Extract Metadata
extract_metadataRead-onlyIdempotent
Pull page metadata from HTML (keyless, offline): , meta description/keywords, and Open Graph (og:*) tags.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| html | Yes | The HTML. |
Htmltext
TDQS
A4.2/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds context beyond annotations by specifying the tool is offline, keyless, and extracts specific metadata. Annotations already indicate read-only, idempotent, non-destructive behavior. 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?
The description is one sentence, no wasted words, and front-loaded with the action verb. It efficiently conveys the tool's purpose and scope.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter, the description covers the main functionality and output types. It could mention the output format, but the purpose is clear given the tool name and sibling context.
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 a simple string parameter. The description does not add significant meaning to the parameter beyond what the schema 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?
The description clearly states the tool extracts specific metadata types (title, meta description/keywords, Open Graph tags) from HTML. It distinguishes from sibling tools like extract_links and html_to_text, which have different purposes.
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 implies the tool works offline and without keys, which guides usage context. However, it does not explicitly state when to use or not use this tool versus alternatives, though the specificity of metadata extraction is clear.
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.