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Glama

Cricket

by io.github.pipeworx-io

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Idempotent

Save data the agent will need to reuse later — across this conversation or across sessions. Use when you discover something worth carrying forward (a resolved ticker, a target address, a user preference, a research subject) so you don't have to look it up again. Stored as a key-value pair scoped by your identifier. Authenticated users get persistent memory; anonymous sessions retain memory for 24 hours. Pair with recall to retrieve later, forget to delete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesMemory key (e.g., "subject_property", "target_ticker", "user_preference")
valueYesValue to store (any text — findings, addresses, preferences, notes)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

The description adds important behavioral context beyond annotations: scoping by identifier, persistence differences between authenticated and anonymous sessions (24h TTL), and pairing with recall/forget. This enriches the agent's understanding of side effects and lifecycle.

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?

Five concise sentences, each earning its place: purpose, usage timing, storage mechanism, persistence details, pairing instructions. No wasted words.

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?

Given the tool's simplicity and the rich annotations/schema, the description fully covers what an agent needs to use the tool correctly: when, how, scope, TTL, and related tools.

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 100% and includes meaningful examples. The description confirms key-value structure but does not add significant new meaning beyond what the schema already provides.

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 verb ('Save data') and resource ('key-value pair') with explicit purpose: reuse later across conversations or sessions. It distinguishes itself from siblings by naming recall and forget as complementary 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?

The description tells when to use it (discover something worth carrying forward) and provides alternatives (recall, forget). However, it does not explicitly state when not to use 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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TDQS

A3.6/5.0
Disambiguation2/5

The set mixes several near-overlapping tools: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, current_matches and match_scores largely duplicate each other, and the Polymarket family (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_fill_risk) has fuzzy boundaries. Long descriptions help, but an agent would often need to read deeply to pick the right tool.

Naming Consistency3/5

Most names are lowercase snake_case, but conventions vary: some are verb_noun (ask_pipeworx, scan_dependency, compare_entities), some are noun phrases (current_matches, match_info, entity_profile), and there are mixed prefixes (pipeworx_*, polymarket_*, plain names). It is readable but not a coherent naming system.

Tool Count2/5

35 tools is heavy, and only four of them (current_matches, match_info, match_scores, search_players) relate to the server's apparent cricket purpose. The rest are a sprawling general-purpose data/research/prediction-market/utility toolkit, making the surface feel bloated and off-scope.

Completeness2/5

As a cricket server, the surface is shallow: it has live matches, scores, match info, and player search, but no player stats, batting/bowling figures, team profiles, series/schedules, or historical match data. The many unrelated tools do not fill these obvious cricket-domain gaps.

Resources