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Glama

Ashby

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

A4.9/5.0
Behavior5/5

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

Description adds value beyond annotations: scoped by identifier, persistence details, and idempotent nature. No contradiction with annotations (readOnlyHint false, idempotentHint true).

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?

Three sentences, front-loaded with purpose, no wasted words. Every sentence adds value.

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 no output schema, description covers behavior, persistence, pairing, and usage scenarios. Complete for a simple key-value store 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 adequate descriptions. Description enhances with practical examples of keys (e.g., 'subject_property', 'target_ticker'), adding meaning beyond schema. Baseline 3, plus 1 for extra context.

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 saves data for reuse across conversations/sessions, using a specific verb-resource pair. It distinguishes from siblings like recall (retrieve) and forget (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?

Explicitly tells when to use: 'when you discover something worth carrying forward'. It describes pairing with recall and forget, and provides context on scoping and persistence (auth vs anonymous).

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

All Ashby toolsInspect
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TDQS

A3.5/5.0
Disambiguation2/5

Multiple tools have overlapping purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical variants; polymarket_edges, polymarket_arbitrage, polymarket_edge_tracker, polymarket_fill_risk, and polymarket_kalshi_spread all target prediction-market opportunities. Research tools like entity_profile, compare_entities, recent_changes, and validate_claim also blur together, making it hard to pick the right tool.

Naming Consistency2/5

Naming conventions are inconsistent: some tools use verb_noun (get_candidate, list_applications, remember), others use noun_verb (bet_research, entity_profile) or prefix-only patterns (ask_pipeworx, pipeworx_feedback, polymarket_edges). The Ashby tools use ashby_ prefix, but the rest mix pipeworx_, polymarket_, and bare names, with no uniform style.

Tool Count2/5

36 tools is excessive for a coherent server and spans unrelated domains: ATS (Ashby), data queries (Pipeworx), prediction markets (Polymarket), memory, subscriptions, and web utilities. This feels like a kitchen sink rather than a focused toolset, and the count alone makes selection overwhelming.

Completeness2/5

The Ashby ATS subset is incomplete: it provides get/list operations but no create, update, or delete for candidates or jobs, and no interview management. The broader server's scope is so mixed that each domain has obvious gaps, leaving agents unable to complete common workflows end-to-end.

Resources