tldr_textSummarize a URL or pasted text into 3-5 concise bullets. $0.01 USDC.
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | URL to fetch and summarize. Provide either text or url. | |
| text | No | Pasted text to summarize. Provide either text or url. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / text / descriptionAdded value: +"Pasted text to summarize. Provide either text or url."Input schema / properties / url / descriptionAdded value: +"URL to fetch and summarize. Provide either text or url."Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the output format (3-5 bullets) and the cost, adding value beyond the readOnlyHint annotation. It does not mention failure modes or edge cases (e.g., if both url and text are provided), but given the read-only nature, the transparency is adequate.
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 concise, consisting of two short sentences. It conveys all necessary information without fluff or unnecessary detail.
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?
The description is complete for its purpose: it explains the input (URL or text), the action (summarize), and the output (3-5 bullets). It could mention potential errors or the requirement of at least one input, but these are implied by the parameter descriptions.
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 coverage is 100% since both parameters have descriptions ('URL to fetch and summarize...' and 'Pasted text to summarize...'). The tool-level description adds no extra parameter semantics, so the baseline score of 3 is appropriate.
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?
The description clearly states the tool's function: summarizing a URL or pasted text into 3-5 concise bullets. It distinguishes itself from sibling tools like token_price or screen_wallet by indicating a summarization action.
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?
It specifies when to use the tool (when summarizing a URL or text) and mentions a cost consideration ($0.01 USDC), which helps with decision-making. However, it does not explicitly state when not to use it or alternative tools that might be more appropriate.
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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Each tool targets a clearly distinct function — anchoring, decoding, wallet intelligence, entertainment, etc. Even similar tools like decode_calldata vs decode_tx and intel_wallet vs screen_wallet are precisely separated by descriptions.
Most names follow a verb_noun pattern (anchor_hash, decode_calldata), but there are exceptions like aura_read (noun_verb), intel_wallet (noun_noun), and ledger_report (ambiguous). This mixed convention is readable but not fully consistent.
18 tools is slightly above the ideal range but not overwhelming. Each tool serves a specific purpose, and the count feels reasonable for the broad set of utilities offered.
The core utilities (anchoring, wallet intelligence, ledger accounting) are well-covered without obvious dead ends. Some domain-specific workflows could be expanded (e.g., verifying anchors), but the existing tools provide complete standalone operations.