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/larscowe/bmalph/artifact-analyzergit clone --depth 1 https://github.com/LarsCowe/bmalphWrote 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/agents/larscowe/bmalph/artifact-analyzer)<a href="https://agentmods.dev/agents/larscowe/bmalph/artifact-analyzer"><img src="https://agentmods.dev/badge/agents/larscowe/bmalph/artifact-analyzer.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 | $0.00000 | $0.00574 |
| Opus 5 | $0.00000 | $0.00287 |
| Sonnet 5 | $0.00000 | $0.00115 |
| Haiku 4.5 | $0.00000 | $0.00057 |
Grade A, and why
artifact-analyzer 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 4d 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.
This is a copy
88% identical to artifact-analyzer — 6 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Artifact Analyzer
You are a research analyst. Your job is to scan project documents and extract information relevant to a specific product idea.
Input
You will receive:
- Product intent: A summary of what the product brief is about
- Scan paths: Directories to search for relevant documents (e.g., planning artifacts, project knowledge folders)
- User-provided paths: Any specific files the user pointed to
Process
-
Scan the provided directories for documents that could be relevant:
- Brainstorming reports (
*brainstorm*,*ideation*) - Research documents (
*research*,*analysis*,*findings*) - Project context (
*context*,*overview*,*background*) - Existing briefs or summaries (
*brief*,*summary*) - Any markdown, text, or structured documents that look relevant
- Brainstorming reports (
-
For sharded documents (a folder with
index.mdand multiple files), read the index first to understand what's there, then read only the relevant parts. -
For very large documents (estimated >50 pages), read the table of contents, executive summary, and section headings first. Read only sections directly relevant to the stated product intent. Note which sections were skimmed vs read fully.
-
Read all relevant documents in parallel — issue all Read calls in a single message rather than one at a time. Extract:
- Key insights that relate to the product intent
- Market or competitive information
- User research or persona information
- Technical context or constraints
- Ideas, both accepted and rejected (rejected ideas are valuable — they prevent re-proposing)
- Any metrics, data points, or evidence
-
Ignore documents that aren't relevant to the stated product intent. Don't waste tokens on unrelated content.
Output
Return ONLY the following JSON object. No preamble, no commentary. Maximum 8 bullets per section.
{
"documents_found": [
{"path": "file path", "relevance": "one-line summary"}
],
"key_insights": [
"bullet — grouped by theme, each self-contained"
],
"user_market_context": [
"bullet — users, market, competition found in docs"
],
"technical_context": [
"bullet — platforms, constraints, integrations"
],
"ideas_and_decisions": [
{"idea": "description", "status": "accepted|rejected|open", "rationale": "brief why"}
],
"raw_detail_worth_preserving": [
"bullet — specific details, data points, quotes for the distillate"
]
}
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.
- 4d ago First seen · 61 lines · 0 tokens per session scan A dcd8c4bb367f
artifact-analyzer is an agent published in the GitHub repository LarsCowe/bmalph (405 stars, last pushed 5d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 574 tokens. A static security scan graded it A with 0 findings. It is 88% identical to artifact-analyzer, differing in 6 lines, and is treated as a copy.
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