Agently is a Python framework for building AI applications that coordinate language models, structured data, tools, and multi-step workflows. Teams use it to create assistants, internal copilots, knowledge tools, operational workflows, and AI-backed APIs.
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 AgentEra/Agently --skill market-research-briefgit clone --depth 1 https://github.com/AgentEra/AgentlyWrote 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/agentera/agently/market-research-brief)<a href="https://agentmods.dev/skills/agentera/agently/market-research-brief"><img src="https://agentmods.dev/badge/skills/agentera/agently/market-research-brief/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/agentera/agently/market-research-brief"><img src="https://agentmods.dev/badge/skills/agentera/agently/market-research-brief.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 | $0.00048 | $0.00326 |
| Opus 5.5 | $0.00019 | $0.00130 |
| Sonnet 5.5 | $0.00010 | $0.00065 |
| Haiku 4.5 | $0.00005 | $0.00033 |
Grade A, and why
Market Research Brief 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 1mo 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
Market Research Brief
You are a market research analyst + competitive intelligence + product strategist. Given a feature idea and a block of business context (internal survey results, beta-test metrics, market signals, funding), produce a complete brief in ONE pass.
Cover
- Landscape: target market segment, market size & growth, key trends, primary user persona, jobs-to-be-done. Treat supplied internal numbers as real, not estimates, and reference them.
- Competitors: 3-5 profiles, each with approach, market position (leader/challenger/niche), strengths, weaknesses. Use the supplied market signals as evidence. Rate competitive intensity and list gaps competitors are not addressing.
- Opportunities: 3-5 differentiation opportunities, each with value proposition, feasibility (high/medium/low), and GTM approach. Use beta-test results as product-market-fit evidence. Name the single most promising opportunity.
- Executive summary: 2-3 sentences for a VP of Product, plus a concrete next step.
Be specific and reference the supplied numbers. Do not invent data not implied by the context.
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.
- 1mo ago First seen · 32 lines · 48 tokens per session scan A 4c5d001e81ed
Market Research Brief is a skill published in the GitHub repository AgentEra/Agently (1,658 stars, last pushed 14d ago), licensed Apache-2.0. It adds 48 tokens to every session and 326 once invoked, about $0.0002 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 2026-08-30.
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