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Glama

Pexels

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

A4.7/5.0
Behavior5/5

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

Beyond annotations (readOnlyHint=false, idempotentHint=true), the description adds key behavioral details: persistence scoped by identifier, authenticated vs anonymous retention periods (24 hours), and key-value storage semantics. No contradiction 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?

The description is concise (three sentences), front-loaded with the main purpose, and each sentence adds new information: what, when, and persistence details. No redundancy.

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?

For a simple two-parameter write tool with rich annotations and no output schema, the description covers use cases, persistence, scoping, and sibling relationships. Nothing essential is missing.

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% with both parameters well-described. The description reinforces but does not substantially extend parameter meaning beyond giving example keys and noting value is any text. Baseline 3 is appropriate.

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 tool's function: 'Save data the agent will need to reuse later.' It specifies the resource (key-value memory) and distinguishes itself from siblings by explicitly mentioning pairing with recall and forget.

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

Usage Guidelines5/5

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

The description provides explicit when-to-use guidance with concrete examples ('a resolved ticker, a target address, a user preference, a research subject') and contrasts with alternatives ('Pair with recall to retrieve later, forget to delete').

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

A3.9/5.0
Disambiguation3/5

Many tools are clearly from distinct domains (Pexels media, Pipeworx data, Polymarket betting, utility), but within each domain there is significant overlap (e.g., ask_pipeworx vs ask_pipeworx_grounded vs deep_research, or numerous polymarket tools). Detailed descriptions help differentiate, but some tools could still be confused.

Naming Consistency3/5

Naming conventions vary: some tools use verb_noun (ask_pipeworx, compare_entities), others are single-word (photo, video), and some mix patterns (photo_curated vs photo_search). The Pexels subset is consistent, but the overall set includes tools from other ecosystems with different styles.

Tool Count2/5

With 38 tools, the set is bloated for a Pexels server. Only 8 tools are actually Pexels-related; the rest are Pipeworx data query, Polymarket betting, and utility tools. This mismatch makes the count inappropriate for the stated server purpose.

Completeness4/5

For the Pexels domain, the tool set covers search, fetch, and collections for both photos and videos, which is adequate. The unrelated tools add bloat but don't create gaps in the Pexels functionality. Minor missing features like uploads or editorial content are not critical.

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