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Producthunt

by io.github.pipeworx-io

Top Launches

top_launches
Read-onlyIdempotent

Get today's and recent top Product Hunt launches — new product and startup launches. Use this to see what launched today/recently or which products are trending. Returns name, tagline, vote/comment counts, URLs, and topics. Example: top_launches({ first: 10, order: "RANKING" })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
firstNoNumber of launches to return (default 10, max 20)
orderNoSort order: "RANKING" (default — trending), "VOTES" (most upvoted), or "NEWEST" (most recently launched)
_apiKeyNoOptional — your own Product Hunt developer token for higher limits; omit to use the shared Pipeworx key.

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, non-destructive. Description adds value by listing specific return fields (name, tagline, votes, etc.) and providing an example call, enhancing 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?

Description is concise (3 sentences plus example) and front-loaded with key purpose. However, the example is repeated in both description and schema examples, slightly redundant.

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

Completeness4/5

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

No output schema, but description lists return fields. For a simple read tool with well-documented parameters and annotations, the description is sufficiently complete to guide agent invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with clear descriptions. Description reinforces meaning with an example call and explains order enum values (RANKING, VOTES, NEWEST) and their defaults, adding context beyond schema.

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?

Description clearly states the tool retrieves 'today's and recent top Product Hunt launches', specifies it's for new product/startup launches, lists return fields, and distinguishes itself from unrelated sibling tools.

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

Usage Guidelines4/5

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

Description explains when to use (to see launches, trending products) but does not explicitly state when not to use or provide alternatives. However, given sibling tools are unrelated, the guidance is clear enough.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Producthunt toolsInspect
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TDQS

A3.8/5.0
Disambiguation2/5

Several tools are functionally near-identical: ask_pipeworx_beta is explicitly a duplicate of ask_pipeworx (descriptions say they 'currently match exactly'), and ask_pipeworx_grounded differs only in answer-extraction mode. The six Polymarket tools (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread) heavily overlap on edge-finding and fill-risk, and ai_visibility_check duplicates scan_competitor_ai_presence's per-entity probing. Agents will frequently misselect among these.

Naming Consistency4/5

Naming is consistently snake_case with a mostly verb_noun pattern (get_post, top_launches, subscribe, forget, validate_claim, resolve_entity). Minor deviations exist where nouns lead (entity_profile, recent_changes, recent_alerts, bet_research), and polymarket_* names use a domain-prefix style rather than pure verb_noun, but the overall pattern is predictable and readable.

Tool Count2/5

33 tools is at the heavy end, and the count is badly mismatched to the server's stated identity: it is named 'Producthunt' yet only 2 of 33 tools (get_post, top_launches) are Product Hunt related — the rest are Pipeworx data lookup, prediction-market, memory, and subscription tools. The redundancy (duplicate ask_pipeworx_beta, overlapping polymarket tools) inflates the count without adding surface.

Completeness2/5

Judged against the Product Hunt domain implied by the server name, the surface is severely incomplete: coverage is limited to list-top-launches and get-one-post, with no search, users, comments, votes, collections, or categories — and no way to act on Product Hunt data at all. As a general Pipeworx data platform the coverage is broader, but for the named purpose there are large gaps that will force agent failures.

Resources