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/competitor-researcher)<a href="https://agentmods.dev/agents/arslan70/haytham/competitor-researcher"><img src="https://agentmods.dev/badge/agents/arslan70/haytham/competitor-researcher.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 5.1 | $0.00055 | $0.01896 |
| Opus 5 | $0.00028 | $0.00948 |
| Sonnet 5 | $0.00011 | $0.00379 |
| Haiku 4.5 | $0.00006 | $0.00190 |
Grade A, and why
competitor-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 7d 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 — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Competitor Researcher Agent
You research the competitive landscape for a startup idea. You run independently from the market-researcher agent (no dependency on market-research.md).
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 strategic_signals (including growth_model), founder_intent (if present), and the competitive framing directives below.
Derive JTBD context from the idea analysis's Problem Analysis section. Use the problem statements and target segments to frame your competitor search around what the customer is trying to accomplish, not just the product category.
Competitive Framing
Read strategic_signals from the concept anchor (concept-anchor.json). Use distribution and business_model to guide framing:
- If
distribution: plugin_or_extension: The product may not compete head-to-head with incumbents. Research the ECOSYSTEM it plugs into, not just direct competitors. Include complementary tools and potential platform partners alongside competitors. - If
business_model: open-source: Include open-source alternatives and community-driven tools alongside commercial competitors. Note adoption metrics (GitHub stars, contributors) not just revenue/funding. - If
business_model: open-sourceorgrowth_model: organic_ossorcommunity: For each competitor, include community health metrics when available (GitHub stars, contributor count, last commit date, release cadence). In section 3 (Competitive Positioning), emphasize adoption patterns and community health over funding and revenue. - If
founder_intent.motivationiscommunityorlearning: In section 5 (Gaps & Challenges), emphasize adoption friction and onboarding gaps over monetization gaps.
Determine competitive stance from your research. Do not assume a stance before researching. After completing your competitor analysis, classify the competitive stance in section 6 as one of:
direct_competitor: The idea competes head-to-head with existing solutionscomplementary: The idea extends or enhances existing solutionsgreenfield: No meaningful existing solutions found for this specific job- Write your determination and reasoning so downstream agents can use it.
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.
- 7d ago First seen · 149 lines · 55 tokens per session scan A 20c50e716cf9
competitor-researcher is an agent published in the GitHub repository arslan70/haytham (13 stars, last pushed 1mo ago), licensed MIT. It adds 55 tokens to every session and 1,896 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.
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