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Walkscore

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)

TDQS

A4.5/5.0
Behavior5/5

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

Beyond annotations (idempotentHint=true, readOnlyHint=false), the description adds key behavioral details: key-value scoping by identifier, persistence difference for authenticated vs anonymous sessions, and pairing with recall/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?

The description is concise (4 sentences) with a front-loaded main purpose. Every sentence adds value without redundancy or fluff.

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, the description sufficiently covers behavioral aspects (storage, scoping, persistence) and usage context. It is complete for a simple write tool.

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?

The schema already provides full descriptions for both parameters (key and value). The description adds minimal extra context (e.g., 'use when...'), but the schema bears the burden. Baseline 3 is appropriate.

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, using a specific verb ('save') and resource ('data'). It distinguishes from siblings 'recall' and 'forget', making its purpose unambiguous.

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 explains when to use ('when you discover something worth carrying forward') with concrete examples. While it mentions related tools, it lacks explicit 'when not to use' guidance, slightly lowering the score.

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

All Walkscore toolsInspect
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TDQS

A4.1/5.0
Disambiguation3/5

Tools are generally distinct but several clusters (ask_pipeworx family, polymarket family) have highly similar names that could cause confusion. For example, ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded all appear to do similar things with subtle differences. The agent would need to read descriptions carefully to pick the right one.

Naming Consistency4/5

Most tools follow a verb_noun pattern (e.g., compare_entities, resolve_entity, validate_claim). However, a few are single verbs (remember, recall, forget) or have inconsistent suffixes (ask_pipeworx_beta, walkscore_score). This is mostly consistent but not perfectly uniform.

Tool Count3/5

32 tools is quite high, bordering on excessive. While each tool serves a distinct purpose, the sheer number may overwhelm the agent. However, the tools cover a wide range of functionality, so the count is not unreasonable for a comprehensive data platform.

Completeness4/5

The tool set is comprehensive for querying data, conducting research, managing subscriptions, and evaluating bets. It includes meta-tools for discovery and memory. Notable gaps include user account management and direct file handling, but overall coverage is strong.

Resources