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Slack_connect

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 readOnly, idempotent, non-destructive. Description adds process details (fetches page, extracts title/description/key links) beyond annotations, no contradictions.

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?

Front-loaded with core purpose, then process, output format, and use cases – every sentence adds value, 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?

No output schema, but description clearly explains output as a text blob for site-root placement. Input parameters and behavior are fully covered. Complete for this tool's complexity.

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% and description adds no further parameter-specific details beyond what schema already provides. 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?

Clearly states the tool generates a llms.txt file for any URL, describes the output format and use cases, and distinguishes from siblings like scan_competitor_ai_presence.

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 three usage scenarios (client indexing, own project drafting, competitor auditing) though lacks explicit when-not-to-use examples.

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

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TDQS

B3.4/5.0
Disambiguation2/5

Many tools have overlapping purposes, particularly the multiple 'ask_pipeworx' variants and various Polymarket tools that serve similar functions. The lack of clear boundaries between data retrieval tools makes it difficult for an agent to choose the right one.

Naming Consistency2/5

Naming patterns are inconsistent: Slack tools use a 'slack_' prefix, while Pipeworx tools use a mix of verbs (ask_, validate_, resolve_) and nouns (entity_profile, bet_research). No uniform convention is applied across the set.

Tool Count3/5

With 36 tools, the count is high but not unreasonable for a comprehensive data platform. However, the inclusion of only 5 Slack tools in a server named 'Slack_connect' indicates a mismatch between tool count and intended purpose.

Completeness1/5

For a Slack integration, the tool surface is severely incomplete—missing core operations like creating channels, archiving, reactions, or message threading. The Pipeworx tools are extensive but unrelated to the server's stated purpose.

Resources