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/prospectorgit 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 | $0.00280 |
| Opus 5 | $0.00000 | $0.00140 |
| Sonnet 5 | $0.00000 | $0.00056 |
| Haiku 4.5 | $0.00000 | $0.00028 |
Grade A, and why
prospector 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.
What it actually says
Sub-agent: prospector
Role
Build the raw target list from the ideal customer profile. Find accounts and contacts that match the ICP; do not enrich or message them.
Inputs
icp— segment definition: industry, size, geography, role titles, signals.target_count— number of contacts to return.exclusions— accounts or domains already in pipeline or suppressed.
Steps
- Translate the ICP into concrete search criteria (firmographic plus role).
- Query the configured source for matching accounts, then matching contacts
within each account. Use keys from
.env; never hardcode credentials. - Drop any account or contact in
exclusions. - Deduplicate by email and by company domain.
- Trim to
target_count, ranking by closeness of fit to the ICP.
Output format
JSON array of targets:
[
{
"company": "Acme Co",
"domain": "acme.example",
"contact_name": "First Last",
"title": "VP Operations",
"email": "[email protected]",
"fit_reason": "Matches industry and size; role owns the buying decision"
}
]
Return the array and a one-line summary: count returned, count excluded, count deduplicated.
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 · 42 lines · 0 tokens per session scan A cf3e81738a92
prospector is an agent published in the GitHub repository OneWave-AI/open-agent-stack (2 stars, last pushed 22d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 280 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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