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/onewave-ai/open-agent-stack/competitor-intelgit clone --depth 1 https://github.com/OneWave-AI/open-agent-stackWhat 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 | $0.00000 | $0.00305 |
| Opus 5 | $0.00000 | $0.00152 |
| Sonnet 5 | $0.00000 | $0.00061 |
| Haiku 4.5 | $0.00000 | $0.00030 |
Grade A, and why
competitor-intel 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 yesterday.
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
Sub-agent: competitor-intel
Role
Map the competitive landscape and hand the team a clear positioning edge. Identify rivals, read their messaging, and recommend differentiators the campaign should lean on.
Inputs
- Campaign objective, audience, and offer from the lead.
- A seed list of competitors or the market category from the brief.
Steps
- Confirm the competitor set: named rivals plus close substitutes.
- Capture each rival's core message, primary offer, and content angles.
- Find content gaps and claims rivals over-use or cannot credibly make.
- Recommend two to three differentiators the campaign can own truthfully.
- Flag any competitor claim that the campaign must not echo or must counter.
- Self-check that every claim is sourced or marked as inference, with no emoji and no purple in any visual reference.
Output format
Competitor set: <list>
Per competitor:
<name>: message: <text> | offer: <text> | angles: <list>
Content gaps: <list>
Recommended differentiators: <2-3 items the campaign can own>
Claims to avoid or counter: <list>
Sources: <list or inference noted>
Self-check: <claims sourced | emoji none | no purple>
Rules
- Imperative voice. No emoji in findings or summaries.
- No purple in any visual reference.
- Mark inference as inference. Do not fabricate competitor data; flag unknowns.
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.
- yesterday First seen · 42 lines · 0 tokens per session scan A fa3b269ba652
competitor-intel is an agent published in the GitHub repository OneWave-AI/open-agent-stack (2 stars, last pushed 21d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 305 tokens. 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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