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 oleg494/coding-kit --skill web-researchgit clone --depth 1 https://github.com/oleg494/coding-kitWrote 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/oleg494/coding-kit/web-research)<a href="https://agentmods.dev/skills/oleg494/coding-kit/web-research"><img src="https://agentmods.dev/badge/skills/oleg494/coding-kit/web-research/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/oleg494/coding-kit/web-research"><img src="https://agentmods.dev/badge/skills/oleg494/coding-kit/web-research.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 | $0.00078 | $0.00689 |
| Opus 5.5 | $0.00031 | $0.00276 |
| Sonnet 5.5 | $0.00016 | $0.00138 |
| Haiku 4.5 | $0.00008 | $0.00069 |
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 2d 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 — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Web Research — facts from the outside world
Workflow
- Define the missing external fact. Local code and established project facts do not need web corroboration.
- Read known primary URLs directly; search when the source is unknown. Use a browser only for interactive or dynamically rendered content.
- Primary sources, not retellings. Official docs, original research or source code; check the actual version and applicability.
- Cross-check where material. One authoritative source can establish a narrow fact; seek independent evidence for disputed, indirect or high-impact claims.
- Dating. Include the relevant version/date for time-sensitive facts.
- Answer with sources. Link external claims and identify remaining uncertainty. Do not invent facts when a source is unavailable.
Source hierarchy & fallback (403/429/captcha)
- Official docs / GitHub repo / source code — the primary source.
- Issue trackers, ADRs, engineering blogs — industry practice.
- Direct HTTP fetch of the page (
readon the URL) — when search engines block you.
On 403/429/captcha, try another legitimate source or access method without bypassing access controls. If sources remain unreachable, name the unresolved fact and what was tried; finish the parts that available evidence supports.
Research depth
Use enough evidence to resolve the question, not a fixed number of queries or pages. A definition can need one source; a technology comparison may require multiple alternatives, benchmarks and counterexamples. Stop when further search cannot materially change the answer.
What to look for
| Type of information | Where to look |
|---|---|
| API / library | Official documentation, GitHub README, source code |
| Industry practice | GitHub issues, ADRs, engineering blogs, Thoughtworks Tech Radar |
| Bug / error | GitHub issues, Stack Overflow, official bug tracker |
| Tool comparison | Benchmarks, practitioner articles, Hacker News discussions |
| Regulations / laws | Official sources (.gov, legal databases) |
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.
- 2d ago Changed 0e8f10c1143e
- 8d ago Changed f594900e6c41
- 11d ago Changed 96c3e2a70120
- 25d ago Changed 1d47f04ab19f
- 26d ago Changed 772ecbb04ede
- 1mo ago Changed 85956726a588
- 1mo ago Changed · +1 lines 1a7b06db6b31
- 1mo ago Changed 14fa1b78f41d
- 1mo ago Changed 6e674174b742
- 1mo ago First seen · 59 lines · 78 tokens per session scan A 1fd9fa22851f
web-research is a skill published in the GitHub repository oleg494/coding-kit (3 stars, last pushed 2d ago), licensed MIT. It adds 78 tokens to every session and 689 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
run
Execute a named agent role with optimized instructions. Explicit invocation only ($run). Never trigger implicitly.
tip
Deliver a transformative life perspective shift and a productivity tip. Use when the user invokes /tip or wants non-technical inspiration or a fresh mental model.
agentic-security-review
Run a security and dependency audit for agent systems, tool-using AI apps, MCP/A2A integrations, or security-sensitive AI-generated code. Check slopsquatting risk, tool shadowing, rug pulls, memory/context poisoning, secrets, unsafe permissions, and common CWE patterns. Use when asked for security review, dependency…
agentic-spec
Create a structured specification before agentic coding work. Assemble the six context types, scale rigor for prototype/internal/production tasks, produce SPEC.md, and configure focused AGENTS.md boundaries. Use when asked to write a spec, plan a feature, design an agent/system, define architecture, or create…
agentic-evals
Design evaluation contracts and test plans for agentic systems. Create deterministic tests, trajectory evals, quality dimensions, gold-set criteria, and CI gates before or after implementation. Use when asked for tests first, an eval plan, success criteria, non-deterministic testing, LLM-as-judge setup, or…
agentic-production-readiness
Prepare an AI agent system for production operation. Cover SHIELD controls, sandbox/canary/production rollout, OpenTelemetry observability with GenAI semantic conventions, Agent Card drafting, governance, and post-deploy monitoring. Use for production readiness checks, go-live checklists, agent monitoring, agent…