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Glama

Balldontlie

by io.github.pipeworx-io

Recall

recall
Read-onlyIdempotent

Retrieve a value previously saved via remember, or list all saved keys (omit the key argument). Use to look up context the agent stored earlier — the user's target ticker, an address, prior research notes — without re-deriving it from scratch. Scoped to your identifier (anonymous IP, BYO key hash, or account ID). Pair with remember to save, forget to delete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyNoMemory key to retrieve (omit to list all keys)

TDQS

A4.4/5.0
Behavior4/5

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

Beyond annotations (readOnlyHint, idempotentHint, destructiveHint), the description adds scoping details and pairing instructions. No contradictions with annotations.

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 concise sentences, front-loaded with the main action. Every sentence adds value: retrieval behavior, usage context, and relationship to sibling tools.

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?

Given simple tool with good annotations and schema, description covers purpose, usage, and behavioral context adequately. Absence of output schema is acceptable for a retrieval tool.

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 description for the single parameter. Description adds the important behavior that omitting key lists all keys, which is not in schema examples.

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 a value by key or lists all keys. It distinguishes itself from sibling tools 'remember' and 'forget' by focusing on retrieval, and uses specific verb 'retrieve' and resource 'value previously saved'.

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?

Provides explicit use case: look up stored context without re-deriving. Describes scoping (identifier-based) and pairs with remember/forget. Lacks explicit when-not-to-use, but context 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 Balldontlie toolsInspect
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TDQS

A3.5/5.0
Disambiguation2/5

Many tools have overlapping purposes, such as ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all performing similar data queries. Similarly, bet_research, polymarket_arbitrage, polymarket_edges, and polymarket_fill_risk cover the same betting domain. Players/player, teams/team, and games/game also blur distinctions.

Naming Consistency2/5

Naming styles are inconsistent: some use verb_noun (e.g., validate_claim, discover_tools), others are plain nouns (e.g., player, team, stats), and some are individual verbs (e.g., forget, recall). There's no predictable pattern.

Tool Count2/5

With 39 tools, the set is large and spans multiple unrelated domains (NBA stats, betting, general data lookup, memory). Given the server name 'Balldontlie' suggests NBA focus, the number is excessive and many tools feel out of place.

Completeness2/5

For an NBA stats server, the tool surface is incomplete (missing play-by-play, advanced stats, season leaders, etc.). As a general data server, it relies on meta-tools like ask_pipeworx rather than dedicated tools, so coverage is indirect and not comprehensive.

Resources