artifact-analyzer

A research assistant that scans specified project documents and extracts information relevant to a product idea.

In plain words
What is it for?
Use it to search planning notes, research, background documents, summaries, and large or split files for material related to a product brief.
Why use it?
It reduces the need to read every file manually when only some parts contain useful product context.

Agent

Install

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.

agentmods
npx agentmods add agents/kksudo/agentfs/artifact-analyzer
Clone the repo
git clone --depth 1 https://github.com/kksudo/AgentFS
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 574 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 88% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 2d ago against content hash dcd8c4bb367f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 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.

Origin

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.

_bmad/bmm/1-analysis/bmad-product-brief/agents/artifact-analyzer.md · 61 lines

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

  1. 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
  2. For sharded documents (a folder with index.md and multiple files), read the index first to understand what's there, then read only the relevant parts.

  3. 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.

  4. 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
  5. 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"
  ]
}

Read the full file on GitHub · 61 lines

Changes

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.

  1. 2d ago First seen · 61 lines · 0 tokens per session scan A dcd8c4bb367f

Subscribe to this mod's changes

artifact-analyzer is an agent published in the GitHub repository kksudo/AgentFS (2 stars, last pushed 4mo 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.