HyperXosist-Agent Remote MCP
Server Details
X feedback discovery, noise-reduced query planning, signal filtering, and AI handoffs.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 4/5 across 3 of 3 tools scored.
Each tool has a distinct, non-overlapping purpose: search planning, signal filtering, and handoff building. Descriptions explicitly clarify boundaries.
All tools follow a consistent verb_noun pattern with the server prefix, making the set predictable and easy to navigate.
With 3 tools, the set is well-scoped for a specialized analysis workflow, not too few or too many.
The tools cover the full intended lifecycle: planning searches, filtering signals from collected data, and building structured handoffs. No obvious gaps given the stated scope.
Available Tools
3 toolshyperxosist_build_handoffARead-onlyIdempotentInspect
Use to turn previously collected X feedback into a structured Signal-to-Fix package and coding-agent prompt. It does not perform general summarization, search the web, scrape X, or modify source code.
| Name | Required | Description | Default |
|---|---|---|---|
| feedback | Yes | Previously collected X feedback text. | |
| productName | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| type | Yes | |
| handoff | Yes | |
| agentPrompt | Yes | |
| signalToFixInput | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds behavioral traits beyond annotations, such as clarifying it does not perform general summarization, web search, scraping, or code modification. The annotations (readOnlyHint=true, idempotentHint=true, destructiveHint=false) are consistent with the description. It could further disclose whether the tool stores any state or output.
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 with two sentences: one for purpose and one for exclusions. No unnecessary words, and the information is front-loaded.
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 the tool's low complexity (2 required params, no enums, output schema exists), the description provides sufficient context about input and behavior. It could mention the existence of the output schema for completeness, but is otherwise adequate.
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 description coverage is 50% (only 'feedback' parameter has description). The tool description reinforces that the input is 'previously collected X feedback', which aligns with the feedback parameter. However, the 'productName' parameter lacks description in both schema and tool description, leaving ambiguity about its format or constraints.
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 uses a specific verb ('turn') and resource ('previously collected X feedback') to clearly state the tool's purpose. It explicitly distinguishes itself from sibling tools by listing what it does not do (general summarization, web search, scrape X, modify source code).
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 provides clear context for when to use the tool (when you have previously collected X feedback to transform into a structured package) and excludes unrelated actions. However, it does not explicitly mention when to use sibling tools like hyperxosist_filter_signals or hyperxosist_search_plan as alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hyperxosist_filter_signalsARead-onlyIdempotentInspect
Use after X posts or tweet text have already been collected. Separates actionable bugs, feature requests, and UX friction from empty praise, engagement bait, and spam. It does not fetch, scrape, or search X.
| Name | Required | Description | Default |
|---|---|---|---|
| feedback | Yes | Previously collected X post text to classify in memory. |
Output Schema
| Name | Required | Description |
|---|---|---|
| keep | Yes | |
| type | Yes | |
| discard | Yes | |
| summary | Yes | |
| keepCount | Yes | |
| discardCount | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint. The description adds that it classifies data in memory and does not fetch/scrape/search, which aligns with annotations. No additional behavioral traits disclosed beyond what annotations imply.
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 concise sentences: first sets usage precondition, second specifies classification targets and exclusions. No fluff, front-loaded with key 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?
Given the simple parameter structure and existence of an output schema, the description covers usage context, purpose, and constraints. Could briefly hint at output format, but output schema fills that gap.
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 full description for the single parameter (feedback). The tool description reinforces that it handles already-collected text, but adds no new parameter-level insight beyond what the schema already offers.
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 separates actionable signals (bugs, feature requests, UX friction) from non-actionable (praise, spam), and explicitly distinguishes it from fetch/scrape/search tools. This contrasts well with sibling tools (build_handoff, search_plan).
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?
Explicitly says 'Use after X posts or tweet text have already been collected' and clarifies what it does not do, providing clear context for when to use. However, it does not name sibling tools explicitly as alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hyperxosist_search_planARead-onlyIdempotentInspect
Use only for specialized X (Twitter) research planning: complaints, bug reports, feature requests, product feedback, or community signals. Builds multiple noise-reduced official x.com/search URLs and quality scores. It is not general web search and does not scrape X or collect posts.
| Name | Required | Description | Default |
|---|---|---|---|
| intent | Yes | An X-specific research goal, for example: Find user complaints and bug reports on X about Acme. |
Output Schema
| Name | Required | Description |
|---|---|---|
| type | Yes | |
| mission | Yes | |
| queries | Yes | |
| missionId | Yes | |
| searchUrls | Yes | |
| paymentPolicy | Yes | |
| qualityScores | Yes | |
| estimatedCostUsd | Yes | |
| requiresPaymentForAutomatedProductionUse | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint=true, etc.), the description discloses that it builds noise-reduced URLs and quality scores, and clarifies it does not scrape or collect posts. This adds useful 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with front-loaded purpose, followed by outcome and exclusions. No redundant or unnecessary 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?
The description covers the tool's purpose, scope, output (URLs and scores), and boundaries (no scraping). With a single parameter and existing output schema, it provides sufficient context for an agent to decide when to use this tool.
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?
The schema coverage is 100% and the description adds an example ('Find user complaints and bug reports on X about Acme') that clarifies the parameter's intent beyond the schema definition.
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 is for specialized X (Twitter) research planning, listing specific use cases (complaints, bug reports, etc.) and what it builds (URLs and quality scores). It distinguishes from general web search and scraping, but does not explicitly differentiate from siblings.
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 provides guidance on when to use (only for X research planning) and when not to use (not general web search). However, it does not explicitly compare with sibling tools or give exclusions for alternative tools.
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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