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Dart Kr

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

A4.9/5.0
Behavior5/5

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

Annotations declare idempotentHint=true, destructiveHint=false, and readOnlyHint=false, which align with the description's claim of a non-destructive write operation. The description adds valuable behavioral context: memory is key-value scoped by identifier, authenticated users get persistent memory, anonymous sessions retain 24 hours.

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 a concise, well-structured paragraph. It front-loads the core purpose, then gives usage guidelines, and ends with behavioral details. No unnecessary words or repetition.

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 the tool's low complexity (2 parameters, no output schema, no nested objects), the description covers all essential aspects: purpose, usage, storage behavior, scoping, persistence, and companion tools. No gaps.

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 coverage is 100% and the description already explains the key-value pair concept. The description adds examples of key naming conventions (e.g., 'subject_property', 'target_ticker'), which provides extra semantic guidance.

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 explicitly states the tool saves data for later reuse and provides concrete examples (resolved ticker, target address, user preference, research subject). It also distinguishes from sibling tools 'recall' and 'forget' by naming them as companions.

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?

Clearly specifies when to use ('when you discover something worth carrying forward') and explicitly mentions alternatives: 'Pair with recall to retrieve later, forget to delete.'

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
Disambiguation2/5

Multiple tools overlap heavily: ask_pipeworx_beta deliberately matches ask_pipeworx exactly right now, discover_tools and suggest_questions both serve as what-can-I-do entry points, and ai_visibility_check is just the single-entity version of scan_competitor_ai_presence. An agent will struggle to pick the right variant without carefully reading long descriptions.

Naming Consistency3/5

All tools are snake_case and several families share clear prefixes (dart_*, polymarket_*, ask_pipeworx_*), but the overall set mixes verb_noun (discover_tools, validate_claim), noun_phrase (entity_profile, deep_research), bare verbs (remember, recall, forget), and prefix-noun (dart_financials). Readable but not unified.

Tool Count2/5

36 tools is far above the 25+ heavy threshold, and the count is inflated by redundancy: ask_pipeworx_beta is a literal duplicate today, suggest_questions overlaps discover_tools, and ai_visibility_check is subsumed by scan_competitor_ai_presence. The broad Pipeworx platform justifies many tools, but the exposed surface is bloated.

Completeness4/5

The surface covers the apparent domain well: universal querying (ask_pipeworx family + deep_research), tool discovery, entity resolution, profiles, comparisons, change feeds, claim verification, Korean DART filings, Polymarket analysis/fill-risk, memory, subscriptions, and feedback. Minor gaps remain—there's no explicit fetch-by-citation-URI tool despite claims those URIs are fetchable, and no way to retrieve full DART filing text beyond discovery.

Resources