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Glama

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)

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds context on how the retrieval works (omit key to list all keys, scoping to identifier, and pairing with remember/forget). No contradictions.

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 that front-load the action, follow with use cases and alternatives, and end with scoping. Every sentence adds value; no fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given a single parameter, high schema coverage, and clear annotations, the description covers purpose, usage, and behavior. It lacks return format details, but without an output schema, this is acceptable. It could mention pagination or limits for listing many keys.

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 a clear parameter description. The description reinforces that omitting the key lists all keys, which is already in the schema. It adds minimal new meaning beyond the schema.

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 (retrieve/list), resource (saved memories), and distinguishes from sibling tools (remember, forget). It provides concrete use cases (target ticker, address, notes) and explicitly contrasts with the alternative of re-deriving context.

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 explicitly says when to use the tool (look up stored context) and mentions sibling tools for complementary actions (save, delete). It also notes scoping to the agent's identifier, but does not explicitly state when not to use it, which would elevate the score to 5.

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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Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.6/5.0
Disambiguation2/5

The server includes many overlapping tools (e.g., multiple ask_pipeworx variants, epa_regulation vs. epa_search vs. discover_tools). More critically, the tool set covers vastly different domains (Polymarket bets, npm packages, AI visibility, memory storage) alongside EPA regulations, making it hard for an agent to distinguish purposes.

Naming Consistency2/5

Tool names use a mix of styles: underscore (epa_regulation, ask_pipeworx), camelCase (deep_research, suggest_questions), and verb phrases (scan_competitor_ai_presence). No consistent pattern is followed across the set.

Tool Count2/5

33 tools is high for a server named 'Epa Regulations'. The vast majority are unrelated to EPA regulations (e.g., Polymarket, npm scanning, memory functions), making the scope mismatched. A focused server should have fewer, domain-specific tools.

Completeness1/5

For a server claiming to be about EPA regulations, only two tools (epa_regulation, epa_search) are directly relevant. The rest are from unrelated domains, leaving severe gaps in expected functionality like rule updates, compliance checks, or cross-referencing with other environmental data.