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Thegamesdb

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).

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. Description adds that it fetches the page, extracts title/description/key links, and emits standard markdown, which enriches understanding without contradiction.

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?

Single paragraph under 70 words, front-loaded with core purpose, then functional detail, then use cases. Every sentence serves a purpose; no fluff.

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?

For a simple tool with 2 parameters, full annotation coverage, and no output schema, the description explains the process, output format, and usage scenarios completely. No gaps identified.

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 coverage is 100% with good descriptions for both parameters. The tool description does not add any additional meaning to the parameters beyond what the schema provides, so 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?

Description uses specific verb 'generate' and resource 'llms.txt file'. It clearly states the action: produce a standard file for AI crawlers by fetching a page and extracting key info. Distinguishes from siblings like scan_competitor_ai_presence by being a file generation tool rather than analysis.

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?

Explicitly lists use cases: getting client indexed, drafting own project, auditing competitors. Does not include when not to use but context is sufficient. Output note about dropping at site-root aids deployment decision.

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

All Thegamesdb toolsInspect
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TDQS

A3.6/5.0
Disambiguation2/5

The set contains several tightly overlapping clusters: ask_pipeworx vs ask_pipeworx_beta (currently identical) vs ask_pipeworx_grounded, five polymarket_* tools with related purposes, and entity_profile vs compare_entities vs recent_changes covering similar company-research ground. The four game tools are distinct but swamped by the unrelated Pipeworx majority, making correct tool selection genuinely difficult.

Naming Consistency2/5

No coherent naming scheme spans the set: snake_case verb_noun (get_game, list_platforms, scan_dependency) coexists with verb_prefix descriptors (ask_pipeworx, generate_llms_txt), domain-prefixed nouns (polymarket_edges, pipeworx_trending), and bare verbs like recall and forget. Even within the Pipeworx cluster, styles vary unpredictably (ask_pipeworx vs pipeworx_feedback vs scan_competitor_ai_presence).

Tool Count2/5

35 tools is far too many for a server named Thegamesdb, where only 4 of 35 tools relate to the game database at all. The remaining 31 tools constitute a broad Pipeworx data platform with heavy internal overlap, making the surface feel bloated rather than well-scoped.

Completeness2/5

For the declared TheGamesDB domain, coverage is minimal: search, get-by-id, and list genres/platforms, with no per-platform game listings, images/artwork, or updates/refresh functionality. If the true domain is Pipeworx data access, the surface is fairly complete, but as presented under Thegamesdb there are major gaps and a severe identity mismatch.

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