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 prime-radiant-inc/greenfield --skill autonomous-discoverygit clone --depth 1 https://github.com/prime-radiant-inc/greenfieldWrote 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/prime-radiant-inc/greenfield/autonomous-discovery)<a href="https://agentmods.dev/skills/prime-radiant-inc/greenfield/autonomous-discovery"><img src="https://agentmods.dev/badge/skills/prime-radiant-inc/greenfield/autonomous-discovery/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/prime-radiant-inc/greenfield/autonomous-discovery"><img src="https://agentmods.dev/badge/skills/prime-radiant-inc/greenfield/autonomous-discovery.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 638 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- medium MCP Rug Pull · line 455 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.00030 | $0.07226 |
| Opus 5 | $0.00015 | $0.03613 |
| Sonnet 5 | $0.00006 | $0.01445 |
| Haiku 4.5 | $0.00003 | $0.00723 |
Grade A, and why
autonomous-discovery scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s -o /dev/null -w "%{http_code}" "http://localhost:$port/health" 2>/dev/null How it starts
The opening of the file, as written. The whole thing — 696 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Autonomous Discovery
Discover and inventory every intelligence source available for the target product. Produce a manifest that downstream agents use to plan their analysis.
The Core Principle
Find everything. Catalog it. Ask the user what you missed.
Discovery is the first thing that runs in Layer 1. Before any analysis agent touches the target, the discovery agent surveys all available intelligence sources — local files, public information, running services, and derivable artifacts. The output is a structured inventory that drives all subsequent dispatch decisions.
When This Skill Applies
This skill is loaded by analyzer agents dispatched with the discovery-agent role. It runs once at the start of Layer 1, before any analysis mode agents are dispatched.
Four-Phase Discovery
digraph discovery {
rankdir=TB;
"Start discovery" [shape=doublecircle];
"Phase 1: Local filesystem scan" [shape=box];
"Phase 2: Web search" [shape=box];
"Phase 3: Service detection" [shape=box];
"Phase 4: Derived source assessment" [shape=box];
"Write inventory manifest" [shape=box];
"User negotiation" [shape=box];
"Write dispatch mapping" [shape=box];
"Discovery complete" [shape=doublecircle];
"Start discovery" -> "Phase 1: Local filesystem scan";
"Phase 1: Local filesystem scan" -> "Phase 2: Web search";
"Phase 2: Web search" -> "Phase 3: Service detection";
"Phase 3: Service detection" -> "Phase 4: Derived source assessment";
"Phase 4: Derived source assessment" -> "Write inventory manifest";
"Write inventory manifest" -> "User negotiation";
"User negotiation" -> "Write dispatch mapping";
"Write dispatch mapping" -> "Discovery complete";
}
Phase 1: Local Filesystem Scan
Survey the target path and its surrounding context. Read directory structures, detect file types, and catalog everything that could feed analysis.
1.1 Source Code Detection
Detect source code by file extension. Do not assume a single language — multi-language projects are common.
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.
- 11d ago First seen · 696 lines · 30 tokens per session scan A cfae7bb92ac4
autonomous-discovery is a skill published in the GitHub repository prime-radiant-inc/greenfield (277 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 30 tokens to every session and 7,226 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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