Extract structured data from a URL using a Presence identity's session. Targets: meta (title/description/h1), text (full cleaned body text), links (all href+text), all (everything). CALL FORMAT: presence_extract({ identity_id: 'uuid', url: 'https://...', target: 'links' })
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL to extract data from. | |
| target | No | meta | text | links | all | |
| identity_id | Yes | Identity whose session to use. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions using a 'Presence identity's session' but does not clarify session prerequisites, whether the extraction is read-only, error behavior for invalid URLs, or any other side effects. The behavioral disclosure is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: a single sentence stating purpose, followed by a list of targets and a call format example. Every word is informative, and the structure is front-loaded with the core purpose. No unnecessary content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description does not explain the return format. It also fails to mention session validity requirements or error handling. For a tool with three simple parameters, this is sufficient to understand basic invocation, but it lacks detail on prerequisites and output structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema provides basic descriptions for all three parameters. The description adds value by explaining the meaning of each target option (e.g., 'meta (title/description/h1)') and includes a call format example. This additional context helps the agent understand parameter semantics beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool extracts structured data from a URL using a Presence identity's session. It lists the four target types (meta, text, links, all) with brief explanations. This distinguishes it from sibling presence tools like presence_screenshot, presence_navigate, etc., which serve different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly indicates usage for extracting structured content from a URL, but it does not explicitly state when to use this tool versus alternatives (e.g., presence_screenshot for visual capture, presence_navigate for navigation). No when-not-to-use guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Many tools have distinct purposes, but there are several overlapping or redundant tools (e.g., leadsignal vs leadsignal_generate, multiple code audit tools, multiple trading proposal/journal tools, and several 'universal' entry points like zambo_help, zambo_ask, zambo_universal). Descriptions help, but the volume creates ambiguity.
Naming conventions vary across prefixes (zambo_, zambot_, axis_, presence_, trading_, etc.), with some tools using single words (weather, translate) and others using verb_noun patterns. Aliases like leadsignal_generate for leadsignal break consistency. While prefixes provide some grouping, the overall pattern is mixed.
125 tools is excessive for a single MCP server, even if the server aims to be a universal stack. This makes it overwhelming for agents to navigate and increases the likelihood of misselection. Many tools could be split into domain-specific servers.
The tool surface is extraordinarily comprehensive, covering agent identity, cross-layer orchestration, code analysis, content generation, legal scanning, lead generation, trading, on-chain data, and more. Nearly any common agent task is supported with multiple tools, leaving few obvious gaps.