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ScrapeMole Social: Telegram, Bluesky, Mastodon, Hacker News and Lobsters data for AI agents: Lobsters hottest / newest

lobsters_hot
Read-onlyIdempotent

Use to see what programmers on Lobsters are discussing right now: returns up to 25 stories from the hottest or newest page, optionally filtered to one tag, with title, URL, score, comment count, tags, submitter and time. Paid tool: x402 USDC on Base, $0.002 per successful call; call without payment to receive the PaymentRequired object.

Input Schema

NameRequiredDescriptionDefault
tagNoOptional tag, e.g. rust, ai, security.
listNo"hottest" or "newest".hottest
limitNoMax stories (1-25).25

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already declare readOnly/openWorld/idempotent, and the description adds genuinely new behavioral facts they cannot convey: the hard 25-story ceiling, the live 'right now' freshness, the exact per-call price ($0.002 USDC on Base), the x402 payment mechanism, and the failure mode of calling unpaid (returns a PaymentRequired object). This is exactly the kind of cost/auth disclosure an agent needs before invoking.

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

Conciseness5/5

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

Two sentences, front-loaded with the purpose, then output shape, then cost/payment. No filler; the long payment clause is dense with required operational information rather than padding.

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?

With no output schema, the description usefully enumerates the returned fields (title, URL, score, comment count, tags, submitter, time). All three parameters are covered by the schema, and the payment/auth model — the biggest risk of misfire for an agent — is fully explained.

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?

Schema description coverage is 100%, so tag, list, and limit are already documented in the schema with defaults and range. The description only echoes them ('optionally filtered to one tag', 'up to 25 stories'), adding no syntax, validation, or semantic detail beyond the schema — the baseline 3 for full coverage.

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?

States a specific verb and resource ('returns up to 25 stories from the hottest or newest page') plus the exact scope (Lobsters, optional single-tag filter) and the fields returned. Since no sibling covers Lobsters, the platform name alone cleanly separates it from the bluesky_*/hn_*/mastodon_*/telegram_* 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?

'Use to see what programmers on Lobsters are discussing right now' gives a clear use context, and the description distinguishes the hottest vs newest pages that the `list` parameter selects. It never states when NOT to use it or names an alternative (e.g., the other platform feeds) for different data sources.

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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