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Glama

Congress

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. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Description adds context beyond annotations: scoping to identifier and pairing with remember/forget. No contradiction with annotations (readOnlyHint, idempotentHint, destructiveHint).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is slightly wordy but well-structured, front-loading the main purpose. Each sentence adds value, though a minor redundancy exists.

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 one optional parameter, no output schema, and rich description covering behavior, scoping, and pairing, no evident gaps remain.

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 covers 100% of parameters, but description adds value by explaining that omitting key lists all saved keys, augmenting the schema's 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?

Description clearly states the tool retrieves a previously saved value or lists all keys, with a specific verb (retrieve/list) and resource (memory key). It distinguishes from sibling tools like remember and forget.

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?

Description explicitly advises when to use the tool (look up stored context) and mentions it is scoped to an identifier. It does not explicitly state when not to use it, but the pairing with remember/forget provides implicit guidance.

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

All Congress toolsInspect
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TDQS

A3.9/5.0
Disambiguation2/5

Multiple tools occupy the same functional space: ask_pipeworx, ask_pipeworx_beta, ask_ipeworx_grounded, and deep_research all answer questions; disover_tools, suggest_questions, and pipeworx_trending all serve discovery; and five polymarket_* tools plus bet_research overlap heavily on prediction-market opportunity detection. The descriptions are detailed, but the boundaries are subtle enough that an agent can easily pick the wrong tool.

Naming Consistency4/5

The set is uniformly lowercase snake_case and uses recognizable prefixes such as ask_pipeworx, polymarket_, pipeworx_, and get_, which makes the naming fairly predictable. It is not a strict verb_noun convention — some names are noun phrases like entity_profile or ai_visility_check — but the overall style is consistent.

Tool Count2/5

With 36 tools, the surface is far heavier than the 'Congress' name suggests: only five tools are actually about congressional data, while the rest are general research, memory, subscription, and meta utilities. Many of these overlap, so the count feels bloated rather than well-scoped.

Completeness3/5

For Congress-specific work, the core needs are covered: search bills, get bill details, list members, and retrieve recent votes. However, deeper legislative operations like member voting records, committee actions, and amendments are missing, and the surrounding Pipeworx tools do nothing to close that gap. As a general data-research platform it is broad, but its actual 'Congress' identity feels incompletely realized.

Resources