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 skills add iFurySt/aifi --skill competitive-landscape-analysisgit clone --depth 1 https://github.com/iFurySt/aifiWrote 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/skills/ifuryst/aifi/competitive-landscape-analysis)<a href="https://agentmods.dev/skills/ifuryst/aifi/competitive-landscape-analysis"><img src="https://agentmods.dev/badge/skills/ifuryst/aifi/competitive-landscape-analysis.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 | $0.00072 | $0.00355 |
| Opus 5 | $0.00036 | $0.00178 |
| Sonnet 5 | $0.00014 | $0.00071 |
| Haiku 4.5 | $0.00007 | $0.00036 |
Grade A, and why
competitive-landscape-analysis 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 8d 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.
What it actually says
Competitive Landscape Analysis
Use this skill to explain what the target is competing against and where its position is strengthening or weakening. Keep peer selection explicit; bad peer sets produce misleading conclusions.
Workflow
- Load the target profile and peer set.
- Validate peers by business segment, customer problem, geography, and investor comparability.
- Compare product position, growth, margins, capital intensity, strategy, and valuation where data is available.
- Identify substitutes and ecosystem dependencies, not only direct public peers.
- Save the comparison under
research/targets/<target>/evidence/competitors/. - Hand off durable advantages, threats, and open questions to thesis and risk skills.
Read references/peer-comparison-framework.md before building the comparison.
Output
Return:
- peer set and rationale
- direct competitors, substitutes, suppliers, and customers where relevant
- comparison table
- target strengths and weaknesses
- market-structure notes
- archive files created or updated
- thesis and risk handoffs
Quality Gate
Before finishing:
- explain why each peer belongs in the comparison
- avoid comparing unrelated multiples without business-model context
- separate current evidence from strategic speculation
- mark missing private-company or segment data
- preserve a list of excluded peers when exclusion affects interpretation
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 8d ago First seen · 48 lines · 72 tokens per session scan A 5e9a19f65d24
competitive-landscape-analysis is a skill published in the GitHub repository iFurySt/aifi (22 stars, last pushed 1mo ago), licensed MIT. It adds 72 tokens to every session and 355 once invoked, about $0.0004 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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