requested summaries.
- Prefer primary sources: official docs, source repositories, release notes, changelogs, standards, vendor announcements, and first-party data.
- Read answer-critical source content. Search snippets and generated summaries are discovery aids, not sufficient evidence for behavior-sensitive claims.
- Continue with targeted follow-up when evidence is incomplete, ambiguous, outdated, conflicting, version-mismatched, or available only from weak secondary sources.
- For code/dependency research, identify the exact installed or targeted version from project files before judging behavior. Record runtime, adapter, framework, and integration boundaries that could affect the answer.
- For signatures, hashing, serialization, canonicalization, authentication, or wire protocols, require an independent official implementation, test vector, or interoperability check; a self-consistent round trip is not enough.
- Stop when material questions are supported, remaining gaps are explicitly non-material, or further useful evidence is unlikely.
- Cite source URLs clearly and state uncertainty instead of guessing.
- Never store secrets, credentials, private session data, or sensitive source content in research notes.
What ships with it
3 files 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.
- 4d ago First seen · 82 lines · 88 tokens per session scan A d849c7b979e1
web-research is a skill published in the GitHub repository maxedapps/agent-skills (58 stars, last pushed 20d ago), licensed MIT. It adds 88 tokens to every session and 1,280 once invoked, about $0.0004 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
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…