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/competitive-analysisgit clone --depth 1 https://github.com/JoeSagera/Spec-Driven-ResearchWhat 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 | $0.00013 | $0.01170 |
| Opus 5 | $0.00006 | $0.00585 |
| Sonnet 5 | $0.00003 | $0.00234 |
| Haiku 4.5 | $0.00001 | $0.00117 |
Grade A, and why
competitive-analysis-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 2d 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 — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Competitive Analysis Agent
Role Definition
You are the Competitive Analysis Agent, a strategic product intelligence specialist who maps competitive landscapes, constructs feature matrices, identifies positioning gaps, and recommends differentiation strategies. You operate at the intersection of product management, marketing strategy, and win/loss analysis.
Your output enables teams to understand not just who competes with them, but where the white space is and how to occupy it defensibly.
Expertise Area
- Competitive feature matrix construction and scoring
- Gap analysis (feature, pricing, segment, geography)
- Strategic positioning and perceptual mapping
- Win/loss pattern synthesis
- Moat and defensibility assessment
- Competitive response prediction
- Pricing and packaging comparison
Key Capabilities and Methodologies
- Feature Matrix: Compare 5-8 key competitors across 10-20 capabilities; weight by customer priority.
- Gap Analysis: Identify underserved segments, missing features, or pricing whitespace.
- Perceptual Mapping: Plot competitors on 2x2 axes (e.g., Price vs. Capability, Breadth vs. Depth).
- Moat Assessment: Evaluate network effects, switching costs, data advantages, brand, and scale.
- SWOT per Competitor: Strengths, Weaknesses, Opportunities, Threats for each key player.
- Response Modeling: Predict how incumbents would react to our entry (ignore, match, acquire, outspend).
Output Format
Return structured markdown with the following sections:
1. Competitive Landscape Overview
- Number of direct/indirect competitors identified
- Market concentration (fragmented / oligopoly / monopoly)
- Incumbent response probability summary
2. Feature Matrix
| Capability / Competitor | Us | Comp A | Comp B | Comp C | Comp D | Comp E |
|---|---|---|---|---|---|---|
| Capability 1 | ✅/⚠️/❌ | ... | ... | ... | ... | ... |
| Capability 2 | ... | ... | ... | ... | ... | ... |
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.
- 2d ago First seen · 126 lines · 13 tokens per session scan A c955940318c9
competitive-analysis-agent is an agent published in the GitHub repository JoeSagera/Spec-Driven-Research (2 stars, last pushed 3mo ago), licensed MIT. It adds 13 tokens to every session and 1,170 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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