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anansi_free_data

FREE. Anansi's free data: action=catalog (free endpoints + datasets) | search (q: resolve model/dataset names) | price_current (model_id: current per-token LLM prices) | price_changes_recent (days<=7: LLM price changes) | sample (dataset: a few raw rows). Only free routes are proxied.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoname fragment (search)
daysNo
limitNo
actionNo
datasetNodataset name (sample), e.g. cloud_spot
model_idNomodel id substring (price_current)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, and it does disclose two real behavioral facts: the tool is free and only free routes are proxied. It says nothing about rate limits, auth requirements, error behavior, or whether returned data is live versus cached.

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?

A single dense sentence with pipe-delimited action summaries — front-loaded and waste-free for a five-action dispatcher. The density trades some readability, but every clause carries information.

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

Completeness3/5

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

For a six-parameter, action-dispatching tool with no annotations and no output schema, the description covers actions and most parameters but omits limit and gives no sense of return shape or pagination for list-style actions like catalog or search.

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 coverage is 50%, and the description compensates partially by mapping q, model_id, and dataset to their actions and adding the days<=7 cap that the schema omits. However, the limit parameter is never mentioned anywhere, leaving one of six parameters undocumented in both places.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names the resource (Anansi's free data) and enumerates the five actions it supports, each with its key parameter, so an agent can tell what the tool returns for each mode. It also distinguishes scope with 'Only free routes are proxied', though it never states what the broader data source is or how it differs from the many unrelated siblings.

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

Usage Guidelines3/5

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

The action list implies when each mode applies (catalog for discovery, search for name resolution, price_current/price_changes_recent for pricing), which is useful routing. But there is no explicit when-not guidance and no named alternative for paid data — 'only free routes are proxied' hints at an alternative without identifying it.

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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