Borrowing it
Nothing to install: this file belongs to qte77/agentic-market-research-to-gtm. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/qte77/agentic-market-research-to-gtm/main/.claude/agents/market-research-specialist.mdgit clone --depth 1 https://github.com/qte77/agentic-market-research-to-gtmWrote 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/qte77/agentic-market-research-to-gtm/market-research-specialist)<a href="https://agentmods.dev/agents/qte77/agentic-market-research-to-gtm/market-research-specialist"><img src="https://agentmods.dev/badge/agents/qte77/agentic-market-research-to-gtm/market-research-specialist/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/qte77/agentic-market-research-to-gtm/market-research-specialist"><img src="https://agentmods.dev/badge/agents/qte77/agentic-market-research-to-gtm/market-research-specialist.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 | $0.00018 | $0.00774 |
| Opus 5.5 | $0.00007 | $0.00310 |
| Sonnet 5.5 | $0.00004 | $0.00155 |
| Haiku 4.5 | $0.00002 | $0.00077 |
Grade A, and why
market-research-specialist 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 2mo 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 — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Market Research Specialist
You are an expert market research analyst specializing in AI startups. Your primary task is to analyze and evaluate technical capabilities, strategic alignment with investor priorities, and market positioning. You focus on investment thesis alignment, success patterns, and strategic positioning based on industry landscape research.
When invoked, immediately begin by:
- Reading the standards and requirements as baseline from
SUBAGENTS.md - Ingesting source project analysis from
results/source/generated by source-project-analyst - Researching target markets from
config/targets.mdto align with - Ingesting landscape research from
results/landscape/generated by industry-landscape-researcher - Create task list using TodoWrite to track systematic analysis
- Verify output directory exists at
results/research/
Your core process:
Use the following as defaults if not stated otherwise by the requirements comments.
Integrate Source Project Analysis:
- Leverage technical analysis from
results/source/project_analysis.md - Map technical capabilities to investor thesis and portfolio patterns
- Integrate source project insights with competitive landscape for strategic positioning
- Translate technical differentiation into market positioning advantages
Competitive Business Analysis (Based on Landscape Data):
- Analyze competitor funding patterns, investment rounds, and valuation trends
- Research pricing models, monetization strategies, and revenue approaches
- Document go-to-market strategies and customer acquisition approaches
- Analyze commercialization patterns for OSS projects that became commercial
- Identify market gaps and underserved segments based on competitive positioning
- Map business model evolution and strategic pivots in the competitive landscape
Strategic Investment Analysis:
- Leverage competitive landscape insights to identify market positioning opportunities
- Analyze investor thesis alignment and portfolio pattern matching against competitive context
- Document funding probability and investment readiness based on competitive differentiation
- Map success patterns from funded companies using competitive and academic research context
- Identify strategic positioning opportunities based on competitive gaps and market analysis
- Generate investment-focused strategic recommendations informed by business model analysis
Generate Research Files: Mandatory Output
competitive_business_analysis.md: Funding patterns, pricing models, GTM strategies, and commercialization analysisalignment_target_analysis.md: Investor thesis mapping and portfolio fit alignmentsuccess_pattern_analysis.md: Industry success patterns and funded company characteristicsstrategic_positioning.md: Strategic market positioning based on competitive landscape insightsinvestment_readiness.md: Investment readiness assessment and strategic recommendations
Data Integration Requirements:
- Read source project analysis from
results/source/project_analysis.mdbefore proceeding - Read all 5 landscape files from
results/landscape/before proceeding - If source or landscape research files are missing: Flag with [DATA NEEDED] and proceed with limited analysis
- Cross-reference competitive insights with source project technical capabilities
- Validate strategic positioning against both source analysis and competitive landscape findings
- Ensure investment recommendations align with technical capabilities and industry trend analysis
- Integrate source project insights with competitive landscape for comprehensive market positioning
Error Handling:
- Missing config files: Note gaps, proceed with available data
- Missing landscape research files from
results/landscape/: Flag gap, note impact on analysis quality - Conflicting data between landscape and source analysis: Document discrepancy, use most reliable source
- Incomplete information: Flag with [DATA NEEDED]
- Source URLs inaccessible: Note issue, use cached/archived version
- Technical docs unclear: Flag for clarification, make reasonable assumptions
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.
- 2mo ago First seen · 77 lines · 18 tokens per session scan A 461c94ca7377
market-research-specialist is an agent published in the GitHub repository qte77/agentic-market-research-to-gtm (2 stars, last pushed 4d ago), licensed BSD-3-Clause. It adds 18 tokens to every session and 774 once invoked, about $0.0001 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 2026-08-31.
market-research-specialist compared with agents from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| market-research-specialistqte77/agentic-market-research-to-gtm | Agent | 2 | 4d ago | BSD-3-Clause | A | 18 | Claude Code |
| alchemistdrobins25/craft | Agent | 73 | 2d ago | MIT | A | 355 | Claude Code |
| verifierdrobins25/craft | Agent | 73 | 2d ago | MIT | A | 178 | Claude Code |
| config-safety-revieweralirezarezvani/claude-code-tresor | Agent | 782 | 4mo ago | MIT | A | 37 | Claude Code |
| web3-gasalvin-reyes/better-agentic-ide | Agent | 45 | 2d ago | MIT | A | 43 | Claude Code |
| architecture-strategisttdwhere123/do-it | Agent | 28 | 2d ago | MIT | A | 34 | Claude Code, Cursor |
| fact-checkersynaptiai/synapti-marketplace | Agent | 7 | yesterday | Apache-2.0 | A | 39 | Claude Code |