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Regulatory Catalysts

by io.github.pipeworx-io

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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

A4.8/5.0
Behavior5/5

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

Beyond annotations, discloses key behavioral traits: scoping by identifier, persistence differences between authenticated (permanent) and anonymous (24h) users. No contradiction with annotations.

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?

Front-loaded with main purpose, followed by usage context and storage details. Every sentence adds value; no superfluous content. Efficient and structured.

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?

No output schema, but description sufficiently covers storage semantics and pairing with recall/forget. Lacks mention of success/failure response, but acceptable for a simple store operation.

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?

With 100% schema coverage, baseline 3. Description adds meaningful examples for key and value beyond schema, e.g., 'subject_property', 'user_preference', and 'findings, addresses, preferences, notes'.

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?

Explicitly states the tool saves data for later reuse across conversations/sessions, with clear verb 'Save' and resource 'data'. Distinguishes from siblings like recall 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 Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit guidance on when to use ('when you discover something worth carrying forward') with concrete examples (resolved ticker, target address). Names alternatives recall and forget for complementary actions.

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

All Regulatory Catalysts toolsInspect
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TDQS

A3.9/5.0
Disambiguation4/5

Most tools have distinct purposes, but the ask_pipeworx variants (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) and multiple Polymarket tools (bet_research, polymarket_edges, polymarket_arbitrage, etc.) could cause confusion for an agent selecting the appropriate tool.

Naming Consistency2/5

Tool names mix snake_case and camelCase inconsistently, with no strong verb_noun pattern. Examples include 'ask_pipeworx' vs 'discover_tools' vs 'validate_claim', indicating a lack of naming convention.

Tool Count2/5

33 tools is high for a single server, including many utility tools (memory, subscriptions) that seem peripheral to the core regulatory/data domain. This suggests scope creep and could overwhelm agents.

Completeness4/5

The tool set covers a wide range of regulatory and financial data needs, including company profiles, entity comparison, claim validation, FDA catalysts, and prediction market analysis. Minor gaps exist (e.g., no tool for editing data), but overall it is comprehensive for its stated purpose.

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