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-positioning-analysisgit 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-positioning-analysis)<a href="https://agentmods.dev/skills/agentera/agently/market-positioning-analysis"><img src="https://agentmods.dev/badge/skills/agentera/agently/market-positioning-analysis.svg" alt="Measured on agentmods" 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 | $0.00028 | $0.00104 |
| Opus 5 | $0.00014 | $0.00052 |
| Sonnet 5 | $0.00006 | $0.00021 |
| Haiku 4.5 | $0.00003 | $0.00010 |
Grade A, and why
Market Positioning Analysis 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.
What it actually says
Market Positioning Analysis
Given product context, produce: a 2-3 paragraph market landscape, one crisp positioning statement, and 3-5 differentiators grounded in the product's features, pricing, and competitive set.
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.
- 9d ago First seen · 14 lines · 28 tokens per session scan A bf67df1ab693
Market Positioning Analysis is a skill published in the GitHub repository AgentEra/Agently (1,649 stars, last pushed yesterday), licensed Apache-2.0. It adds 28 tokens to every session and 104 once invoked, about $0.0001 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
python-run
Run and debug Python scripts in the project. Use when the user says "run python", "execute this script", "debug this py file", or wants to run/modify a .py file. Handles dependency checks, linting, execution, and error analysis.
python
Python package management.
jupyter-live-kernel
Iterative Python via live Jupyter kernel (hamelnb).
python-feature-lifecycle
Guidance for package and feature lifecycle in the Agent Framework Python codebase, including stage meanings, feature-stage decorators, feature enums, and how to move APIs from one stage to the next.
python-development
Coding standards, conventions, and patterns for developing Python code in the Agent Framework repository. Use this when writing or modifying Python source files in the python/ directory.
hive.chart-creation-foundations
Required reading whenever any chart tool is available. Teaches the one-tool embedding contract (call chartrender → live chart appears in chat AND a downloadable PNG lands in the queen session dir), the ECharts (data viz) vs Mermaid (structural diagrams) decision, the BI/financial-grade aesthetic baseline (no…