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 solofounder-ai/solofounder --skill live-researchgit clone --depth 1 https://github.com/solofounder-ai/solofounderWrote 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/solofounder-ai/solofounder/live-research)<a href="https://agentmods.dev/skills/solofounder-ai/solofounder/live-research"><img src="https://agentmods.dev/badge/skills/solofounder-ai/solofounder/live-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/solofounder-ai/solofounder/live-research"><img src="https://agentmods.dev/badge/skills/solofounder-ai/solofounder/live-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 | $0.00037 | $0.02648 |
| Opus 5 | $0.00018 | $0.01324 |
| Sonnet 5 | $0.00007 | $0.00530 |
| Haiku 4.5 | $0.00004 | $0.00265 |
Grade A, and why
live-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 11d 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 — 243 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Live Research
Overview
LLM training data is 1-2 years old. Every technology recommendation based on memory alone is potentially wrong — outdated versions, deprecated APIs, renamed packages, changed pricing, new better alternatives.
Core principle: Never recommend a specific version, framework, API, or model from memory. Always verify with live documentation first.
Violating this rule produces confident, detailed, wrong advice — the most dangerous kind.
When to Use
Before ANY output that depends on current state of the world:
- Framework/library versions — "Use React Native 0.84" → is 0.76 actually the latest?
- AI model recommendations — "Use GPT-4" → is there a newer model? What's the current pricing?
- API endpoints/syntax — "Call /v1/completions" → has the API changed?
- Package names — "npm install X" → does X still exist? Was it renamed?
- Pricing/limits — "The free tier includes..." → has pricing changed?
- Best practices — "Use X pattern" → is this still the recommended approach?
- Platform requirements — "Requires iOS 16+" → what's the current minimum?
- Service availability — "Deploy to X" → is X still available/recommended?
- UI/UX design — "Design a dashboard" → what do top-rated current designs look like on Dribbble/Behance? What are current design trends, not 2-year-old patterns from training data?
The Rule
NEVER RECOMMEND FROM MEMORY ALONE.
Before suggesting any technology, version, API, model, or
tool — verify it exists, is current, and works as described
by checking live documentation.
"I'm fairly sure it's version X" is not verification.
"The docs say it's version X" is verification.
How to Verify
Use available research tools in this order of preference:
- Official documentation — fetch the actual docs page (WebFetch/WebSearch)
- Package registries — npm, PyPI, crates.io, pub.dev for current versions
- GitHub releases — check latest release tags
- API reference — verify endpoints, parameters, response formats
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.
- 11d ago First seen · 243 lines · 37 tokens per session scan A cf46f2143e07
live-research is a skill published in the GitHub repository solofounder-ai/solofounder (3 stars, last pushed 5mo ago), licensed MIT. It adds 37 tokens to every session and 2,648 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 2026-08-31.
Other skills, from other repositories
codex
Run the Codex CLI directly in the user's checkout for code analysis, refactoring, or automated editing without Claude Architect's verified delegation lifecycle.
commit
A guided process for committing code changes to Git. It checks the working tree, follows a conventional commit format, links a task when available, reviews the changes, and asks for approval.
x-multi-llm-align
A review process in which two sub-agents examine an API, data format, event schema, or workflow from their separate implementation perspectives. The user passes documents and feedback between them over multiple rounds.
design
Create a doc-as-code design package from a PRD or SPEC. Conditionally generates C4 diagrams (Context/Container/Component), sequence diagrams, ER diagram + Data Dictionary, OpenAPI 3.0, AsyncAPI 3.0, ADRs, domain glossary, state diagrams, and deployment view as Mermaid-rendered Markdown files. Use when PM mentions…
x-cr
A software-correctness investigation skill for finding why code behaves differently from what was expected. It uses evidence from code paths, specifications, tests, logs, and changes to assess possible causes.
explain
Use when user invokes /explain with a file path, directory path, function/class name, or natural language concept. Also triggers on "explain this", "how does X work", "walk me through". Produces a structured, layered explanation of what the code does, how it connects, and where to start if you need to change it. Do…