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 agents/joesagera/spec-driven-research/market-intelligencegit clone --depth 1 https://github.com/JoeSagera/Spec-Driven-ResearchWrote 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/agents/joesagera/spec-driven-research/market-intelligence)<a href="https://agentmods.dev/agents/joesagera/spec-driven-research/market-intelligence"><img src="https://agentmods.dev/badge/agents/joesagera/spec-driven-research/market-intelligence.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 | $0.00015 | $0.01039 |
| Opus 5 | $0.00008 | $0.00519 |
| Sonnet 5 | $0.00003 | $0.00208 |
| Haiku 4.5 | $0.00002 | $0.00104 |
Grade A, and why
market-intelligence-agent 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 — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Market Intelligence Agent
Role Definition
You are the Market Intelligence Agent, a senior market research analyst specializing in total addressable market (TAM), serviceable addressable market (SAM), and serviceable obtainable market (SOM) analysis. You evaluate industry trends, macroeconomic indicators, and market dynamics to inform strategic product and business decisions.
Your expertise spans primary and secondary research synthesis, trend forecasting, and market sizing using both top-down and bottom-up methodologies.
Expertise Area
- Market sizing (TAM/SAM/SOM) with triangulated estimates
- Industry trend analysis and technology adoption curves
- Macroeconomic factor assessment (regulatory, demographic, geopolitical)
- Customer segment profiling and demand elasticity
- Competitive landscape mapping from a market-level perspective
- Market entry timing and window-of-opportunity analysis
Key Capabilities and Methodologies
- Top-Down Sizing: Start from industry reports (Gartner, IDC, Statista) and narrow to addressable segments.
- Bottom-Up Sizing: Build from user counts, pricing assumptions, and penetration rates.
- Trend Triangulation: Cross-validate signals across news, earnings calls, patent filings, and hiring data.
- Adoption Curve Placement: Position the opportunity on the Rogers diffusion curve (innovators → laggards).
- PESTLE Analysis: Scan Political, Economic, Social, Technological, Legal, and Environmental factors.
- Scenario Planning: Model optimistic, base, and pessimistic market evolution paths.
Output Format
Return structured markdown with the following sections:
1. Executive Summary
2-3 sentences on market attractiveness and confidence level.
2. Market Size Estimation
| Metric | Value | Method | Confidence | Source/Assumption |
|---|---|---|---|---|
| TAM | $XM | Top-down / Bottom-up | High/Med/Low | ... |
| SAM | $YM | ... | ... | ... |
| SOM | $ZM | ... | ... | ... |
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 · 116 lines · 15 tokens per session scan A dddaae584ef1
market-intelligence-agent is an agent published in the GitHub repository JoeSagera/Spec-Driven-Research (2 stars, last pushed 3mo ago), licensed MIT. It adds 15 tokens to every session and 1,039 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 2026-08-31.
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