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Cactus

by io.github.pipeworx-io

Remember

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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

A4.4/5.0
Behavior4/5

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

Annotations already cover idempotency and non-destructiveness. The description adds valuable context about scoping by identifier and persistence behavior (24 hours for anonymous sessions, persistent for authenticated users). It does not contradict annotations.

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?

Four sentences, front-loaded with the primary purpose. The examples and usage guidance earn their place, though slightly verbose in listing cases; still well-structured.

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 simple key-value write tool with complete schema coverage and no output schema, the description covers use cases, persistence, scoping, and sibling relationships. No critical gaps remain.

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 description coverage is 100% for both parameters, with examples in the schema. The description only reinforces the key-value concept without adding new parameter-specific details, so the baseline 3 applies.

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 uses a specific verb ('Save') and a clear resource ('data... key-value pair'), and explicitly states the scope ('across this conversation or across sessions'). It also distinguishes from siblings by mentioning 'Pair with recall to retrieve later, forget to delete.'

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 an explicit 'Use when' list with concrete examples (resolved ticker, target address, user preference, research subject), and directly names alternative tools for related operations (recall, forget).

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

A3.9/5.0
Disambiguation3/5

Most tools have clearly differentiated roles, but several pairs blur boundaries: ask_pipeworx and ask_pipeworx_beta are currently functionally identical, and identify vs resolve both wrap the same NCI CACTUS service. The detailed descriptions rescue most selections, but an agent could easily mispick between the research and chemical lookup options.

Naming Consistency3/5

Names are mostly snake_case and readable, but conventions are mixed: some are verb-first (ask_pipeworx, validate_claim, search_within) while many are noun-first or domain-prefixed (entity_profile, polymarket_edges, recent_changes, pipeworx_trending). There is no single predictable pattern for a new tool's name, though subfamilies (polymarket_*, ask_pipeworx_*) are internally consistent.

Tool Count3/5

At 33 tools, this is well above the typical well-scoped range and carries real selection overhead. The unusually broad purpose—a data router plus prediction-market analysis, memory, subscriptions, and several standalone utilities—partially justifies the count, but it still feels heavy and could be consolidated.

Completeness4/5

For its varied subdomains, coverage is strong: memory has remember/recall/forget, subscriptions have subscribe/unsubscribe/list/recent_alerts, and prediction markets span research, edge scanning, arbitrage, fill-risk, and edge telemetry. Minor gaps exist—such as no direct tool to fetch a specific citation URI by identifier, and the redundant stable/beta router pair—but there are no obvious dead ends.

Resources