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Fbi Artcrimes

by io.github.pipeworx-io

Generate llms.txt

generate_llms_txt
Read-onlyIdempotent

Generate a production-ready llms.txt file for any URL so AI crawlers (ChatGPT, Claude, Perplexity) can index the site cleanly. Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format. Output is a single text blob ready to drop at site-root/llms.txt. Useful for: getting a client's site indexed by AI, drafting llms.txt for your own project, or auditing how an AI crawler would see a competitor.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesFull URL of the site to summarize, e.g. "https://example.com" or a specific landing page.
max_linksNoMaximum number of link entries to include (default 25, max 50).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare read-only, open-world, idempotent, and non-destructive. Description adds behavioral details: fetches page, extracts title/description/key links, emits standard format, output is a single text blob. This goes beyond annotations, though it doesn't cover potential issues like rate limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a concise paragraph of three sentences. It front-loads the main action and purpose, and every sentence adds value. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (2 params, no output schema), the description covers the purpose, process, and output format. It is complete and leaves no significant gaps for an agent to understand usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% with clear descriptions for both parameters. The description doesn't add specific parameter details, but the schema is sufficient. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it generates a production-ready llms.txt file for any URL. It specifies the verb 'generate', the resource 'llms.txt file', and the scope 'for any URL'. It details the process (fetches, extracts, emits) and lists use cases, distinguishing it from siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly provides usage scenarios: getting a client's site indexed, drafting for own project, auditing competitors. It does not mention exclusions, but the context is clear and sufficient for selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Fbi Artcrimes toolsInspect
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TDQS

A3.7/5.0
Disambiguation2/5

ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical routers (beta is currently exactly the same as stable), and the Polymarket tools (polymarket_edges, polymarket_arbitrage, polymarket_edge_tracker, polymarket_fill_risk, bet_research) all scan or price prediction-market opportunities with fuzzy boundaries. Other clusters like memory and subscriptions are clear, but enough overlap remains that an agent can easily misroute a query.

Naming Consistency3/5

Most names are readable snake_case and many follow a verb_noun shape (list_art_crimes, resolve_entity, validate_claim), but the set also contains noun-phrase names (entity_profile, recent_alerts, pipeworx_feedback, deep_research) and brand-prefixed composites (polymarket_kalshi_spread, ask_pipeworx_beta). This is mixed but still scannable; there is no outright convention chaos.

Tool Count2/5

33 tools exceeds the 25+ threshold and is bloated for a server whose name promises FBI art crimes—only two tools relate to that name. Even treated as a Pipeworx platform, the sprawl makes the tool surface harder to navigate than necessary.

Completeness2/5

For the nominal art-crime domain, only list_art_crimes and get_art_crime exist, with no category search, statistics, or art-crime alerting, so an agent expecting art-crime workflows hits dead ends. The unrelated Pipeworx functionality is broadly covered, but that does not make the set complete for its stated server purpose.

Resources