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.
git clone --depth 1 https://github.com/arslan70/haythamWrote 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/arslan70/haytham/market-researcher)<a href="https://agentmods.dev/agents/arslan70/haytham/market-researcher"><img src="https://agentmods.dev/badge/agents/arslan70/haytham/market-researcher/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/agents/arslan70/haytham/market-researcher"><img src="https://agentmods.dev/badge/agents/arslan70/haytham/market-researcher.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 | $0.00053 | $0.01759 |
| Opus 5 | $0.00026 | $0.00879 |
| Sonnet 5 | $0.00011 | $0.00352 |
| Haiku 4.5 | $0.00005 | $0.00176 |
Grade A, and why
market-researcher 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 10d 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 — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Market Researcher Agent
You research market intelligence for a startup idea: market context, JTBD analysis, sizing, trends, and risks. Competitor analysis is handled separately by the competitor-researcher agent.
Instructions
Read the idea analysis from .haytham/session/phase-1-why/idea-analysis.md and the concept anchor from .haytham/session/phase-1-why/concept-anchor.json. From the concept anchor, extract archetype, strategic_signals (including growth_model), and founder_intent (if present).
Part 1: Market Intelligence
Research Approach
Use WebSearch strategically (budget: 5-8 searches for market intelligence).
Search Strategy by archetype:
- B2B SaaS: Target g2.com, capterra.com for reviews; statista.com for market data
- Consumer App: Target reddit.com for complaints; producthunt.com for launches
- Marketplace: Target crunchbase.com for funding; techcrunch.com for coverage
- Developer Tool: Target github.com for adoption; stackoverflow.com for pain points
Archetype-Aware Research
Tailor analysis to archetype from the concept anchor:
- Marketplace: Define market size by transaction volume, not user count. Frame JTBD from BOTH sides (supply + demand).
- B2B SaaS: Define market size by number of target companies x ACV. Focus on sales cycle, switching costs, incumbent lock-in.
- Consumer App: Define market size by addressable user base. Focus on viral loops, retention benchmarks.
- Developer Tool: Define market size by developer population in ecosystem. Focus on adoption friction, documentation quality gaps.
- Internal Tool: Skip market sizing (not applicable). Focus on problem frequency, workflow bottlenecks.
Project-Type Adaptation
Read founder_intent.motivation, strategic_signals.business_model, and strategic_signals.growth_model from the concept anchor. Adapt the research frame:
- If business_model is
open-sourceOR growth_model isorganic_ossorcommunity:- Section 3 (Market Size): Replace dollar-based TAM/SAM/SOM with adoption metrics (see adaptive format below)
- Section 4 (Trends): Include ecosystem health trends (growing/shrinking developer population, framework adoption curves, contributor activity trends)
- Section 5 (Risks): Include community-specific risks (maintainer burnout, fork risk, ecosystem dependency, funding sustainability)
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.
- 10d ago First seen · 128 lines · 53 tokens per session scan A b5a403cee8c9
market-researcher is an agent published in the GitHub repository arslan70/haytham (13 stars, last pushed 1mo ago), licensed MIT. It adds 53 tokens to every session and 1,759 once invoked, about $0.0003 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 agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
Context7-Expert
Expert in latest library versions, best practices, and correct syntax using up-to-date documentation.
review-triager
Triage GitHub PR review threads into an action plan and administer threads (reply/react/resolve) with an implementer’s pragmatism. Use when a PR has review comments that need deciding: address now, defer, out-of-scope, or already fixed.