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Yc Rejection

by io.github.pipeworx-io

What Can I Ask Pipeworx?

suggest_questions
Read-onlyIdempotent

What can I ask Pipeworx? / what is Pipeworx good for? / what can you do? / give me ideas / show me examples / getting started / what data do you have? — the onboarding entry point for an agent that just connected and wants to know what is worth asking. Returns category-bucketed example questions (company financials, drugs & clinical trials, economics, real estate, prediction markets, weather, government & patents, science & academia, news) — each with the exact tool + argument shape that answers it, drawn from the live catalog of thousands of tools. Call with no arguments for the full spread, or pass topic (e.g. "finance", "pharma", "betting") to focus. Use this FIRST when you do not yet know what Pipeworx can do for you, or to learn how to call the meta-tools (ask_pipeworx, entity_profile, compare_entities, etc.).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicNoOptional focus area: finance | pharma | economics | real-estate | betting | weather | government | science | news. Omit for a cross-category spread.

TDQS

A4.6/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds context about the output format and that it draws from a live catalog, providing transparency beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is lengthy but well-structured, front-loading the purpose and using bullet-style listing of topics. Every sentence adds value, though some redundancy exists with the schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite no output schema, the description fully explains the return value (category-bucketed examples with tool details), parameter behavior, and use case. It is complete for an onboarding tool.

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?

The schema coverage is 100% and the description doesn't add significant meaning beyond the schema's description of the topic parameter. The schema already lists the allowed values and usage.

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's purpose: an onboarding entry point that returns category-bucketed example questions with tool+argument shapes. It distinguishes itself from siblings like ask_pipeworx by focusing on suggesting questions rather than answering them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says when to use this tool: 'Use this FIRST when you do not yet know what Pipeworx can do for you, or to learn how to call the meta-tools.' It also mentions passing a topic to focus and lists alternatives (ask_pipeworx, entity_profile, etc.).

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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TDQS

B3.3/5.0
Disambiguation2/5

Many tools have overlapping purposes, e.g., multiple ask_pipeworx variants and several Polymarket analysis tools. The presence of meta-tools like discover_tools and suggest_questions adds confusion. Distinguishing between tools like entity_profile, compare_entities, and recent_changes requires careful reading of descriptions.

Naming Consistency2/5

Naming conventions are mixed: some use snake_case (ai_visibility_check, ask_pipeworx), others use underscores (compare_entities, deep_research). Prefixes like pipeworx_ and polymarket_ are inconsistently applied, and there is no clear verb_noun pattern across the set.

Tool Count2/5

With 32 tools, the server is heavily over-scoped for its name 'Yc Rejection'. Only one tool directly relates to that domain. The rest constitute a full data platform, making the count far too high for the implied narrow purpose.

Completeness1/5

For a server named 'Yc Rejection', the tool set is severely incomplete: only one tool generates rejection text. There are no tools for application management, review, or related tasks. The actual completeness of the underlying platform is irrelevant given the misleading name.

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