Skip to main content
Glama

Stat Lv

by io.github.pipeworx-io

Remember

remember
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?

The description adds valuable behavioral context beyond annotations: memory is 'scoped by your identifier,' authenticated users get persistent memory, anonymous sessions retain for 24 hours. This complements the idempotentHint and destructiveHint annotations without contradicting them.

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 yet information-dense, with three sentences that front-load the purpose and follow with usage, persistence, and pairing. Every sentence serves a distinct function with 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 2-parameter write tool with rich annotations and full schema coverage, the description completely covers when to use, how data is stored, and how it relates to sibling tools. No output schema is needed for a store operation, so its absence is not a gap.

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% with detailed descriptions for both 'key' and 'value.' The description does not add parameter-specific semantics beyond the schema, but it does reinforce the key-value nature and gives examples in context. Baseline of 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.' The verb 'save' plus resource (key-value memory) is specific, and it distinguishes itself from siblings by explicitly mentioning 'Pair with recall to retrieve later, forget to delete.'

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?

Explicit usage guidance is provided: 'Use when you discover something worth carrying forward' with concrete examples (ticker, address, preference). It also mentions persistence differences for authenticated vs anonymous users, and names companion tools (recall, forget) for related operations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Stat Lv toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.8/5.0
Disambiguation3/5

Several tools form overlapping families (ask_pipeworx/ask_pipeworx_beta/ask_pipeworx_grounded/deep_research, plus the six polymarket_* tools), and ask_pipeworx_beta is currently an exact behavioral duplicate. The long descriptions usually disambiguate them, but an agent could still struggle to quickly choose between similar research and edge-detection tools.

Naming Consistency3/5

Names are uniformly snake_case and prefix families like pipeworx_* and polymarket_* help, but there is no consistent verb_noun pattern: subjects, table_meta, recent_alerts, and entity_profile are noun phrases while remember, generate_llms_txt, and compare_entities are action-first. The mixed conventions are readable but less predictable than a uniform pattern.

Tool Count2/5

34 tools is well into the 'too many' range for a single tool set, even if each is individually documented. Several could plausibly be consolidated, such as ask_pipeworx_beta, the polymarket edge tools, and the AI-visibility pair.

Completeness4/5

For its broad stated purpose, the set covers the full lifecycle: lookup/research, entity profiles, comparisons, claim validation, prediction-market edge analysis, memory, subscriptions, and discovery. Minor gaps exist, such as no direct fetch-by-URI tool or subscription update path, but most workflows have a clear route.

Resources