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Glama

Movies

by io.github.pipeworx-io

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. Added

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description adds useful context about scoping ('Scoped to your identifier') and listing behavior when the key is omitted. No contradictions with annotations; the added details enhance transparency beyond the structured data.

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, with the primary action stated first and no filler. Each sentence adds meaningful information: what it retrieves, when to use it, how it is scoped, and how it relates to sibling tools.

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 tool with a single optional parameter, no output schema, and safety annotations already present, the description covers all essential aspects: operation, use cases, scoping, and complementary tools. It leaves no significant gaps for an agent to misuse the 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?

The schema already fully documents the 'key' parameter, but the description reinforces and expands on its semantics by explaining that omitting it lists all saved keys and providing example values. This enriches the parameter meaning beyond the bare type/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 immediately states the core action: 'Retrieve a value previously saved via remember', with a clear alternative behavior of listing all keys when the key is omitted. It also distinguishes itself from sibling tools by referencing 'remember' and 'forget' explicitly.

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 concrete guidance on when to use this tool: 'Use to look up context the agent stored earlier', with examples like target ticker, address, and research notes. It also names the complementary tools ('Pair with remember to save, forget to delete'), making the workflow explicit.

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

A3.5/5.0
Disambiguation2/5

Many tools have heavily overlapping purposes—ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are nearly identical, while entity_profile, compare_entities, and recent_changes all pull overlapping company data. The server is named 'Movies' but only 4 of 35 tools relate to movies, making it impossible to infer what the tool set is actually for.

Naming Consistency2/5

Naming is a mix of verb_noun (search_movies, get_tv_schedule), bare nouns (remember, recall), brand prefixes (pipeworx_*, polymarket_*), and ad-hoc verbs (ask_pipeworx vs validate_claim). There is no consistent convention; even the pipeworx family uses ask_ vs grounded vs beta suffixes that don't follow a predictable pattern.

Tool Count2/5

35 tools is heavy for a single server, and for a 'Movies' server it is extreme overkill since the vast majority have nothing to do with movies. Even if the intent was a general data/betting server, 35 tools exceed the upper bound of the well-scoped range and would be better split into focused servers.

Completeness2/5

As a movies/TV server it is severely incomplete: there is no get_movie, no reviews, no watchlist, no person/actor search—only search_movies, search_tv_shows, get_tv_show, and get_tv_schedule. If instead the domain is Pipeworx data, coverage is better but still lacks mutation tools (e.g., no create/update for subscriptions beyond subscribe/unsubscribe) and the movie tools become dead weight.

Resources