Extract Links
extract_linksRead-onlyIdempotent
Extract all hyperlinks from HTML as {href, text} pairs (keyless, offline).
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| html | Yes | The HTML. |
Htmltext
TDQS
A4.1/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description adds 'keyless, offline' beyond annotations, indicating no API keys needed and no network calls. Annotations already cover readOnly and idempotent, so description enriches behavioral context.
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 sentence, direct, and front-loaded with purpose. No redundant 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?
Simple tool with one parameter, full annotations, and output described in the description. No missing information for correct 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?
Single parameter 'html' with baseline coverage 100%. Description adds no extra meaning beyond 'the HTML' and the tool's purpose; schema does the heavy lifting.
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 clearly states the verb 'extract' and resource 'hyperlinks from HTML', with output format '{href, text} pairs'. Distinguishes from sibling tools like 'extract_metadata' and 'html_to_text'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implied usage is clear (extract links from HTML), but no explicit guidance on when to use versus alternatives or when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Try in Browser
Glama MCP Gateway
Add one secure layer between your agents and this server.
TDQS
A4.1/5.0
Disambiguation3/5
Several tools form overlapping clusters (ask_pipeworx/ask_pipeworx_beta/ask_pipeworx_grounded, the five polymarket_* tools, and discover_tools vs suggest_questions) that could cause misselection on first glance. The detailed descriptions mostly clarify the boundaries, but the overlaps are real and require careful reading.
Naming Consistency4/5
The naming is overwhelmingly snake_case with a verb_noun pattern (ask_, extract_, generate_, list_, resolve_, subscribe), which is predictable. A few noun-style or special-form names (entity_profile, html_to_text, recent_changes, polymarket_edges) break the pattern, but these are minor deviations.
Tool Count2/5
At 34 tools the surface is heavy, especially for a server named 'Htmltext' where only 4 of 34 tools relate to HTML. Even accounting for the broad data/research domain, the set includes several redundant research and Polymarket helpers that push it past a well-scoped count.
Completeness4/5
The major subdomains are well covered: HTML extraction, entity/data research, prediction-market analysis, memory, and subscriptions all have the core operations needed with no obvious dead ends. Some niches are shallow (HTML lacks a general fetch/render tool; scan_dependency is a one-off), but agents can work around these gaps.