social_x_post_impactCorrelate an X (Twitter) post to a memecoin price impact. Fetches post metadata via oEmbed (no API key) and computes price delta from the pump.fun bonding curve in a ±windowMin window around the post.
| Name | Required | Description | Default |
|---|---|---|---|
| mint | Yes | Solana token mint address (base58) | |
| network | No | mainnet | |
| postUrl | Yes | X post URL (e.g. https://x.com/user/status/123) | |
| windowMin | No | ±window in minutes around the post time |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only and non-destructive; description adds context about data sources (oEmbed, pump.fun) and the time window. 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose, then method. No fluff or redundant information.
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?
Explains purpose, method, and key constraints (no API key, time window). Lacks output format details, but overall sufficient for a read-only computation tool with no output schema.
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 covers 3 of 4 parameters with descriptions; description explains windowMin as ±window and mentions oEmbed for postUrl, adding value. Network parameter lacks description but is covered by default and enum.
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 correlates an X post to a memecoin price impact, using specific methods (oEmbed, pump.fun bonding curve). This distinguishes it from siblings like get_bonding_curve or social_cashtag_sentiment.
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 implies usage for correlating a specific post to price impact and notes no API key is needed, but does not explicitly exclude alternatives or state 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.
Add one secure layer between your agents and this server.
Most tools have distinct purposes, but get_coin_intel and get_oracle_conviction overlap in providing intelligence signals; descriptions help differentiate but still may cause confusion.
Naming patterns are mixed: some use snake_case (get_bonding_curve), others use camelCase (sns_reverseLookup), and kol_leaderboard lacks a prefix that others like pumpfun_ have.
19 tools cover a broad range of pump.fun functionality, from token details to claims and social analysis; the count feels appropriate for the scope.
The tool set covers virtually all core aspects of pump.fun ecosystem: token info, intelligence, trading, claims, AMM quotes, metadata upload, SNS, and social sentiment, with no obvious gaps.