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Glama

Corporate Apology

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)

Schema Changelog

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

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
      +  {
      +    "key": "user_research_topic"
      +  },
      +  {}
      +]
  2. First observed

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already establish readOnly, idempotent, and non-destructive behavior. The description adds extra behavioral context beyond that: scoping to 'anonymous IP, BYO key hash, or account ID' and the listing behavior when key is omitted. This goes beyond the structured fields, though it doesn't cover edge cases like missing keys.

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 three sentences long, front-loaded with the primary action. Every sentence earns its place: definition of behavior, usage context, and relationship to siblings. There is no redundant or filler content.

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 low complexity (one optional parameter, no output schema), the description covers everything needed: what it retrieves, how to list, scoping, and how it fits with remember/forget. It is complete for an agent to invoke correctly without further assumptions.

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% for the single 'key' parameter, so baseline is 3. The description adds value by providing concrete examples of keys ('user's target ticker, an address, prior research notes') and explicitly linking parameter omission to listing all keys. This enriches the parameter's meaning beyond the schema's short description.

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: 'Retrieve a value previously saved via remember, or list all saved keys (omit the key argument).' It uses a specific verb and names the resource (saved values/keys), and explicitly contrasts itself with siblings remember and forget, leaving no ambiguity about its role.

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 usage context: '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.' It also differentiates from alternatives by saying 'Pair with remember to save, forget to delete,' giving clear when-to-use and when-not-to-use guidance.

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

A3.8/5.0
Disambiguation4/5

Most tools have clearly distinct purposes with detailed descriptions. Some overlap exists in the Polymarket-related tools, but each has a specific focus (arbitrage detection, edge scanning, persistence tracking, fill risk, cross-venue spread). The two ask_pipeworx variants are similar but differentiated by hallucination resistance.

Naming Consistency5/5

All tool names use lowercase with underscores, following a consistent pattern of verb_noun or noun_verb. Examples include 'ai_visibility_check', 'bet_research', 'entity_profile', and 'validate_claim'. There are no mixed conventions or erratic naming.

Tool Count2/5

The server is named 'Corporate Apology' but contains 31 tools, only one of which (corporate_apology_generate) relates to apologies. The vast majority are unrelated data retrieval and analysis tools, making the count excessive and poorly scoped for the server's stated purpose.

Completeness1/5

For a server focused on corporate apologies, the only tool is corporate_apology_generate. There are no tools for analyzing apology impact, managing crisis response, or tracking apologies. The tool surface is severely incomplete relative to the server's name.